Carolina Ruiz

CURRICULUM VITA
April 2019

Department of Computer Science	Phone: (508) 831-5640
Worcester Polytechnic Institute	Fax: (508) 831-5776
Worcester, MA 01609	email: ruiz@wpi.edu
U. S. A.	URL= http://www.cs.wpi.edu/~ruiz/

• Media Coverage:

  • Media Coverage of my Research

• Research on Machine Learning in Medicine:

  In collaboraton with Univ. Massachusetts Medical School, Univ. of Connecticut Medical School, and Boston College

  • Research on Machine Learning in Human Sleep:

    • Research on Interpretable Deep Learning on Human Sleep:
      • BIOKDD 2018, in conjunction with the KDD2018 conference
      • Deep Learning Day at the KDD 2018 conference
      • Health Day at the KDD 2018 conference
      • IEEE/ACM Transactions on Computational Biology and Bioinformatics article. In press, pre-print available here. 2019.

    • Research on Modeling and Clustering of Human Sleep Time Series

    • Media coverage of my sleep research.

  • Research on Machine Learning in Behavioral Medicine and Mobile Health:

    • Machine learning algorithms for predicting and preventing overeating:
      • HICSS-2017, European Journal on Nutrition, WISH-AMIA-2017.
      • Research featured in numerous TV, radio, newspapers and online news outlets

    • Machine learning algorithms for improving sleep behavior and health:
      • HICSS-2018, HICSS-2017, AMCIS 2016.

  • Research on Predictive Modeling of Stroke Patient Outcomes

  • Research on Predictive Modeling in Gastrointestinal Cancer

  • Invited Co-Editor of the special issue on "Wearable Sensor Signal Processing for Smart Health" of Elsevier's Smart Health Journal.

  • Program Co-Chair of the 9th International Conference on Health Informatics (HEALTHINF2016), Rome, Italy February 2016.

• Other Machine Learning Research:

  • Ensemble ('Meta') Learning Algorithms

  • Machine Learning Algorithms for Gene Expression Analysis

  • Machine Learning Algorithms for Electronic Commerce

  • Machine Learning Algorithms for Intelligent Tutoring Systems

• Interdisciplinary Biology - Computer Science Research

  • Co-PI in National Science Foundation STEM+C grant NSF#1742446. "Building Educational Bridges between Computer Science and Biology through Transdisciplinary Teamwork and Modular Curriculum Design". $1,228,848. Sept. 2017 - Aug. 2021.
    • Media coverage of this grant.

  • Research on Computational Methods to Study Biodiversity:
    • Media coverage of this research.
   

  Education and Professional Experience

  
  EDUCATION
  
  

  Ph.D. in Computer Science. 1996
  University of Maryland College Park.

  MS in Computer Science. 1990
  University of The Andes. Bogotá, Colombia.

  BS in Mathematics. 1989
  University of The Andes. Bogotá, Colombia.

  BS (5 year degree) in Computer Science. 1988
  University of The Andes. Bogotá, Colombia.

  
  CURRENT POSITION
  
  

  Associate Dean of Arts and Sciences, 2021-Present
  WPI's School of Arts & Sciences

  Professor, Since 2020
  Harold L. Jurist '61 and Heather E. Jurist Dean's Professor Since 2021
  Department of Computer Science
  Worcester Polytechnic Institute
  Worcester, MA 01609, USA.

  
  PREVIOUS POSITIONS
  
  

  Associate Department Head, 2018-2021
  Department of Computer Science
  Worcester Polytechnic Institute
  Worcester, MA 01609, USA.

  Associate Professor (with tenure), 2004-2020
  Department of Computer Science
  Worcester Polytechnic Institute
  Worcester, MA 01609, USA.

  Assistant Professor, 1996 - 2004
  (on leave of absence 1996-1997 visiting the University of Pittsburgh)
  Department of Computer Science
  Worcester Polytechnic Institute
  Worcester, MA 01609, USA.

  Visiting Assistant Professor, 1996-1997
  (on leave of absence from WPI)
  Department of Computer Science
  University of Pittsburgh
  Pittsburgh, PA 15260, USA.

     

  Research

  
  RESEARCH INTERESTS
  
  

  Machine Learning; Data Mining; Artificial Intelligence; Applications to Medicine and Behavioral Health; Transdiciplinary Research; Vertical Integration of Research Teams from PhD to High School Students; STEM Education and Research.

   

  Publications

  Authors marked with one asterisk (*) are graduate students and
  authors marked with two asterisks (**) are undergraduate students.
  

  
  BOOK CHAPTERS
  
  

  • A. Kabir*, C. Ruiz, S.A. Alvarez, and M. Moonis. "Regression, Classification and Ensemble Machine Learning Approaches to Forecasting Clinical Outcomes in Ischemic Stroke" In Biomedical Engineering Systems and Technologies. Communications in Computer and Information Science. N. Peixoto, M. Silveira, H.H., Ali, C. Maciel, E.L. van den Broek (Eds.). pp. 376-402. Springer-Verlag. 2018.

  • C. Wang*, S.A. Alvarez, C. Ruiz, and M. Moonis. "Modeling and Clustering of Human Sleep Time Series using Dynamic Time Warping: Sequential and Distributed Implementations". In Biomedical Engineering Systems and Technologies. Communications in Computer and Information Science. A. Fred and H. Gamboa, (eds.), pp. 276-294. Springer-Verlag. 2017.

  • H. Wan*, C. Ruiz, and J. Beck. "Automatic Extraction of Highly Predictive Sequence Features that Incorporate Contiguity and Mutation". In Biomedical Engineering Systems and Technologies, Plantier, G., Schultz, T., Fred, A., Gamboa, H. (eds.). Communications in Computer and Information Science (CCIS), Volume 511, pp. 212-229. Springer-Verlag. 2015. (ISBN 978-3-319-26129-4)

  • C. Wang*, F.W. Usher*, S.A. Alvarez, C. Ruiz, and M. Moonis. "Clustering of Human Sleep Recordings using a Quantile Representation of Stage Bout Durations". In Biomedical Engineering Systems and Technologies. J. Gabriel, J. Schier, S.V. Huffel, E. Conchon, C. Correia, A. Fred and H. Gamboa (eds.). Communications in Computer and Information Science, Volume 357, Springer-Verlag. 2013. (ISBN 978-3-642-38256-7)

  • A. Khasawneh*, S. A. Alvarez, C. Ruiz, S. Misra*, and M. Moonis. ``Similarity Grouping of Human Sleep Recordings using EEG and ECG''. In Biomedical Engineering Systems and Technologies. A. Fred, J. Filipe and H. Gamboa, (eds.). Communications in Computer and Information Science, Volume 273, Springer-Verlag, 2013. (ISBN: 978-3-642-29751-9)

  • S. Floyd*, C. Ruiz, S. A. Alvarez, J. Tseng, and G. Whalen. "Prediction of pancreatic cancer survival through automated selection of predictive models". In Biomedical Engineering Systems and Technologies. A. Fred, J. Filpe, H. Gamboa (eds.). Communications in Computer and Information Science, Volume 127, pp. 29-43. Springer-Verlag. 2011. (ISBN: 978-3-642-18471-0)

  • S.A. Alvarez, C. Ruiz , and T. Kawato**. More Efficient Mining over Heterogeneous Data using Neural Expert Networks. In Multimedia Data Mining and Knowledge Discovery. V.A. Petrushin and L. Khan, eds. Springer-Verlag. 2007. (ISBN: 978-1-84628-436-6)

  • S.A. Alvarez, C. Ruiz , and V. Dignum. Data mining and web knowledge management. In O. Bartenstein, U. Geske, M. Hannebauer, and O. Yoshie, editors, Web Knowledge Management and Decision Support. Fourteenth International Conference on Applications of Prolog, INAP 2001 Revised Papers, chapter 4, pages 235-236. Lecture Notes in Computer Science, Vol. 2543. Springer-Verlag, 2003.

  • C. Ruiz and J. Minker. Computing stable and partial stable models of extended disjunctive logic programs. In J. Dix, L.M. Pereira, and T.C. Przymusinski, editors, Nonmonotonic Extensions of Logic Programming, pages 205-229. Lecture Notes in Computer Science 927. Springer-Verlag, 1995.

  
  RESEARCH ARTICLES IN JOURNALS
  
  

  • B.C. Nephew, A.C. Incollingo Rodriguez, V. Melican**, J.J. Polcari**, K.E. Nippert**, M. Rashkovskii, L.B. Linnell, R. Hu*, C. Ruiz, J.A. King, P. Gardiner. "Depression Predicts Chronic Pain Interference in Racially Diverse, Income-Disadvantaged Patients." Pain Med. 23(7):1239-1248. Jul 1, 2022.

  • Sarun Paisarnsrisomsuk*, Carolina Ruiz, Sergio A. Alvarez. "Capturing the Development of Internal Representations in a High-Performing Deep Network for Sleep Stage Classification". Springer Nature Computer Science Journal, 2:318. June 2021. https://doi.org/10.1007/s42979-021-00697-3.

  • Michael Sokolovsky*, Francisco Guerrero*, Sarun Paisarnsrisomsuk*, Carolina Ruiz, Sergio A. Alvarez. "Deep learning for automated feature discovery and classification of sleep stages" IEEE/ACM Transactions on Computational Biology and Bioinformatics. Volume: 17, Issue: 6, Nov.-Dec. 1, 2020.

  • L. Zhang, S. Pagoto, C. May, B. Olendzki, K. Tucker, C. Ruiz, Y. Cao, and Y. Ma. "Effect of the AHA Dietary Counselling on Added Sugar Intake among Participants with Metabolic Syndrome" European Journal of Nutrition. Springer. March 2017. DOI 10.1007/s00394-017-1390-6.

  • X. Lin*, A. Mukherji*, E. A. Rundensteiner, C. Ruiz, and M. Ward. "PARAS: A Parameter Space Framework for Online Association Mining". Proceedings of the VLDB Endowment. Vol. 6, No. 3. pp. 193-204. 2013.

  • Z. Guo*, M. Ward, E. Rundensteiner, C. Ruiz. "Evaluation of a Pointwise Local Pattern Exploration Method". Tsinghua Science and Technology Journal. Vol. 17, Issue 4, pp 429-439. 2012.

  • S.A. Alvarez, C. Ruiz , T. Kawato**, and W. Kogel*. Neural expert networks for faster combined collaborative and content based recommendation. Journal of Computational Methods in Sciences and Engineering (JCMSE). IOS Press. Vol. 11, N. 4, pp. 161-172. 2011.

  • J. Hayward*, S. A. Alvarez, C. Ruiz, M. Sullivan, J. Tseng, and G. Whalen. "Machine Learning of Clinical Performance in a Pancreatic Cancer Database", Artificial Intelligence in Medicine, special issue on Data Mining Approaches to the Study of Disease Genes and Proteins (Sun Kim, ed.), vol. 49, issue 3, July 2010, 187-195.

  • A. Varde*, E. Rundensteiner, C. Ruiz, M. Maniruzzaman and R. Sisson Jr. LearnMet: Learning Domain-Specific Distance Metrics for Plots of Scientific Functions. International Journal on Multimedia Tools and Applications (MTAP). Special Issue on Multimedia Data Mining. Volume 35, pp. 29-53. Springer. 2007.

  • P. Laxminarayan*, S.A. Alvarez, C. Ruiz, M. Moonis. Mining Statistically Significant Associations for Exploratory Analysis of Human Sleep Data. IEEE Transactions on Information Technology in Biomedicine (TITB). Vol. 10, N. 3, July 2006.

  • W. Lin*, S.A. Alvarez, and C. Ruiz . Efficient adaptive-support association rule mining for recommender systems. Data Mining and Knowledge Discovery, 6(1):83-105, Kluwer, January 2002.

  • C. Shoemaker*, M. Pungliya*, M. Sao Pedro*, C. Ruiz , S.A. Alvarez, M. Ward, E. Ryder, and J. Krushkal. Computational methods for single point and multipoint analysis of genetic variants associated with a simulated complex disorder in a general population. Genetic Epidemiology, 21 (Suppl. 1):S738-S745, 2001.

