WPI Worcester Polytechnic Institute

Computer Science Department

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2013-2014 Colloquium Series
Planning Page

* * * This Page is Frequently Updated * * *
| Fall 2013 | Spring 2014 |

All Colloquia are from 11am until noon, unless otherwise stated

Potential and actual colloquium speakers should look at the FAQ for answers to typical questions about their visit.

Colloquium Coordinators: 2013-2014: Profs. Lindeman, Pollice


Fall 2013

Date Room Speaker Talk
30 Aug. 2013
Friday
11 am
Fuller Labs, 320   - -
6 Sep. 2013
Friday
11 am
Fuller Labs, 320   - -
13 Sep. 2013
Friday
11 am
Fuller Labs, 320   Prof. Jason H. Moore, Dartmouth College Computational Intelligence Approaches to Human Genetics
16 Sep. 2013 Monday
11 am
Fuller Labs, 320  
Steven Hurd,
Sandia National Laboratories
Successfully Transitioning Promising Research to Practice
20 Sep. 2013
Friday
11 am
Fuller Labs, 320  
-
27 Sep. 2013
Friday
11 am
Fuller Labs, 320 John Ridgeway TBD
4 Oct. 2013
Friday
11 am
Fuller Labs, 320   CS Faculty Mtg External Review Issues
11 Oct. 2013
Friday
11 am
Fuller Labs, 320  
-
18 Oct. 2013
Friday
11 am
Fuller Labs. 320 Semester Break
No Colloquium
25 Oct. 2013
Friday
11 am
Fuller Labs. 320 Semester Break No Colloquium
1 Nov. 2013
Friday
11 am
Fuller Labs, 320   Dr. Ayan Banerjee,
Arizona State University
TBD
8 Nov. 2013
Friday
11 am
Fuller Labs, 320   Dr. Nils Gehlenborg, Harvard Medical School and Broad Institute of MIT and Harvard
TBD
15 Nov. 2013
Friday
11 am
Fuller Labs, 320   - -
22 Nov. 2013
Friday
11 am
Fuller Labs, 320   - -
29 Nov. 2013
Friday
11 am
   Thanksgiving Holiday, No Colloquium
6 Dec. 2013
Friday
11 am
Fuller Labs, 320   Dr. Lee Osterweil, U.niversity of  Massachusetts
TBD
13 Dec. 2013
Friday
11 am
Fuller Labs, 320   Andras Kornai, Budapest Institute of Technology TBD
20 Dec. 2013
Friday
11 am
Fuller Labs, 320   - -



Spring 2014

Date Room Speaker Talk
17 Jan. 2014
Friday
11am  
Fuller Labs, 320   Dr. Dmitry Korkin, BCB/CS Candidate

Dr. Dmitry Korkin is an Associate Professor in the Department of Computer Science, Informatics Institute, and Bond Life Science Center at the University of Missouri-Columbia. Prior to joining University of Missouri in 2007, he was a postdoc at the University of California, San Francisco and Rockefeller University. He obtained his Ph.D. in 2003 at the University of New Brunswick, Canada. Dr. Korkin's areas of research include bioinformatics, machine learning and data mining, and computational genomics. His recent awards include 2009 National Science Foundation CAREER Award and 2013 Junior Research Faculty of the Year Award. His research projects are supported through National Science Foundation and University of Missouri funding programs.

Data-driven bioinformatics: From studying complex diseases to understanding genomic evolution

With the unprecedented advancement of the next-generation sequencing and high-throughput -omics technologies, the challenges of biomedical research are becoming data-driven, requiring development of the informatics methods for rapid integration, processing, and analysis of the massive amounts of data. The data-driven informatics research has also become an integral component of studying complex diseases, such as genetic disorders and deadly infections, which constitute the major health threat in the modern society, with a tremendous economic impact on health care. My presentation consists of four parts. I will first talk about our recent progress in developing computational and informatics methods to study complex genetic diseases, such as cancer, diabetes, and neurological disorders. Next, I will highlight current bioinformatics projects geared towards studying host-pathogen interactions in viral, bacterial, and parasitic infections. I will talk about our progress in mining host-pathogen-interaction data from the literature, understanding the evolution of influenza virus, and developing an integrative computational epidemiology model. In the third part of the talk, I will introduce another research problem—identifying and characterizing long identical multispecies elements (LIMEs), the genomic regions that were slowed down through the course of evolution to their extremes. I will discuss our recent findings of the LIMEs in animals and plants, computational challenges associated with expanding our results towards other species, and a Big Data driven informatics approach to tackle these challenges. I will conclude with the discussion of my future research plans and will outline possible collaborative opportunities.