  • C. Ruiz and J. Minker. Logic knowledge bases with two default rules. Annals of Mathematics and Artificial Intelligence, 22(3,4):333-361, 1998.

  • C. Ruiz and J. Minker. Combining closed world assumptions with stable negation. Fundamenta Informaticae, 32(2):163-181, Nov. 1997.

  • D. Seipel, J. Minker, and C. Ruiz . Model generation and state generation for disjunctive logic programs. Journal of Logic Programming, 32(1):48-69, July 1997.

  • J. Minker and C. Ruiz . Semantics for disjunctive logic programs with explicit and default negation. Fundamenta Informaticae, 20(3/4):145-192, 1994. Anniversary Issue edited by H. Rasiowa.

  
  RESEARCH ARTICLES IN CONFERENCE PROCEEDINGS
  
  

  • Carolina Ruiz, Ali Yousefi, Ruofan Hu*, C. McLaughlin, Efi Kokkoutou, Lisa Conboy. ``Using Machine Learning Techniques to Understand the Complexity of Pain Experience with Acupuncture Treatment.'' Society for Acupuncture Research. Online. June 14-17, 2021.

  • Carolina Ruiz, Shari Weaver, Robert Gegear. ``Bridging biology and computer science to engage high school students in solving real world problems.'' In Anderson D, Milner-Bolotin M, Santos R, Petrina S (Eds.) Proceedings of the 6th International STEM in Education Conference (STEM 2021). University of British Columbia, Vancouver, Canada, July 5-9. https://dx.doi.org/10.14288/1.0402129, 490-493. 2021.

  • Sarun Paisarnsrisomsuk*, Carolina Ruiz, Sergio A. Alvarez. "Improved deep learning classification of human sleep stages". IEEE 33rd International Symposium on Computer Based Medical Systems (CBMS 2020). July 28-30, 2020 (online).

  • Shari Weaver, Carolina Ruiz, Maria Berrios, Elizabeth Ryder. "Bio-CS Bridge: Investigating Biodiversity Using Computational Thinking and a Real-World Citizen Science Project". National Science Teachers Association (NSTA) 2020 Virtual Fall Conference. Nov 13-14, 2020.

  • Elizabeth Ryder, Carolina Ruiz, Shari Weaver and Robert Gegear. "Bridging Biology and Computer Science to Engage High School Students in Solving Real World Problems". 6th International STEM in Education Conference (STEM 2020). (July 2020 conference postponed until 2021).

  • Elizabeth F. Ryder, Carolina Ruiz, Shari Weaver, Robert J. Gegear. "A Team Science approach to developing high school curriculum that integrates biology and computer science". Science of Team Science Conference (SciTS 2020). June 1-4, 2020. Virtual conference.

  • Ilona Regan**, Dany Alkurdi**, Sarun Paisarnsrisomsuk*, Carolina Ruiz, Elizabeth F. Ryder, Robert Gegear. "Investigating the Efficacy of Data Mining Techniques for Crowdsourced Biological Datasets" (peer-reviewed paper). 2019 IEEE MIT Undergraduate Research Technology Conference (URTC). Cambridge, Massachusetts. Oct. 11-13, 2019.

  • Elizabeth Ryder, Carolina Ruiz, Shari Weaver and Robert Gegear. "Choosing your own adventure: Engaging the new learning society through integrative curriculum design". Learning International Networks Consortium Conference (LINC) 2019. MIT, Cambridge, MA. June 18-20, 2019. Appears in EPIC Series in Education Science 3, pp. 188-199. 2020. https://doi.org/10.29007/567f.

  • Ahmedul Kabir*, Carolina Ruiz, Sergio A. Alvarez. "Mixed Bagging: A Novel Ensemble Learning Framework for Supervised Classification based on Instance Hardness" (short paper, combined acceptance rate for long and short papers 19.94%). In Proc. of the 2018 IEEE International Conference on Data Mining (ICDM'18). Singapore. November 2018.

  • Michael Sokolovsky*, Francisco Guerrero*, Sarun Paisarnsrisomsuk*, Carolina Ruiz, Sergio A. Alvarez. "Human expert-level automated sleep stage prediction and feature discovery by deep convolutional neural networks" (full oral presentation). In Proceedings of the 17th International Workshop on Data Mining in Bionformatics (BIOKDD2018), in conjunction with the ACM SIGKDD Conference on Knowledge Discovery and Data Mining KDD2018. London, England. August 2018.

    This paper was selected for Oral Presentation at BIOKDD2018 and also selected to be featured as a poster at the KDD2018 Health Day.

  • Sarun Paisarnsrisomsuk*, Michael Sokolovsky*, Francisco Guerrero*, Carolina Ruiz and Sergio A. Alvarez. "Deep Sleep: Convolutional Neural Networks for Predictive Modeling of Human Sleep Time-Signals". KDD2018 Deep Learning Day, at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining KDD2018. London, England. August 2018.

  • Holly Nguyen**, Carolina Ruiz, Vance Wilson, Diane Strong, Soussan Djamasbi. "Using Personality Traits and Chronotype to Support Personalization and Feedback in a Sleep Health Behavior Change Support System". Proceedings of the 51st Annual Hawaii International Conference on System Sciences (HICSS-51), January 3-6, 2018.

  • Katherine Finnerty** (Amherst College), Carolina Ruiz, Bengisu Tulu, Qiaoyu Liao**, Jessica Oleski, and Sherry Pagoto. "Comparing Qualitative Evaluation Methods for Improving User Engagement with Mobile Health Applications". Workshop on Interactive Systems in Healthcare (WISH), in conjunction with the American Medical Informatics Association (AMIA) 2017 Annual Symposium. Nov. 4-8, Washington DC.

  • A. Kabir*, C. Ruiz, S.A. Alvarez, and M. Moonis. "Predicting Outcome of Ischemic Stroke Patients using Bootstrap Aggregating with M5 Model Trees" (full paper, acceptance rate 21%). In Proc. Tenth International Conference on Health Informatics (HEALTHINF 2017). Porto, Portugal. Feb. 2017.

  • V. Wilson, D. Strong, S. Djamasbi, and C. Ruiz. "Using a Key Informant Focus Group, Formative User Testing, and Theory to Guide Design of a Sleep Health BCSS". Proceedings of the 50th Annual Hawaii International Conference on System Sciences (HICSS-50), January 4-7, 2017.

  • B. Tulu, C. Ruiz, J. Allard**, J. Acheson**, A. Busch**, A. Roskuski**, G. Heeringa** (Michigan Technological University), V. Jaskula** (Skidmore College), J. Oleski, S. Pagoto. "SlipBuddy: A Mobile Health Intervention to Prevent Overeating". Proceedings of the 50th Annual Hawaii International Conference on System Sciences (HICSS-50), January 4-7, 2017.

  • S. Djamasbi, D. Strong, V. Wilson, and C. Ruiz. "Designing and Testing User-Centric Systems with both User Experience and Design Science Research Principles". The 22nd Americas Conference on Information Systems (AMCIS 2016). San Diego, CA. August 2016.

  • C. Wang*, S.A. Alvarez, C. Ruiz, and M. Moonis. "Deviation-based dynamic time warping for clustering human sleep" (full paper). In Proc. Ninth International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2016). Rome, Italy. February 2016.

  • A. Kabir*, C. Ruiz, S.A. Alvarez, N. Riaz, and M. Moonis. "Model-Based Clustering of Ischemic Stroke Patients". (full paper, acceptance rate 11%). In Proc. Eighth International Conference on Health Informatics (HEALTHINF 2015). Lisbon, Portugal. Jan 12-15, 2015.

  • C. Wang*, S.A. Alvarez, C. Ruiz, and M. Moonis. "Semi-Markov Modeling-Clustering of Human Sleep with Efficient Initialization and Stopping" (full paper, acceptance rate 13%). In Proc. Seventh International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2014). Angers, France. March 2014.

  • H. Wan*, C. Ruiz and J. Beck. "A novel feature generation method for sequence classification: Mutated Subsequence Generation" (full paper, acceptance rate 10%). In Proc. Fifth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2014). Angers, France. March 2014.

  • A. Mukherji*, X. Lin*, C.R. Botaish, J. Whitehouse, E. A. Rundensteiner, M. Ward, and C. Ruiz. "PARAS: Interactive Parameter Space Exploration for Association Rule Mining". SIGMOD'2013. Demonstration. New York, NY. June 2013.

  • X. Lin*, A. Mukherji*, E. A. Rundensteiner, C. Ruiz, and M. Ward. "PARAS: A Parameter Space Framework for Online Association Mining". In Proc. 39th International Conference on Very Large Data Bases (VLDB2013). Trento, Italy. Aug. 2013.

  • C. Wang*, S.A. Alvarez, C. Ruiz, and M. Moonis. "Computational Modeling of Sleep Stage Dynamics using Weibull Semi-Markov Chains" (full paper, acceptance rate 14%). In Proc. Sixth International Conference on Health Informatics (HEALTHINF 2013), pp. 122-130. Barcelona, Spain, Feb. 2013.

  • H. Wan*, G. Barrett**, C. Ruiz and E.F. Ryder. "Mining Association Rules that Incorporate Transcription Factor Binding Sites and Gene Expression Patterns in C. elegans" (full paper, acceptance rate 10%). In Proc. Fourth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2013), pp. 81-89. Barcelona, Spain, Feb. 2013.

  • S.A. Alvarez and C. Ruiz. "Collective Probabilistic Dynamical Modeling of Sleep Stage Transitions" (short paper, acceptance rate 37%). In Proc. Sixth International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2013), pp. 209-214. Barcelona, Spain, Feb. 2013.

  • Y. Gong*, J. Beck, C. Ruiz. "Modeling Multiple Distributions of Student Performances to Improve Predictive Accuracy." In Proc. of the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP 2012). Lecture Notes in Computer Science Volume 7379. pp. 102-113. Montreal, Canada. July 16-20, 2012.

  • F. Usher*, C. Wang*, S.A. Alvarez, C. Ruiz, and M. Moonis. "Machine learning of human sleep patterns based on stage bout durations", full paper (acceptance rate = 65/522 = 12.5%). In Proc. Fifth International Conference on Health Informatics (HEALTHINF 2012), in conjunction with the Fifth International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2012), Vilamoura, Portugal, Feb. 1-4, 2012.

  • Z. Guo*, M. Ward, E. Rundensteiner, C. Ruiz. "Pointwise Local Pattern Exploration for Sensitivity Analysis", (acceptance rate = 32%). In Proc. IEEE Conference on Visual Analytics Science and Technology (IEEE VAST2011). Providence, RI, Oct. 23-28, 2011.

  • A. Khasawneh*, S. A. Alvarez, C. Ruiz, S. Misra*, and M. Moonis. "EEG and ECG Characteristics of Human Sleep Composition Types", full paper (acceptance rate = 48/538 = 8.92%). In Proc. Fourth International Conference on Health Informatics (HEALTHINF 2011), in conjunction with the Fourth International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2011), pp. 97-106, Rome, Italy, Jan. 26-29, 2011.
    * Best Paper Award *

  • A. Khasawneh*, S. A. Alvarez, C. Ruiz, S. Misra*, and M. Moonis. "Discovery of Sleep Composition Types using Expectation-Maximization", In Proc. 23rd IEEE International Symposium on Computer-Based Medical Systems (CBMS 2010), Perth, Australia, Oct. 12-15, 2010.

  • S. Floyd*, C. Ruiz, S. A. Alvarez, J. Tseng, and G. Whalen. "Model Selection Meta-Learning for the Prognosis of Pancreatic Cancer", full paper (acceptance rate: 46/410 = 11.2%), In Proc. Third International Conference on Health Informatics (HEALTHINF 2010), in conjunction with the Third International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2010), pp. 29-37. Valencia, Spain, Jan. 2010.

  • A. Bodnari**, T. Matsumura**, C. Ruiz, M.M. Murphy, J.P. Simons, G.F. Whalen, and J.F. Tseng. "Computationally Enhanced Medical Decision Support for Pancreatic Cancer". In Proceedings of the 2009 American Medical Informatics Association (AMIA) Spring Congress". Poster paper. Orlando, FL. May 2009.

  • J. Hayward*, S.A. Alvarez, C. Ruiz, M. Sullivan, J. Tseng, and G. Whalen. "Knowledge Discovery in Clinical Performance of Cancer Patients." In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM08), pp. 51-58. Philadelphia PA, USA. Nov. 2008.

  • Z.A. Pardos*, J. Beck, C. Ruiz, and N.T. Heffernan. "The Composition Effect: Conjunctive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS". In Proceedings of the First International Conference on Educational Data Mining. Montreal, Canada. 2008. pp. 147-156.

  • Z.A. Pardos*, N.T. Heffernan, C. Ruiz, and J. Beck. "Effective Skill Assessment Using Expectation Maximization in a Multi Network Temporal Bayesian Network". The Young Researchers Track at the 20th International Conference on Intelligent Tutoring Systems. Montreal, Canada. 2008. pp. 31-40.

  • D. Thakkar*, C. Ruiz, E.F. Ryder. "Hypothesis Driven Specialization of Gene Expression Association Rules". In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM2007). pp. 48-55. Fremont, CA. USA. Nov. 2007.

  • N. Lloyd*, N.T. Heffernan, C. Ruiz. "Predicting Student Engagement in Intelligent Tutoring Systems Using Teacher Expert Knowledge". Educational Data Mining Workshop. Held in conjunction with the 13th International Conference on Artificial Intelligence in Education (AIED 2007). Marina Del Rey, CA. USA. July 2007.

  • S. Floyd*, S.A. Alvarez, C. Ruiz, J. Hayward*, M. Sullivan, J. Tseng, G. Whalen. "Improved Survival Prediction for Pancreatic Cancer using Machine Learning and Regression". The Society for Surgery of the Alimentary Tract (SSAT). SSAT Track of Digestive Disease Week. Washington DC, USA. May 2007.

  • J. Hayward*, S.A. Alvarez, C. Ruiz, J. Tseng, M. Sullivan, G. Whalen. "Survival of Patients with Pancreatic Cancer Predicted using Machine Learning Techniques". Society of Surgical Oncology's 60th Annual Cancer Symposium. Washington DC, USA. March 2007.

  • A. Varde*, E. Rundensteiner, C. Ruiz, D. Brown, M. Maniruzzaman and R. Sisson Jr. "Designing Semantics-Preserving Cluster Representatives for Scientific Input Conditions". In Proc. of ACM Fifteenth Conference on Information and Knowledge Management (CIKM 2006). Washington DC, USA. November 2006.

  • A. Varde*, E. Rundensteiner, C. Ruiz, M. Maniruzzaman and R. Sisson Jr. "Effectiveness of Domain-Specific Cluster Representatives for Graphical Plots". In 3rd International ACM SIGMOD Workshop on Information Quality in Information Systems (IQIS 2006). Chicago, US, June 2006.

  • A. Varde*, E. Rundensteiner, C. Ruiz, D. Brown, M. Maniruzzaman and R. Sisson Jr. "Integrating Clustering and Classification for Estimating Process Variables in Materials Science". In AAAI Member Abstracts and Posters Track at the Twenty-First National Conference on Artificial Intelligence (AAAI-06), Boston, Massachusetts. July 16 - 20, 2006.

  • A. Varde*, E. Rundensteiner, C. Ruiz, M. Maniruzzaman and R. Sisson Jr. "Learning Semantics-Preserving Distance Metrics for Clustering Graphical Data". In Proc. of the Sixth International Workshop on Multimedia Data Mining (MDM/KDD2005). Held in conjunction with the Eleventh International Conference on Knowledge Discovery and Data Mining (KDD2005). Chicago, IL. USA. August 2005.

  • K.A. Pray*, C. Ruiz. "Mining Expressive Temporal Associations From Complex Data". International Conference on Machine Learning and Data Mining MLDM'2005. Springer Verlag. Leipzig, Germany. July 9-11, 2005.

  • P. Laxminarayan*, C. Ruiz, S.A. Alvarez, M. Moonis. "Mining Associations over Human Sleep Time Series". 18th IEEE International Symposium on Computer-Based Medical Systems. Dublin, Ireland, June 22-24, 2005.

  • A. Varde*, E. Rundensteiner, C. Ruiz, M. Maniruzzaman and R. Sisson Jr. "Data Mining over Graphical Results of Experiments with Domain Semantics." ACM SIGART's 2nd International Conference on Intelligent Computing and Information Systems ICICIS 2005. pp. 603-611, Cairo, Egypt, March 5-7, 2005.

  • M. El Sayed*, C. Ruiz, E.A. Rundensteiner. FS-Miner: Efficient and Incremental Mining of Frequent Sequence Patterns in Web Logs. In 6th ACM International Workshop on Web Information and Data Management (WIDM'04). pp 128-135, Washington DC, USA, November 12-13, 2004.

  • J. Freyberger*, N. Heffernan, C. Ruiz. Using Association Rules to Guide a Search for Best Fitting Transfer Models of Student Learning. Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes. Proc. of 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. 2004.

  • A. Icev*, C. Ruiz , and E. Ryder. Distance-Enhanced Association Rules for Gene Expression. In Proc. of the Third ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD2003). Held in conjunction with the Ninth International Conference on Knowledge Discovery and Data Mining (KDD2003). pp. 34-40. Washington DC, USA. August 2003.

  • S. Alvarez, T. Kawato**, and C. Ruiz. Mining over Loosely Coupled Data Sources using Neural Experts. In Proc. of the Fourth International Workshop on Multimedia Data Mining (MDM/KDD2003). Held in conjunction with the Ninth International Conference on Knowledge Discovery and Data Mining (KDD2003). Washington DC, USA. August 2003.

  • C. Shoemaker* and C. Ruiz . Association rule mining algorithms for set-valued data. In Lecture Notes in Computer Science. Proc. of the Fourth International Conference on Intelligent Data Engineering and Automated Learning. Revised Papers. Vol. 2690. g, March 2003. Lecture Notes in Computer Science Vol. 2690. pp. 669-676. Springer-Verlag. June 2003.

  • F. Tan**, B. Murphy**, D. Phu**, I. Pushee**, C. Ruiz , J. Krushkal, and E. Ryder. Identifying promoter motifs and predicting gene expression patterns in C. elegans using data mining tools. In Proc. of the Thirteenth International C. elegans Conference, Los Angeles, CA, June 2001.

  • C. Ruiz . Deductive database integration and knowledge discovery. In Proc. Thirteenth International Conference on Applications of Prolog, Tokyo, Japan, Oct. 2000.

  • M. Sao Pedro*, C. Shoemaker*, M. Pungliya*, C. Ruiz , S.A. Alvarez, M. Ward, M. Stevens, E. Ryder, and J. Krushkal. Computational population-based techniques in identifying genetic variants associated with simulated complex disorder in a general population. In Proc. of the Twelfth Genetic Analysis Workshop (GAW12), pages 415-419. Southwest Foundation for Biomedical Research, Oct. 2000.

  • C. Shoemaker*, M. Sao Pedro*, S.A. Alvarez, and C. Ruiz . Prediction vs. description: Two data mining approaches to the analysis of genetic data. In Proc. of the Twelfth Genetic Analysis Workshop (GAW12), pages 449-453. Southwest Foundation for Biomedical Research, Oct. 2000.

  • W. Lin*, S.A. Alvarez, and C. Ruiz . Collaborative recommendation via adaptive association rule mining. In R. Kohavi, M. Spiliopoulou, and J. Srivastava, editors, Proc. Intl. Workshop on Web Mining for E-Commerce (WebKDD2000). In conjunction with the Sixth Conference on Knowledge Discovery in Databases (KDD'2000), pages 35-41, Aug. 2000.

  • D. Seipel, J. Minker, and C. Ruiz . A characterization of the partial stable models for disjunctive databases. In J. Maluszynski, editor, Proceedings of the Fourteenth International Logic Programming Symposium (ILPS'97), pages 245-259. MIT Press, Cambridge, Mass., Oct. 1997.

  • J. Aronis, C. Ruiz , and B. Buchanan. Knowledge and data integration for discovery. In Proceedings of the Workshop on Research and Development Opportunities in Federal Information Services, May 1997. Arlington, VA. ( http://www.isi.edu/nsf/).

  • J. Minker and C. Ruiz . Mixing a default rule with stable negation. In Proceedings of the Fourth International Symposium on Artificial Intelligence and Mathematics, pages 122-125, Jan. 1996.

  • J. Minker and C. Ruiz . On extended disjunctive logic programs. In J. Komorowski and Z.W. Ras, editors, Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems, ISMIS'93, pages 1-18. Lecture Notes in AI. Springer-Verlag, June 1993.

• Y. Zhang, F. Xhafa, C. Ruiz , L. Yao, editors. Special issue on "Wearable Sensor Signal Processing for Smart Health" of Elsevier's Smart Health Journal. Vol. 5-6. December 2017. ISSN 2352-6483. Available online March 2018.

• A. Fred, H. Gamboa, J. Gilbert, H. Azhari, H. Ali, C. Quintão, J. Sliwa, C. Ruiz, editors. Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016). SCITEPRESS, 2016.

• U. Geske, C. Ruiz , and D. Seipel, editors. Proceedings of the Seventh International Workshop on Deductive Databases and Logic Programming DDLP'99, Tokyo, Japan, September 1999. GMD - German National Research Center for Information Technology. Included also in the Proceedings of the International Conference on Applications of Prolog (INAP99).

• P. Fraternali, U. Geske, C. Ruiz , and D. Seipel, editors. Proceedings of the Sixth International Workshop on Deductive Databases and Logic Programming DDLP'98, Manchester, UK, June 1998. GMD - German National Research Center for Information Technology.

• U. Geske, C. Ruiz , and D. Seipel, editors. Proceedings of the Fifth International Workshop on Deductive Databases and Logic Programming DDLP'97, Leuven, Belgium, July 1997. GMD - German National Research Center for Information Technology. ISBN 3-88457-317-9. July 1997.

• Posters at Professional Meetings:

  • Peer Reviewed Posters

    • Carolina Ruiz, Robert J. Gegear, Shari Weaver, and Elizabeth F. Ryder. "The Bio-CS Bridge: Developing a Modular Computational Framework to Support Integrated STEM+C Curriculum Design". Poster (peer reviewed). Digital Learning Arcade organized by the Community for Advancing Discovery Research in Education (CADRE). Washington DC, June 2018.

  • Non Peer Reviewed Posters

    • Elizabeth Ryder, Carolina Ruiz, Shari Weaver and Robert Gegear. "The Bio-CS Bridge: A Transdisciplinary Team Approach to Integrating Biology and Computer Science in High School Curricula". Poster. Science of Team Science Conference (SciTS 2019). Lansing, Michigan. May 2019.

    • Elizabeth F. Ryder, Robert J. Gegear, Carolina Ruiz, and Shari Weaver. "STEM+C: Building Educational Bridges between Computer Science and Biology through Transdisciplinary Teamwork and Modular Curriculum Design" Poster. 2018 NSF DRK-12 and STEM+C PI Meeting. Washington DC, June 2018.

• Peer Reviewed Abstracts and Presentations at Professional Meetings:

  • E.F. Ryder, R.J. Gegear, C. Ruiz, S. Weaver, J. Field, R. Cochran, J. vanderSpek, J. Hardy.
    "Beecology: A Bio-CS Bridge to address ecological problems"
    Massachusetts Association of Science Teachers (MAST) Conference. Nov. 2018.

• Publications by Undergraduate Research Mentees:

  Research conducted with Ruiz's Luce Scholar Mentee and CS undergraduate student, Holly Nguyen, yielded a peer-reviewed conference paper and a poster presentation. This research work was conducted at WPI during the summer of 2016 with the support of a Clare Boothe Luce Undergraduate Research Award from the Luce Foundation.

  • Zellerbach, Karitta. "A Machine Learning Investigation of the Influence of Nutritional Deficiency on Overeating and Obesity" (poster). Next-in-Bio: Regional Showcase for Undergraduate Research. WPI. November 2019 First Place Research Award

  • Nguyen, Holly. "Personalizing a Sleep Health App for College Students Using Personality Traits and Chronotype" (peer-reviewed paper). IEEE MIT Undergraduate Research Technology Conference. Nov. 4-6, 2016.

  • Nguyen, Holly. "Using Mobile Apps to Fight Sleep Deprivation Among College Students" (poster). Next-in-Bio: Regional Showcase for Undergraduate Research. WPI. October 1, 2016

  
  THESES
  
  

  • C. Ruiz. "Semantics of Knowledge Based Systems with Multiple Forms of Negation". Ph.D. thesis, Department of Computer Science. University of Maryland, College Park, MD. 20742. August 1996.
    Advisor, Prof. Jack Minker.

  • C. Ruiz. "Manta 2: An abstract data types manager". Master's thesis, Department of Computer Science. University of Los Andes. Bogotá, Colombia, 1990. (In Spanish).

  • C. Ruiz. "Automata topoi". BS Thesis. Department of Mathematics. University of Los Andes. Bogotá, Colombia, 1989. (In Spanish).

  • C. Ruiz. "An implementation of the Boyer and Moore theorem prover". BS Thesis. Department of Computer Science. University of Los Andes. Bogotá, Colombia, 1988. (In Spanish).

INVITED TALKS AT SEMINARS, CONFERENCES AND UNIVERSITY COLLOQUIA

• Invited Research Talk at the Broad Institute:
  Carolina Ruiz (WPI) and Sergio A. Alvarez (Boston College)
  "Predictive Machine Learning for Human Sleep Modeling"
  Machine Learning for Health (ML4H) Seminar, The Broad Institute. March 3, 2022.

• "Project-Based Learning: Impacts and Implementation".
  Together with Prof. Kristin Wobbe.
  Two-day Workshop for faculty of the Vellore Institute of Technology. Vellore, India. April 11-12, 2019.

• "CS Components of the Bio-CS Bridge: Using Modular Design to Promote Computational Thinking".
  Bio-CS Bridge Summer Institute, funded by NSF's STEM+C. WPI. June 18-20, 2018.

• "Concepts in Data Mining: Approaches, Techniques and Cutting-edge Applications "
  12th Annual Digital Commonwealth Conference. April 10, 2018.

• "Mining Data to Find a Way to Better Sleep"
  An Innovation Forum: The Digital Health and IoT Journey - On the Road to Personalized Medicine and Better Health
  Organized by WPI's Healthcare Delivery Institute (HDI)
  September 12, 2016

• "Smartphone apps for Health, Wellness, and Disease management"
  Together with Profs. Diane Strong and Soussan Djamasbi
  NSF Smart and Connected Health Research for Undergradutes (NSF-SCH-REU) Workshop
  Organized by the Univ. of Massachusetts Medical School at WPI for undergraduate biomedical engineering students from Massachusetts Colleges and Universities
  May 17, 2016

• "What is Bioinformatics?"
  Together with Prof. Elizabeth Ryder
  Women in Science Workshop
  WPI K-12 outreach for 7th grade female students interested in STEM
  July 22, 2016

• "Data Science and Data Analytics"
  WPI Systems Dynamics Seminar
  September 10, 2015

• "Deductive Database Integration and Knowledge Discovery".
  Thirteenth International Conference on Applications of Prolog.
  Tokyo, Japan. October 2000.
  

• "From Logical Rules to Association Rules".
  University of Economics, Prague.
  Laboratory for Intelligent Systems Seminar.
  Prague, Czech Republic. November, 1999.
  

• "Deductive Data Mining".
  University of Maryland
  Workshop in Honor of Jack Minker, October 1998.
  

• "Inductive Learning in a Deductive Framework".
  University of Pittsburgh
  Computer Science Seminar.
  Pittsburgh PA, USA. June 1997.
  

• "Knowledge Based Systems with Multiple Forms of Negation".
  York University
  Computer Science Seminar.
  York Ontario, Canada. November 1996.
  

• "Knowledge Based Systems with Multiple Forms of Negation".
  McMaster University
  Computer Science and Systems Seminar.
  Hamilton Ontario, Canada. November 1996.
  

• "Knowledge Based Systems with Multiple Forms of Negation".
  University of Pittsburgh
  Intelligent Systems AI Research Seminar.
  Pittsburgh PA, USA. November 1996.
  

• "Knowledge Based Systems with Multiple Forms of Negation".
  University of North Texas
  Computer Science Colloquium.
  Denton TX, USA. March 1996.
  

• "Knowledge Based Systems with Multiple Forms of Negation".
  Kansas State University
  Computing and Information Sciences Colloquium.
  Manhattan KS, USA. March 1996.
  

• "Knowledge Based Systems with Multiple Forms of Negation".
  Worcester Polytechnic Institute
  Computer Science Colloquium.
  Worcester MA, USA. February 1996.
  

• "Logic Programs with Multiple Forms of Default Negation".
  University of Maryland, College Park
  Logic and Artificial Intelligence Seminar.
  College Park MD, USA. April 1995.
  

• "Computing Stable and Partial Stable Models of Extended Disjunctive Logic Programs".
  University of Maryland, College Park
  Logic and Artificial Intelligence Seminar.
  College Park MD, USA. Oct. 1994.
  

• "On Extended Disjunctive Logic Programs".
  University of Maryland, College Park
  Logic and Artificial Intelligence Seminar.
  College Park MD, USA. April 1993.
  

• "Kripke Models and Logic Programs".
  University of Maryland, College Park
  Logic and Artificial Intelligence Seminar.
  College Park MD, USA. June 1992.
  

• Grants Awared:

  • Co-PI in National Science Foundation grant NSF#1742446
    Building Educational Bridges between Computer Science and Biology through Transdisciplinary Teamwork and Modular Curriculum Design
    $1,228,848
    Sept. 1, 2017 - Aug. 31, 2021
    PI: Prof. Elizabeth Ryder

  • Research Advisor in National Science Foundation grant
    REU SITE: Data Science Research for Healthy Communities in the Digital Age
    $361,632
    Jan. 1, 2019 - Dec. 31, 2021
    PI: Prof. Elke Rundensteiner

  • Research Advisor in National Science Foundation grant NSF#CNS-1560229
    REU SITE: Data Science Research for Safe, Sustainable and Healthy Communities
    $358,574
    May 1, 2016 - April 30, 2019
    PI: Prof. Elke Rundensteiner

  • Co-PI and Research Mentor and Advisor in Henry Luce Foundation grant
    Clare Boothe Luce Undergraduate Research Awards in Computer Science, Mathematics, Physics, and Robotics Engineering
    $204,000
    Jan. 1, 2016 - Dec. 31, 2018.
    PI: Prof. Karen Oates

  • Senior Personnel in National Science Foundation grant NSF#0742503
    PIMSE: A GK-12 Partnership Implementing Mathematics and Science Education (PIMSE): Assisting Middle School Use of Tutoring Technology in the Classroom
    $2,090,700,
    May 15, 2008 - April 30, 2014.
    PI: Neil Heffernan

  • Co-PI in National Science Foundation grant NSF-DRL#0733286
    "ASSISTments Meets Inquiry"
    $1,498,428
    Sept. 1, 2007 - Aug. 31, 2013.
    PI: Janice Gobert

• Media Coverage of my Machine Learning Research on Human Sleep:
  My collaborative research with Boston College and the University of Massachusetts Medical School on machine learning algorithms to discover patterns in human sleep data has been featured in several media outlets:
  • Telegram & Gazette, "WPI study may promote sweet dreams", Feb. 22, 2017.
  • 2017 WPI Research Magazine, "Digging Deep to Improve Healthcare", 2017.

• Media Coverage of my Collaborative Research on Computational Methods to Study Biodiversity:
  My interdisciplinary collaborative research with Professors Robert Gegear (BBT, BCB) and Liz Ryder (BBT, BCB) on developing computational tools for a crowdsourcing, biodiversity citizen science project was featured in numerous media outlets around the country including:
  • Washington Times. "Smartphone app helps researchers track bumblebees", June 19, 2017.
  • Miami Herald, "Smartphone App Helps Researchers Track Bumblebees" June 19, 2017.
  • U.S. News & World Report, "Smartphone App Helps Researchers Track Bumblebees" June 19, 2017.
  • The same article was featured in 26 additional media outlets around the country in June 2017: The Fresno Bee, The Kansas City Star, The State, The Charlotte Observer, San Francisco Chronicle, News-Times, Tri-City Herald, The Advocate, Sun News, Tribune, Sun Herald, Belleville News-Democrat, Merced Sun Star, Connecticut Post, Greenwich Time, Republic, Sun Chronicle, Times Union, Wakefield Daily, The Daily Journal, Island Packet, The Hour, My informs, ccenterdipatch.com, Alva Review-Courier, and the Tri-Valley Dispach.

• Media Coverage of our NSF STEM+C Grant:
  Several media outlets covered the awarding to WPI of the "Building Educational Bridges between Computer Science and Biology through Transdisciplinary Teamwork and Modular Curriculum Design" grant from the STEM+Computing program of the National Science Foundation (NSF). PI: Prof. Liz Ryder (BBT, BCB), Co-PIs: Prof. Robert Gegear (BBT, BCB), Prof. Carolina Ruiz (CS, BCB, DS), and Shari Weaver (WPI STEM Education Center).

  • Boston Globe, October 2017.
  • Worcester Business Journal, "WPI lands $1.2M high school curriculum grant", October 18, 2017.
  • GenomeWeb, October 2017.
  • WPI Press Release, "WPI Receives $1.2M Grant to Help High Schools Improve Biology Curriculum with Computer Science and Hands-on Projects", October 18, 2017.

• Media Coverage of my Research on Machine Learning in Mobile-Health:
  My interdisciplinary collaborative research with Professor Bengisu Tulu (FBS) and Dr. Sherry Pagoto (formerly at UMass Medical School, now at UConn) on creating machine learning approaches to predict and prevent overeating were featured in the following media outlets:
  • TV channel interviews:
    • Charter Channel 3 (Worcester), broadcasted on Dec. 13, 2017.
    • Boston Channel 25 (Fox News), broadcasted on Jan 2, 2018
  • News articles in general and professional media outlets:
    • Worcester Business Journal: "WPI app aims to stop overeating", Dec. 12, 2017.
    • Clinical Innovations + Technology. "Researchers develop machine learning app that predicts overeating tendencies", Dec 18, 2017.
    • Medical News Today, "Obesity: Could a new smartphone app prevent overeating?", Dec. 26, 2017.
    • WPI News Release
  • Radio coverage:
    • NPR: Health in a Heartbeat: Smartphone app targets obesity prevention based on users' eating habits. National Public Radio (NPR) (2 min). April 19, 2018.
    • WSRS, Dec. 13, 2017

ORGANIZER OF CONFERENCES AND WORKSHOPS

• Program Co-Chair of the 9th International Conference on Health Informatics (HEALTHINF2016). Rome, Italy. February 2016.

• Co-organizer (with Prof. Sergio Alvarez, Boston College) of the Data Mining and Decision Support Track of the Fifteenth International Conference on Applications of Declarative Programming and Knowledge Management (INAdP2004).
  Berlin, Germany. March 2004.

• Co-organizer (with Prof. Matthew O. Ward, WPI) of the one-day Workshop "From Data to Knowledge: Exploring Industrial, Commercial, and Scientific Databases". Sponsored by the WPI Center for Research in Exploratory Data and Information Analysis (CREDIA). Held at WPI on March 4, 2003.

• Co-organizer (with Prof. Sergio Alvarez, Boston College) of the International Workshop on Rule-Based Data Mining (RBDM2001).
  Tokyo, Japan, Oct. 20-22, 2001.
  In conjunction with International Conference on Applications of Prolog (INAP2001).
  

• Co-organizer (with Prof. Dr. Ulrich Geske, Fraunhofer Institute for Computer Architecture and Software Technology and the University of Potsdam, Germany; and Prof. Dr. Dietmar Seipel, University of Wuerzburg, Germany) of the Seventh International Workshop on Deductive Databases and Logic Programming (DDLP'99).
  Tokyo, Japan, Sept. 3-5, 1999.
  In conjunction with International Conference on Applications of Prolog (INAP'99).
  

• Co-organizer (with Prof. Piero Fraternali, Politecnico di Milano, Italy; Prof. Dr. Ulrich Geske, Fraunhofer Institute for Computer Architecture and Software Technology and the University of Potsdam, Germany; and Prof. Dr. Dietmar Seipel, University of Wuerzburg, Germany) of the Sixth International Workshop on Deductive Databases and Logic Programming (DDLP'98).
  Manchester, UK, June 20, 1998.
  Post-Conference Workshop of the Joint International Conference and Symposium on Logic Programming (JICSLP'98).
  

• Co-organizer (with Prof. Dr. Ulrich Geske, Fraunhofer Institute for Computer Architecture and Software Technology and the University of Potsdam, Germany; and Prof. Dr. Dietmar Seipel, University of Wuerzburg, Germany) of the Fifth International Workshop on Deductive Databases and Logic Programming (DDLP'97).
  Leuven, Belgium, July, 1997.
  In conjunction with the International Conference on Logic Programming (ICLP'97).
  

MEMBER OF PROGRAM COMMITTEES

• 24th IEEE International Conference on Data Mining (ICDM 2024). Abu Dhabi, UAE, Dec. 2024.

• 23rd IEEE International Conference on Data Mining (ICDM 2023). Shanghai, China. Dec. 2023.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2023). Istanbul, Turkey. Dec. 2023.

• AMIA 2023 Annual Symposium. New Orleans, Louisiana. USA. Nov. 11-15, 2023.

• 22nd IEEE International Conference on Data Mining (ICDM 2022). Orlando, Florida. Nov-Dec. 2022.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2022). Las Vegas, Nevada. Dec. 2022.

• 31st ACM International Conference on Information and Knowledge Management (CIKM2022). Atlanta, Georgia. Oct. 2022.

• SIAM International Conference on Data Mining (SDM22). Online, Alexandria, Virginia, USA. April 2022.

• Fifteenth International Conference on Health Informatics (HEALTHINF 2022). Vienna, Austria. Feb. 2022.

• IEEE International Conference on Data Mining (ICDM 2021). Auckland, New Zealand. Dec. 2021.

• 30th ACM International Conference on Information and Knowledge Management (CIKM). Online. Nov. 2021.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2021). Houston, TX, USA. Dec. 2021.

• Reviewer, American Medical Informatics Association (AMIA) 2021 Annual Symposium. San Diego, CA, USA. Oct-Nov. 2021.

• Fourteenth International Conference on Health Informatics (HEALTHINF 2021). Online. Feb. 2021.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2020). Seoul, South Korea. Dec. 2020.

• IEEE International Conference on Data Mining (ICDM 2020). Sorrento, Italy. Nov. 2020.

• Reviewer, American Medical Informatics Association (AMIA) 2020 Annual Symposium. Chicago, IL. Nov. 2020.

• 12th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2020). Budapest, Hungary. Nov. 2020.

• 29th ACM International Conference on Information and Knowledge Management (CIKM). Galway, Ireland. Oct. 2020.

• Thirteenth International Conference on Health Informatics (HEALTHINF 2020). Valletta, Malta. Feb. 2020.

• Tenth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2020). Valletta, Malta. Feb. 2020.

• IEEE International Conference on Data Mining (ICDM 2019). Beijing, China. Nov. 2019.

• 28th ACM International Conference on Information and Knowledge Management (CIKM). Beijing, China. Nov. 2019.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2019). San Diego, CA, USA. Nov. 2019.

• Reviewer, American Medical Informatics Association (AMIA) 2019 Annual Symposium. Washington D.C., Nov. 2019.

• Eleventh International Conference on Knowledge Discovery and Information Retrieval (KDIR 2019). Vienna, Austria. September 2019.

• Twelve International Conference on Health Informatics (HEALTHINF 2019). Prague, Czech Republic. Feb. 2019.

• Ninth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2019). Prague, Czech Republic. Feb. 2019.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2018). Madrid, Spain. Dec. 2018.

• Reviewer, American Medical Informatics Association (AMIA) 2018 Annual Symposium. San Francisco CA. Nov. 2018.

• 27th ACM International Conference on Information and Knowledge Management (CIKM2018). Turin, Italy. October, 2018.

• Tenth International Conference on Knowledge Discovery and Information Retrieval (KDIR 2018). Seville, Spain. September 2018.

• Eleventh International Conference on Health Informatics (HEALTHINF 2018). Madeira, Portugal. Jan. 2018.

• Ninth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2018). Madeira, Portugal. Jan. 2018.

• Reviewer, American Medical Informatics Association (AMIA) 2017 Annual Symposium. Washington DC. Nov. 2017.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2017). Kansas City, USA. Nov. 2017.

• Ninth International Conference on Knowledge Discovery and Information Retrieval (KDIR 2017). Madeira, Portugal. Nov. 2017

• Tenth International Conference on Health Informatics (HEALTHINF 2017). Porto, Portugal. Feb. 2017.

• Eighth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2017). Porto, Portugal. Feb. 2017.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2016). Shenzhen, China. Dec. 2016.

• Twenty-Eighth International Conference on Tools with AI (ICTAI 2016). San Jose, California. Nov. 2016.

• Eighth International Conference on Knowledge Discovery and Information Retrieval (KDIR 2016). Porto, Portugal. Nov. 2016.

• Seventh International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2016). Rome, Italy. Feb. 2016.

• Seventh International Conference on Knowledge Discovery and Information Retrieval (KDIR 2015). Lisbon, Portugal. Nov. 2015.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2015). Washington DC, USA. Nov. 2015.

• Sixth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2015). Lisbon, Portugal. January 2015.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2014). Belfast, UK, Nov. 2014.

• Sixth International Conference on Knowledge Discovery and Information Retrival (KDIR2014). Rome, Italy. Oct. 2014.

• Fifth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2014). Angers, France. March 2014.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2013). Shanghai, China, Dec. 2013.

• Fifth International Conference on Knowledge Discovery and Information Retrival (KDIR2013). Portugal. Sept. 2013.

• 20th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2013). Kiel, Germany. Sept. 2013.

• Session Chair, Fourth International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2013). Barcelona, Spain, Feb. 2013.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2012). Philadelphia, PA, Oct. 2012.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011). Atlanta, Georgia, Nov. 2011.

• 19th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2011). Viena, Austria. Sept. 2011.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM2010). Hong Kong, Dec. 2010.

• Workshop for Ph.D. Students in Information and Knowledge Management (PIKM2010). In conjunction with the ACM Conference on Information and Knowledge Management CIKM 2010, Toronto, Canada, Oct. 2010.

• 18th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2009). Evora, Portugal. Nov. 2009.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2009). Washington DC, USA. Nov. 2009.

• IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2008). Philadelphia, PA, USA. Nov. 2008.

• Second Ph.D. Workshop in CIKM (PIKM2008). In conjunction with the ACM Conference on Information and Knowledge Management (CIKM 2008). Napa Valley, CA, USA. Oct. 2008.

• First International Conference on Educational Data Mining (EDM08). Co-located with the International Conference on Intelligent Tutoring Systems (ITS2008). Montreal, Canada. June 2008.

• First Ph.D. Workshop in CIKM (PIKM2007). In conjunction with the ACM Conference on Information and Knowledge Management (CIKM 2007). Lisboa, Portugal. November 2007.

• Seventeenth International Conference on Applications of Declarative Programming and Knowledge Management (INAdP2007). Wuerzburg, Germany. 2007.

• Sixteenth International Conference on Applications of Declarative Programming and Knowledge Management (INAdP2005). Fukuoka, Japan. October, 2005.

• Fifteenth International Conference on Applications of Declarative Programming and Knowledge Management (INAdP2004). Berlin, Germany. March 2004.

• First ACM Symposium on Applied Computing Special Track on Declarative Data Mining (SAC-DDM 2002). Madrid, Spain, March 2002.

• Fourteenth International Conference of Applications of Prolog (INAP2001). Tokyo, Japan, Oct. 2001.

• Ninth International Conference on Information and Knowledge Management (CIKM'2000). Washington DC. November 2000.

• Thirteenth International Conference of Applications of Prolog (INAP2000). Tokyo, Japan, Oct. 2000.

• Eight International Workshop on Deductive Databases and Logic Programming (DDLP'2000). Tokyo, Japan. September 2000.

• Seventh International Workshop on Deductive Databases and Logic Programming (DDLP'99). Tokyo, Japan, Sept. 1999.

• Sixth International Workshop on Deductive Databases and Logic Programming (DDLP'98). Manchester, UK, June 1998.

• Fifth International Workshop on Deductive Databases and Logic Programming (DDLP'97). Leuven, Belgium, July 1997.

REFEREE FOR JOURNALS, CONFERENCES, AND GRANT PROPOSALS

• Referee for Journal Papers
  • Annals of Mathematics and Artificial Intelligence.
  • Artificial Intelligence Journal.
  • Data & Knowledge Engineering Journal.
  • Data Mining and Knowledge Discovery.
  • IEEE Transactions on Information Technology in BioMedicine.
  • IEEE Transactions on Knowledge and Data Engineering.
  • IEEE Transactions on Systems, Man, and Cybernetics.
  • Information Systems.
  • Journal of Logic Programming.
  • Journal of Intelligent Information Systems.
  • Logic Journal of the Interest Group in Pure and Applied Logics.
  • Pattern Recognition Letters.
  • PLOS Computational Biology.
  • PLOS ONE.
  • Theory and Practice of Logic Programming Journal.
  • The VLDB Journal.

• Referee for Book Chapters
  • Post-conference proceedings of the Kiel Declarative Programming Days (KDPD2013). Springer LNCS series. January 2014.
  • Collection of papers selected from the Workshop on Logic-Based Artificial Intelligence. June 1999.

• Referee for Conference Papers
  • See list under Member of Program Committees above.

• Reviewer for Grant Proposals
  • National Science Foundation (NSF) Directorate for Computer & Information Science & Engineering (CISE). Summer 2018.
  • National Science Foundation (NSF) Directorate for Computer & Information Science & Engineering (CISE). Division of Information and Intelligent Systems (IIS). Fall 2007.
  • National Science Foundation (NSF) Directorate for Computer & Information Science & Engineering (CISE). Division of Information and Intelligent Systems (IIS). Spring 2007.
  • National Institutes of Health (NIH) Director's Roadmap Initiative. 2005.
  • National Science Foundation (NSF) Program in Artificial Intelligence and Cognitive Science. Spring 2004.

MEMBER OF PROFESSIONAL SOCIETIES

PATENTS

ADVISING OF GRADUATE AND UNDERGRADUATE RESEARCH, AND K-12 OUTREACH

• GRADUATE RESEARCH

  Unless otherwised noticed, the graduate students listed below are/were students in the Department of Computer Science, WPI.

  • Advisor of Ph.D. Dissertations

    • Isaac Zhao (Data Science)
      "Developing and Interpreting Deep Learning Architectures for Feature Extraction of EEG Signals"
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      In Progress.

    • Sarun Paisarnsrisomsuk
      "Understanding Internal Feature Development in Deep Convolutional Neural Networks for Time Series"
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      Completed Aug. 2021.

    • Ahmedul Kabir.
      "Mixed Bagging: A Novel Ensemble Learning Framework for Supervised Classification based on Instance Hardness".
      Completed May 2018.

    • Chiying Wang.
      "Contributions to Collective Dynamical Clustering-Modeling of Discrete Time Series".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      Completed May 2016.

  • Advisor of M.S. Theses

    • Akshit (Axe) Soota
      "Exploring Internal Representations Learned by Autoencoders for Sleep EEG"
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      August 2024.

    • Xiaojun (Susan) Wang, Bioinformatics and Computational Biology
      "Bringing 'Bee-cological' Data to Life through a Relational Database and an Interactive Visualization Tool".
      Co-advisors: Prof. Robert Gegear and Prof. Elizabeth Ryder (BB and BCB, WPI)
      August 2018.

    • Michael Sokolovsky.
      "Designing Convolutional Neural Networks and Autoencoder Architectures for Sleep Signal Analysis".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      May 2018.

    • Francisco Guerrero
      "Visualizing the Behavior of Deep Neural Networks for Time Signal Classification".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      May 2018.

    • Amro Khasawneh.
      "Human Sleep Data Analysis Using Hidden Markov Models".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)

    • Shivin Misra.
      "A Database for Exploratory Analysis of Human Sleep".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College) <
      May 2008.

    • Yuan Gao.
      " Weighted Association Rules".
      Co-advisor: Prof. Elizabeth Ryder (Biology Dept.)

    • Dharmesh Thakkar.
      "Hypothesis-Driven Specialization-based Analysis of Gene Expression Association Rules".
      Co-advisor: Prof. Elizabeth Ryder (Biology Dept.).
      May 2007.

    • Stuart Floyd.
      "Data Mining Techniques for Prognosis in Pancreatic Cancer".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College)
      May 2007.

    • John Hayward.
      "Mining Oncology Data: Knowledge Discovery in Clinical Performance of Cancer Patients".
      Co-advisors: Prof. Sergio A. Alvarez (Boston College), Prof. George Heineman, and Dr. Giles Whalen (U. of Massachusetts Medical School)
      Aug. 2006.
      First Prize, Science Category, WPI Graduate Research Achievement Day (GRAD) 2006.

    • Senthil K Palanisamy.
      "Association Rule Based Classification".
      May 2006.

    • Zachary Stoecker-Sylvia.
      " Mining for Frequent Events in Time Series".
      Aug 2004.

    • Keith A. Pray.
      " Mining Association Rules from time Sequence Attributes".
      May 2004.

    • Jonathan Freyberger.
      "Using Association Rules to Guide a Search for Best Fitting Transfer Models of Student Learning".
      Co-advised with Prof. Neil Heffernan.
      May 2004.

    • Maged El-Sayed.
      "An Efficient and Incremental System to Mine Contiguous Frequent Sequences".
      Jan 2004.

    • Parameshvyas Laxminarayan.
      " Exploratory Analysis of Sleep Data".
      Co-advisors: Prof. Sergio A. Alvarez (Boston College) and Dr. Majaz Moonis (U. of Massachusetts Medical School)
      Jan 2004.

    • Aleksandar Icev.
      " Distance-Based Association Rule Mining".
      Co-advisor: Prof. Elizabeth Ryder (BBT).
      May 2003.

    • Wendy Kogel.
      " Faster Training of Neural Networks in Recommender Systems".
      Co-advisor: Prof. Sergio A. Alvarez (Boston College).
      May 2002.

    • Michael Sao Pedro.
      " Utilizing Content Information in an Association Rule Based Recommender System".
      August 2001.
      

    • Christopher Shoemaker.
      " Mining Association Rules over Set-Valued Data".
      May 2001.

    • Weiyang Lin.
      " Association Rule Mining for Collaborative Recommender Systems".
      Co-advisor: Prof. Sergio A. Alvarez.
      May 2000.

  • Member of Ph.D. Dissertation Committees

    • Erin Teeple.
      "Strategies and Structures for Biological Datasets Integration and Knowledge Discovery"
      PhD Advisor: Prof. Rundensteiner.
      PhD Dissertation completed in July 2023.

    • Oleksandr Narykov.
      "Modern Computer Science Approaches in Biology: From Predicting Molecular Functions to Modeling Protein Structure"
      PhD Advisor: Prof. Korkin.
      PhD Dissertation completed in April 2022.

    • Suhas Srinivasan.
      "Biological Discovery via Data Science: Multigranular Artificial Intelligence Approaches for Cells, Cerebra and Cruise Ships"
      PhD Advisor: Prof. Korkin.
      PhD Dissertation completed in February 2022.

    • Ermal Toto.
      "Towards Instantaneous Mental Health Screening from Voice Using Machine and Deep Learning"
      PhD Advisor: Prof. Rundensteiner.
      PhD Dissertation completed in March 2021.

    • Cansu Sen.
      "Attention-based Deep Learning Models for Text Classification and their Interpretability"
      PhD Advisors: Prof. Rundensteiner and Prof. Kong.
      PhD Dissertation completed in July 2020.

    • Qian (Steve) He.
      "Context-Aware Mobile Interventions to Mitigate Sedentary Lifestyles"
      PhD Advisor: Prof. Emmanuel Agu.
      PhD Dissertation completed in May 2017.

    • Russell Toris.
      "Knowledge Extraction and Generalized Goal State Learning from Large Scale Human Demonstrations"
      PhD Advisor: Prof. Sonia Chernova.
      PhD Dissertation completed in April 2016.

    • Yue Gong.
      "Student Modeling in Intelligent Tutoring Systems"
      PhD Advisor: Prof. Joseph Beck..
      PhD Dissertation completed in November 2014.

    • Jorge Alberto Jaramillo-Garzon.
      "Protein function prediction with semi-supervised classification based on evolutionary multi-objective optimization"
      Universidad Nacional de Colombia sede Manizales.
      PhD Advisor: Prof. Cesar German Castellanos Domínguez.
      PhD Dissertation completed in November 2013.

    • Zhenyu Guo
      "Visually Mining Interesting Patterns in Multivariate Datasets"
      PhD Advisor: Prof. Matthew Ward.
      PhD Dissertation completed in December 2012.

    • John Shutt.
      "Fexprs as the basis of Lisp function application or $vau: the ultimate abstraction"
      PhD Advisor: Prof. Michael Gennert.
      PhD Dissertation completed in September 2010.

    • Mingyu Feng.
      "Towards Assessing Students. Fine Grained Knowledge: Using an Intelligent Tutor for Assessment"
      PhD Advisor: Prof. Neil Heffernan.
      PhD Dissertation completed in August 2009.

    • Aparna Varde.
      "Domain-type-dependent Data Mining over Complex Data Types in the Heat Treating of Materials"
      PhD Advisor: Prof. Elke Rundensteiner.
      PhD Dissertation completed in August 2006.

    • Songting Chen.
      "Efficient Incremental View Maintenance for Data Warehousing"
      PhD Advisor: Prof. Elke Rundensteiner.
      PhD Dissertation completed in December 2005.

    • Maged El Sayed.
      "Incremental Maintenance of Materialized XQuery Views"
      PhD Advisor: Prof. Elke Rundensteiner.
      PhD Dissertation completed in August 2005.

    • Janet Burge.
      "Software Engineering using Design Rational (SEURAT)"
      PhD Advisor: Prof. David Brown.
      PhD Dissertation completed in April 2005.

    • Li Chen.
      "Semantic Caching for XML Queries"
      PhD Advisor: Prof. Elke Rundensteiner.
      PhD Dissertation completed in February 2004.

    • Kajal Claypool.
      "Managing Change in a Heterogeneous Environment"
      PhD Advisor: Prof. Elke Rundensteiner.
      PhD Dissertation completed in August 2002.

    • Andreas Koeller.
      "Integration of Heterogeneous Databases: Discovery of Meta-Information and Maintenance of Schema-Restructuring Views"
      PhD Advisor: Prof. Elke Rundensteiner.
      PhD Dissertation completed in November 2001.

  • Coadvisor of Research Qualifying Exams:

    • Suhas Srinivasan.
      "A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq Data"
      Summer 2020.

    • Erin Teeple.
      "Canonical Correlation Analysis"
      Summer 2019.

    • Oleksandr Narykov.
      "Determining rewiring effects of alternatively spliced isoform on protein-protein interaction using supervised and semi-supervised learning"
      Spring 2018.

    • Qian (Steve) He.
      "Characterizing the Performance and Behaviors of Runners Using Twitter "
      Fall 2014.

    • Xika Lin.
      "Online Association Rule Mining by Exploring Parameter Space"
      Spring 2011.

    • Yue Gong.
      "Improving a student model's predictive accuracy by utilizing subgroups of student performances"
      Spring 2011.

    • Zhenyu Guo.
      "User Driven Attribute Scaling and Prototype-based Multiple Classifier System"
      Spring 2010.

    • Maged El Sayed.
      "Incremental prediction for users' access patterns"
      Spring 2002.

    • Aparna Varde.
      "The SWECCA Approach: Incremental Maintenance of Data Warehouses with Multi-Relation Sources"
      Fall 2001.

    • Hong Su.
      "Automating the translation of XML documents"
      Fall 2000.

  • Reader for Master's theses:

    • Hongzhu Cui
      Boosting Gene Expression Clustering with System-Wide Biological Information and Deep Learning
      M.S. in Computer Science
      Advisor: Professor Dmitry Korkin (CS, BCB)
      May 2019

    • Xitong Zhang
      "vU-net: edge detection in time-lapse fluorescence live cell images based on con-volutional neural networks"
      M.S. in Computer Science
      Advisors: Professor Kwonmoo Lee (BME) and Professor Dmitry Korkin (CS, BCB)
      May 2018

    • Chong Zhou
      "Robust Auto-encoder"
      M.S. in Data Science
      Advisor: Professor Randy C. Paffenroth
      May 2016

    • Zachary Broderick
      "Increasing parent engagement in student learning using an Intelligent Tutoring System with Automated Messages"
      Advisor: Prof. Neil Heffernan
      March 2011

    • Suvesh Pratapa
      "Improving Latency in the Crankshaft - An energy-aware MAC protocol for Wireless Sensor Networks"
      Advisor: Prof. Robert Kinicki
      Dec. 2009

    • Richard Skowyra
      "An Energy-Efficient Dynamic Reclustering Strategy for Wireless Sensor Networks"
      Advisor: Prof. Robert Kinicki
      May 2009

    • Nicholas M. Lloyd
      "Measuring Student Engagement in an Intelligent Tutoring System"
      Advisor: Prof. Neil Heffernan
      May 2007

    • Di Yang
      "Analysis Guided Visual Exploration of Multivariate Data"
      Advisors: Prof. Elke Rundensteiner and Prof. Matthew Ward
      May 2007

    • Jason Walonoski
      "Visual Feedback for Gaming Prevention in Intelligent Tutoring Systems"
      Advisor: Prof. Neil Heffernan
      January 2006

    • Tyler Yuan
      "Coevolving Voters for a Classification Task: Cooperative Coevolution for Financial Forecasting"
      Advisor: Prof. Lee Becker
      February 2005

    • Katica Dimitrova
      "Order-sensitive View Maintenance of Materialized XQuery Views"
      Advisor: Prof. Elke Rundensteiner
      May 2003

    • Mukund Seshadri
      "Genetic Programming for Understandable Technical Trading Rules"
      Advisor: Prof. Lee Becker
      May 2003

    • Jehad Al-Sabbah
      "Recovery of Data Warehouse using Distributed Query Adaptation"
      Advisor: Prof. Elke Rundensteiner
      July 2002

    • Kurt W. Deschler
      "A Dynamic Index for Efficient XML Path Evaluation"
      Advisor: Prof. Elke Rundensteiner
      May 2002

    • Manish Pangliya, Dept. of Biology and Biotechnology, WPI
      "Single Nucleotide Polymorphism Analysis in Application to Fine Gene Mapping"
      Advisor: Prof. Julia Krushkal (BBT)
      May 2001

    • Lingli Ding
      "Scalable Maintenance of Multiple Interrelated Data Warehousing Systems"
      Advisor: Prof. Elke Rundensteiner
      January 2001

    • Luping Quan,
      "XQL-Based Web Query Repository"
      Advisor: Prof. Elke Rundensteiner
      July 2000

    • Daniel Stroe
      "Speculative Prefetching for Exploratory Data Analysis"
      Advisor: Prof. Elke Rundensteiner and Prof. Matthew Ward
      May 2000

    • Shawn Nicholson
      "A Test-bed for Distributed Multi-Agent Learning using Coactive Cooperation"
      Advisor: Prof. Lee Becker
      May 1999

    • Janet Burge
      "Knowledge Elicitation for Design Task Sequencing Knowledge"
      Advisor: Prof. David Brown
      December 1998

• UNDERGRADUATE RESEARCH

  • Advisor of Undergraduate Graduation Projects (MQPs)

    • Aidan Burns, Lauren Flanagan, and Smera Gora
      "Machine Learning in Pain Medicine" In Progress.
      Co-advised with Prof. Ben Nephew (BB, NEU).
      2022-2023 academic year.

    • Eri Kim and Patrick Mejia
      "Sleep Health App" In Progress.
      2022-2023 academic year.

    • Sophia Strano
      "Visualization of Butterfly-Plant Interaction Data" In Progress.
      Co-advised with Prof. Elizabeth Ryder (BB, BCB).
      2022-2023 academic year.

    • Aidan Pecorale and Jared Poulos
      "Expanding Beecology Project's Web Application for Butterfly Observations"
      Co-advised with Prof. Elizabeth Ryder (BB, BCB).
      2021-2022 academic year.

    • Andrew Ressler and Meadow Wicke.
      "Exploratory Cluster Analysis of Bumblebee and Plant Interaction Data"
      Co-advised with Prof. Elizabeth Ryder (BB, BCB).
      2020-2021 academic year.

    • Kirsten Hart.
      "Designing High School CS Curriculum to Address Real-World Biological Problems with Computational Thinking"
      Co-advised with Prof. Elizabeth Ryder (BB, BCB).
      2020-2021 academic year.

    • Sarah Armstrong, Ching Wing Cheng, Elizabeth Del Monaco, Shine Linn Thant.
      "Developing a Sleep Health Web Application for College-Age Users"
      2019-2020 academic year.

    • Holly Nguyen
      "Using Personality Traits and Chronotype for Personalized Feedback in a Sleep Web App"
      2017-2018 academic year.

    • Jacob A. Moon and Ziyang (Gavin) Yu
      Bee-cology: A Citizen Science Mobile App
      Co-advised with Prof. Robert Gegear and Prof. Elizabeth Ryder (BB, BCB).
      Summer 2017.

    • Theresa Inzerillo, Preston Mueller
      Predicting Ischemic Stroke Recovery with Data Mining
      Co-advised with Prof. Sergio A. Alvarez (Boston College)
      2016-2017 academic year.

    • Michael Harney and Qiaoyu Liao
      Developing Behavioral Interventions and Visual Intervention Displays for a Mobile Health Application
      Co-advisor: Prof. Bengisu Tulu (Business School, WPI).
      In collaboration with Dr. Sherry Pagoto and other members of the Univ. of Massachusetts Center for mHealth and Social Media.
      2016-2017 academic year.

    • Jackson Oliva
      Citizen Science Bee Ecology
      Co-advised with Profs. Robert Gegear and Elizabeth Ryder (Biology).
      2016-2017 academic year.

    • Joseph (Randy) Acheson, Joshua Allard, Andrew Busch, and Andrew Roskuski
      SlipBuddy: A Machine Learning based Mobile Health App to Track and Prevent Overeating
      Co-advisor: Prof. Bengisu Tulu (Business School, WPI).
      In collaboration with Dr. Sherry Pagoto and other members of the Univ. of Massachusetts Center for mHealth and Social Media.
      2015-2016 academic year.

    • Sean Amos and Essam Al-Mansouri
      Using Artificial Neural Networks and Sentiment Analysis to Predict Upward Movements in Stock Price
      Co-advised with Prof. Hossein Hakim (ECE, WPI) and Prof. Michael Radzicki (SSPS, WPI)
      2015-2016 academic year.

    • Andrew McKay and Patrick Murphy
      Data Preprocessing for Advanced Analytics
      Sponsored by QueBIT
      2014-2015 academic year.

    • Alexander Gorowara and Christina Webb
      Predicting Clicks on Mobile Ads
      Sponsored by Chitika
      2014-2015 academic year.

    • Tyler Stone and Ryan McKenna
      Trading in the Financial Market using Data Mining
      Co-advised with Prof. Hossein Hakim (ECE, WPI) and Prof. Michael Radzicki (SSPS, WPI)
      2014-2015 academic year.

    • Philip Davidson and Justin Liu
      Analysis of Microarray Data to Confirm Novel Subtype of Breast Cancer
      Co-advised with Prof. David Adams (Biology) and Prof. Karl Simin (UMass Medical School)
      April 2010.
      

    • Andreea Bodnari
      Mapping Text to Knowledge using Natural Language Processing
      Co-advised with Prof. Gary Pollice
      March 2010.
      Honorable Mention, Provost's MQP Award for Computer Science, 2009-2010.
      

    • Gregory Barrett
      Gene Expression Classification
      Co-advised with Prof. Elizabeth Ryder (BBT Dept., WPI)
      March 2010.
      

    • Jonathan Rudolph
      Gene Expression Rule Modeling
      Co-advised with Prof. Elizabeth Ryder (Biology).
      In progress.

    • Piotr Mardziel
      Improved Two-Dimensional Warping
      Co-advised with Prof. Sergio A. Alvarez (Boston College)
      Aug. 2005.
      Winner, Provost's MQP Award for Computer Science, 2005-2006.
      

    • Michael McCowan and James Martineau
      Spam Filtering using Bayesian Networks
      Co-advised with Prof. Sergio A. Alvarez (Boston College)
      2004-2005.

    • Eduardo Paredes
      Post-Processing of Association Rules
      2003-2004.

    • Iavor N. Trifonov
      Predicting Extreme Stock Performance using Cooperative Coevolution
      Co-advised with Prof. Lee A. Becker. 2003-2004.

    • Takeshi Kawato
      Multi-Expert Neural Networks for Recommendation
      Co-advised with Sergio A. Alvarez (Boston College)
      2002-2003.

    • Cindy Leung and Sam Holmes
      Exploring Temporal Associations in the Stock Market
      2002-2003.

    • John Baird, Jay Farmer, Rebecca Gougian, Ken Monterio, Paul Young
      Motif Analysis of Gene Expression
      Co-advised with Prof. Elizabeth Ryder (Biology).
      Interdisciplinary CS/BBT project.
      2002-2003.

    • Zachary Stoecker-Sylvia.
      "Merging the Association Rule Mining Modules of the Weka and ARMiner Data Mining Systems".
      2001-2002.

    • Kristin Blitsch, Ben Lucas, Sarah Towey
      "Computational Analysis of Gene Expression".
      Co-advised with Prof. Elizabeth Ryder (Biology).
      Interdisciplinary CS/BBT project.
      2001-2002.

    • Wendy Kogel, Brooke LeClair, and Christopher St. Yves.
      " SCoRs: A Content and Collaborative Based Recommender System".
      2000-2001.

    • Brian Murphy and David Phu and Ian Pushee and Frederick Tan.
      " Motif- and Expression-Based Classification of DNA".
      Co-advised with Prof. Elizabeth Ryder (Biology) and Prof. Julia Krushkal (Biology).
      Honorable Mention, Provost's MQP Award for Computer Science, 2001.
      2000-2001.

    • Daniel Doyle and Jared Judecki and James Lund and Bryan Padovano.
      " Genomic Data Mining".
      Co-advised with Prof. Julia Krushkal (Biology), and Prof. Elizabeth Ryder (Biology).
      2000-2001.

    • Christopher Cole.
      " Mining State Machine Simulations".
      Co-advised with Prof. Kathi Fisler.
      2000-2001.

    • Michael Ciman and John Gulbrandsen.
      " Mining Functional Dependencies".
      Co-advised with Prof. Elke Rundensteiner.
      2000-2001.

    • Tara Halwes
      " Transformation-Based Similarity Methods for Sequence Mining".
      Co-advised with Prof. Sergio A. Alvarez.
      Winner, Provost's MQP Award for Computer Science, 2001.
      1999-2000.
      

    • Christopher Martino.
      " Comparing the Effectiveness of MineSet and Intelligent Miner in Knowledge Extraction".
      Co-advised with Prof. Matthew Ward.
      1999-2000.

    • Matthew Berube.
      " TinFOIl: A System for Learning Rules from Examples".
      Co-advised with Prof. Sergio A. Alvarez.
      Winner, Provost's MQP Award for Computer Science, 2000.
      1998-1999.

    • Anna Novikov.
      " Combination of Relevance Rankings for Web Metasearch".
      Co-advised with Prof. Sergio A. Alvarez.
      1998-1999.

    • Amy Kao and Dana Rock.
      " Collaborative and Content-Based Filtering Using Neural Networks".
      Co-advised with Prof. Sergio A. Alvarez.
      1998-1999.

  • Advisor of Undergraduate Technology/Society Projects (IQPs)

    • Christian Cedron
      "Making the Bio-CS Bridge Accessible to High School Teachers and Students"
      Co-advised with Prof. Liz Ryder (BBT) and Prof. Robert Gegear (BBT)
      2018-2019.

    • Alexander Michelson, Amanda Moulaison, Alejandro Soler-Gayoso, Zachary Weiland
      "Improving Science Communication Outreach in Wellington: An Analysis of Public Knowledge of Sea Level Rise in the Central Business District of Wellington, New Zealand"
      Co-advised with Prof. Michael Elmes (Foisie Business School).
      Sponsored by Antarctic Research Center, Victoria University of Wellington
      WPI New Zealand Project Center. C Term 2018.

    • Edward Andrews, Juliana Cabello, Tristin Carlton, Holly Gagnon, Malachi Nelson
      "Designing and Prototyping an Interactive Ice Core Exhibition at the Museum of New Zealand Te Papa Tongarewa"
      Co-advised with Prof. Michael Elmes (Foisie Business School).
      Sponsored by Museum of New Zealand Te Papa Tongarewa
      WPI New Zealand Project Center. C Term 2018.

    • Heather Bourassa, Peter Luro, Toby Macaluso, Alana Sher
      "Living with Flood Protection in the Hutt Valley"
      Co-advised with Prof. Michael Elmes (Foisie Business School).
      Sponsored by Greater Wellington Regional Council
      WPI New Zealand Project Center. C Term 2018.

    • Azita Bakhtyari, Aidan Cookson, Austin McCalmont, and Madison Michaud
      "Designing a Forestry Stewardship Council (FSC) Community Campaign for Wellington Zoo"
      Co-advised with Prof. Michael Elmes (Foisie Business School).
      Sponsored by Wellington Zoo
      WPI New Zealand Project Center. C Term 2018.

    • Toni Joy, Nathaniel Mione, Bryannah Voydatch, and William Wartman
      "Evaluating the Effects of Wellington's Animal Bylaw and Snip'n'Chip Campaign"
      Co-advised with Prof. Michael Elmes (Foisie Business School).
      Sponsored by Wellington City Council
      WPI New Zealand Project Center. C Term 2018.

    • Madeline Burke, Kaleigh Iler, Kellen Randall, Ana Restrepo
      "What Makes Dog Owners Unique?"
      Co-advised with Prof. Michael Elmes (Foisie Business School).
      Sponsored by New Zealand Department of Conservation - Marine Mammals
      WPI New Zealand Project Center. C Term 2018.

    • Eoin J. O'Connell, Kenneth Levasseur, Samuel Christopher Coache
      "The Beecology Project: Providing tools and information to promote citizen scientist participation in solving pollinator decline"
      Co-advised with Prof. Robert Gegear (BBT) and Prof. Liz Ryder (BBT)
      2017-2018

    • Devin T. Stevens, Kenedi E. Heather, Rachel Lee Murphy
      "Bee-cology"
      Co-advised with Prof. Robert Gegear (BBT) and Prof. Liz Ryder (BBT)
      2016-2017

    • Nysa Casha, Shuyang Sun, Angela Conklin, George Benda.
      "Improving Visitor Evaluation at the British Postal Museum and Archive".
      Co-advised with Prof. Ingrid Shockey (IGSD).
      Sponsored by The British Postal Museum and Archive (BPMA).
      WPI London Project Center. Summer 2014.

    • Yi Sun, Will Evangelakos, and Sean Greene.
      "Crossrail Community Investment Program - Establishing Benchmarks for Community Investment Programs".
      Co-advised with Prof. Ingrid Shockey (IGSD).
      Sponsored by Crossrail Ltd.
      WPI London Project Center. Summer 2014.

    • Jason Klein, Shuhan Liu, Kevin Lynch, and Alex Manternach.
      "Business Biking in Croydon".
      Co-advised with Prof. Ingrid Shockey (IGSD).
      Sponsored by Croydon City Council.
      WPI London Project Center. Summer 2014.

    • Charles Frick, Nicholas Lemere, Alexander Shoop, and Stefan Smith.
      "Analysis of Consumer Energy Behavior in the Arboretum".
      Co-advised with Prof. Ingrid Shockey (IGSD).
      Sponsored by The University of Worcester, England.
      WPI London Project Center. Summer 2014.

    • Peter Craft, Rebecca Lee, and William Spurgeon.
      "RGS-IBG Expeditions Database and Report Collection".
      Co-advised with Prof. Ingrid Shockey (IGSD).
      Sponsored by The Royal Geographical Society (with the Institute of British Geographers) (RGS-IBG).
      WPI London Project Center. Summer 2014.

    • Colbert Sesanker, K Zin Thet, and Jonathan Wong.
      "Human Sleep Disorders: Apnea and its diagnosis using the ECG".
      Co-advised with Prof. Sergio A. Alvarez (Boston College).
      2009-2010.

    • Soe San Win.
      "Analysis of Societal and Technical Aspects of Human Sleep".
      Co-advised with Prof. Sergio A. Alvarez (Boston College).
      2009-2010.

    • Andreea Bodnari and Towa Matsumura.
      "Computationally Enhanced Medical Decision Support for Pancreatic Cancer".
      2007-2008.

    • Jared Judecki and Eric Rackliff.
      "Web-based Teaching Evaluations".
      Co-advised with Prof. Judith Miller (CEDTA).
      1999-2000.

    • Khue Bich Huynh and Tim Nguyen.
      "The Effect of Instructor Gender and Student Gender on Course Evaluations".
      Co-advised with Prof. Judith Miller (CEDTA).
      1998-1999.

• K-12 OUTREACH AND RESEARCH ADVISING

  • Bioinformatics and Computational Biology Summer Research Experience (BCB-SRE) for High School Students
    • Summer 2018: June 26 - July 27, 2016
    • Summer 2017: June 27 - July 28, 2016
    • Summer 2016: June 28 - July 29, 2016
    I conceived and have co-directed with Prof. Liz Ryder this 5-week program, which brings selected high school rising juniors and seniors to our BCB research labs to work with WPI faculty, graduate and undergraduate students on research projects using Computer Science and Mathematics to solve problems in Biology and Medicine. The program has generated a great deal of interest among high school students. We have had strong cohorts of students (21 in 2016, 17 in 2017, and 19 in 2018) selected among a large pool of applicants. Research advisors in this program have included WPI faculty in the Bioinformatics and Computational Biology Program across 4 departments: Biology: Profs. Gegear, Ryder, Shell and Vidali; Computer Science: Profs. Harrison, Korkin and Ruiz; Mathematics: Prof. Olson, Servatius and Wu; Physics: Prof. Tuzel.

  • "What is Bioinformatics?" 3-hour session
    Together with Prof. Elizabeth Ryder
    Women in Science Workshop
    WPI K-12 outreach for 7th grade female students interested in STEM
    July 22, 2016

• Graduate Courses:

  • Biological and Biomedical Database Mining. BCB503 / CS583
    • Fall 2019 (co-located with CS548)
    • Fall 2018 (co-located with CS548)
    • Fall 2017 (co-located with CS548)
    • Fall 2016 (co-located with CS548)
    • Spring 2016 (co-located with CS548)
    • Fall 2013
    • Fall 2011

  • Knowledge Discovery and Data Mining. CS548 / CS525 KDD
    • Fall 2019
    • Fall 2018
    • Fall 2017
    • Fall 2016
    • Spring 2016
    • Spring 2015
    • Spring 2014
    • Spring 2012
    • Fall 2009
    • Spring 2008
    • Spring 2004
    • Fall 2001
    • Fall 1999

  • Machine Learning. CS539
    • Spring 2017
    • Fall 2015
    • Fall 2014
    • Fall 2012
    • Spring 2011
    • Spring 2009
    • Spring 2007
    • Spring 2005
    • Spring 2003
    • Fall 2000
    • Spring 1999

  • Artificial Intelligence. CS534
    • Spring 2019
    • Spring 2013 (Cisco)
    • Fall 2007
    • Fall 2006
    • Fall 2005
    • Spring 1998

  • Independent Study Courses on Machine Learning and Data Mining
    • Most semesters since Fall 2000.

  • Independent Study Course on Mathematical Logic.
    • Fall 1997

• Undergraduate Courses:

  • Biological and Biomedical Database Mining. BCB4003 / CS4803
    • A term 2013 (Aug. to Oct. 2013)
    • A term 2011 (Aug. to Oct. 2011)

  • Data Mining and Knowledge Discovery in Databases. CS444X and CS4445
    • B term 2014 (Oct. to Dec. 2014)
    • B term 2012 (Oct. to Dec. 2012)
    • B term 2010 (Oct. to Dec. 2010)
    • A term 2008 (Aug. to Oct. 2008)
    • B term 2006 (Oct. to Dec. 2006)
    • A term 2004 (Aug. to Oct. 2004)
    • D term 2004 (Mar. to April 2004)
    • D term 2003 (Mar. to April 2003)

  • Introduction to Artificial Intelligence. CS4341
    • A term 2017 (Aug. to Oct. 2017)
    • B term 2003 (Oct. to Dec. 2003)
    • C term 2002 (Jan. to Feb. 2002)
    • D term 2001 (Mar. to May 2001)
    • C term 2000 (Jan. to Mar. 2000)
    • A term 1997 (Aug. to Oct. 1997)

  • Theory of Computation. CS4123
    • B term 2004 (Oct. to Dec. 2004)
    • B term 2002 (Oct. to Dec. 2002)
    • D term 2002 (Mar. to May 2002)
    • A term 1999 (Aug. to Oct. 1999)
    • B term 1997 (Oct. to Dec. 1997)

  • Foundations of Computer Science. CS3133
    • A term 2009 (Aug. to Oct. 2009)

  • Algorithms. CS2223
    • D term 2015 (Mar. to May 2015)
    • B term 2013 (Oct. to Dec. 2013)
    • D term 2009 (Mar. to May 2009)
    • D term 2008 (Mar. to May 2008)
    • B term 2005 (Oct. to Dec. 2005)

  • Programming Language Concepts. CS2135
    • A term 2000 (Aug. to Oct. 2000)
    • A term 1998 (Aug. to Oct. 1998)

• Invited Lecturer, Dept. of Computer Science. Univ. of Pittsburgh. 1997

• Invited Lecturer, Dept. of Computer Science. Univ. of Maryland at College Park. 1995-1996

• Graduate Teaching Assistant, Dept. of Mathematics. Univ. of Maryland at College Park. 1990-1992

• Instructor, Dept. of Computer Science. Univ. of Los Andes. 1989-1990.

• Teaching apprentice, Dept. of Mathematics. Univ. of Los Andes. 1988-1989

• Campus-wide Service

  • Faculty Appointee:

    • WPI Board of Trustees' Academic Planning Committee. 2020-2022.

  • Elected Member, Faculty Governance Standing Committees:

    • WPI Committee on Tenure and Academic Freedom (CTAF). 2013-2017.

    • WPI Committee on Academic Policy (CAP). 2008-2011. Secretary Fall 2009. Chair Spring 2010.

    • WPI Committee on Academic Operations (CAO). 1998-2001.

  • Faculty Member, WPI's Center for Project-Based Learning:

    • Faculty co-presenter and co-facilitator (with Prof. Kristin Wobbe) of a 2-day workshop on Project-Based Learning at the Vellore Institute of Technology. Vellore, India. April 11-12, 2019.

    • Faculty coach of a national university team attending the WPI Summer Institute for Project-based Learning, Summer 2019.

    • Faculty coach of a national university team attending the WPI Summer Institute for Project-based Learning, Summer 2018.

    • Faculty coach of an international university team attending the WPI Summer Institute for Project-based Learning, Summer 2017.

  • WPI's Healthcare Delivery Institute (HDI):

    • Member, HDI's Steering Committee. 2014-present.

    • Member, UMass-HDI Steering Committee. 2013-present.
      This committee's mission is to plan strategic collaborations and to investigate and explore opportunities of mutual interest and benefit to both the HDI and the University of Massachusetts Medical School.

  • Campus-wide Hiring Committees:

    • President's representative to the Humanities and Arts Department Head Search Committee. 2006-2007.

    • President's representative to the Electrical and Computer Engineering Department Head Search Committee. 2002-2003.

    • Member, Bioinformatics Faculty Search Committee. 2002-2003.

  • Faculty mentor, WPI's Mentoring Program For New Faculty. 2006-2018.

  • Judge, Graduate Research Achievement Day (GRAD) 2007-Present.

  • Faculty representative to the WPI Community Council. 2003-2004.

  • Member, ad hoc Committee on Maternity Benefits. 1999-2000.

  • Organized and hosted several Campus-wide Colloquia during the 1998-2000 academic years.

• Service to the Department and Programs

  • Bioinformatics and Computational Biology (BCB) Program:

    • BCB Faculty Steering Committee. 2009-present.
      This committee has introduced new BS, BS/MS, MS, and PhD degree programs in BCB at WPI. In addition, this committee helps the BCB program director oversee these degree programs at WPI.

  • Data Science (DS) Program:

    • DS Faculty Steering Committee. 2013-present.
      This committee has introduced new MS, PhD, BS and BS/MS degree programs in DS at WPI. In addition, this committee helps the DS program director oversee these degree programs at WPI.

  • Neuroscience (NEU) Program:

    • NEU Faculty Steering Committee. 2017-present.
      This committee has introduced a new MS degree program in NEU at WPI. In addition, this committee is currently preparing a new BS degree in NEU.

  • Computer Science (CS) Department:

    • Major Departmental Service Roles:

      • Associate Department Head. 2018-Present.

      • CS Graduate and Research Coordinator. 2009-2012.

      • Chair, Computer Science Graduate Committee. 2009-2012.

      • Chair, Computer Science Graduate Admissions Committee. 2009-2012.

      • Member, Computer Science Graduate Committee. 1997-1998, 2006-2012.

      • Member, Computer Science Undergraduate Committee. 2016-2017.

      • Member, Computer Science Faculty Promotions Committee. 2011-2013.

      • Member, Computer Science Faculty Hiring Committee. 2018-2019.

      • Member, External Assessment Committee, 2013-2014.

    • Other Departmental Service Roles:

      • Artificial Intelligence Graduate Bin Committee.

      • Faculty member, Graduate Council. 2000-2005.

      • Chair, PhD Qualifying Exam Committee. 2000-2005.

      • CS Library Liason. 2000-2002.

      • Organizer, Computer Science Colloquium. 1999-2000 and 1998-1999

      • Founder and Coordinator, Knowledge Discovery and Data Mining Research Group (KDDRG). 1998-Present.

      • Coordinator, Artificial Intelligence Research Group (AIRG). Spring 09, Fall 08, Spring 05, Fall 04, Spring 00, Fall 99, Spring 99, and Fall 98.

      • CS TR Coordinator. 2007-2008, 2006-2007.

      • Undergraduate Placement Exam Committee. 1998-2000.

      • CS Graduate Applications Review Committee. D term 2004.

      • Member, Task Force for attracting female high school students to enroll in CS major. 1998-2001.