24 Jan. 2014
Friday
11am  
Fuller Labs, 320   Adam Groce, University of Maryland -
31 Jan. 2014
Friday
11am  
Fuller Labs, 320   - -
7 Feb. 2014
Friday
11am  
Fuller Labs, 320   David Wolinsky, Yale / Univ. of Florida -
10 Feb. 2014
Monday
11am  
Atwater-Kent 233   Randy Paffenroth, Univ. of Maryland / Numerica -
11 Feb. 2014
Tuesday
11am  
Fuller Labs, 320   Yinzhi Cao, Northwestern -
14 Feb. 2014
Friday
11am  
Fuller Labs, 320   Dr. Juan Banda, Montana State Univ.

Dr. Juan M. Banda is currently a post-doctoral research associate at Montana State University. He received his Ph.D. degree in Computer Science in 2011 from Montana State University and his M.A degree in Mathematics from Eastern New Mexico University. His main research interests lie in data science, particularly in the big data mining area, and specifically in the knowledge acquisition from massive real-life data sources. Dr. Banda has published over 25 journal articles, book chapters and peer-reviewed conference papers in these areas. His research has been constantly sponsored by the federal agencies such as NASA since 2008.

What we can learn from mining the Sun

With the launch of the NASA's Solar Dynamics Observatory (SDO) Mission, a new chapter of solar data analysis was started. Producing over 70,000 high-resolution images per day, the SDO mission produces an unprecedented amount of data: 1.5 terabytes of data per day. Traditional methods of data analysis were not feasible with this massive amount of data; hence, NASA funded the Feature Finding Team (FFT) to tackle this problem. The majority of the FFT modules are task-specific, except our trainable module. This talk will discuss the process behind the trainable module's task of building a content-based image retrieval system for the SDO mission. Starting from the selection of features to represent our solar image data and going through dissimilarity evaluation, clustering, dimensionality reduction, indexing, and retrieval, to the successful deployment of the first version of the SDO CBIR system. This talk will address some of the most important challenges of searching through the whole SDO repository, and solutions uncovered along this process.

14 Feb. 2014
Friday
2pm  
Fuller Labs, 320   Dr. Hosam M. Mahmoud, The George Washington University

Hosam Mahmoud (Professor of Statistics, 1983 Ph.D. in computer science) is an elected member of the International Statistical Institute. He currently serves as an Editor of Journal of Applied Probability, Editor of Advances in Applied Probability (British publications), and Editor-in-Chief of Online Journal of Discrete Mathematics. He is also an Associate Editor of the Annals of the Institute of Statistical Mathematics (Japan) and an Associate Editor of Methodology and Computing in Applied Probability (USA).

He has research interest in the areas of probabilistic analysis of algorithms, searching and sorting, random structures, and randomized algorithms. He has served as department chair in 1998-2001, and visited numerous institutions worldwide. Dr. Mahmoud is a productive scholar with three books and more than 80 peer-refereed papers, many are in premier journals.

Professor Mahmoud spent sabbatical visits at University of Waterloo (Waterloo, Canada, 1990), Institut National de Recherche ( Rocquencourt, France, 1997), Princeton University (Princeton, New Jersey, USA, 1998), the Institute of Statistical Mathematics (Tokyo, Japan, 2004) and Purdue University (West Lafayette, Indiana, USA, 2012).

Analysis of Quickselect under Yaroslavskiy's Dual-Pivoting Algorithm

There is excitement within the algorithms community about a new partitioning method introduced by Yaroslavskiy. This algorithm renders Quicksort slightly faster than the case when it runs under classic partitioning methods. We show that this improved performance in Quicksort is NOT sustained in Quickselect; a variant of Quicksort for finding order statistics.

We investigate the number of comparisons made by Quickselect to find a key with a randomly selected rank under Yaroslavskiy's algorithm. This grand averaging is a smoothing operator over all individual distributions for specific fixed order statistics. The grand distribution of the number of comparison (when suitably scaled) is given as the fixed-point solution of a distributional equation of a contraction in the Zolotarev metric space. The limiting distributions is a "perpetuity" (a sum of products of independent mixed continuous random variables).

17 Feb. 2014
Monday
11am  
Atwater-Kent 233   Martha White, Univ. of Alberta -
18 Feb. 2014
Tuesday
11am  
Fuller Labs, 320   Gianluca Stringhini, UC Santa Barbara -
21 Feb. 2014
Friday
11am  
Fuller Labs, 320   NO SPEAKER -
25 Feb. 2014
Tuesday
11am  
Fuller Labs, 320   Michelle Mazurek, CMU -
28 Feb. 2014
Friday
11am  
Fuller Labs, 320   Prof. Magy Seif El-Nasr, Associate Professor & Director of Game Design, Northeastern University

Magy Seif El-Nasr is an associate Professor in the Colleges of Computer and Information Sciences and Arts, Media and Design, where she directs the PLAIT (Playable Innovative Technologies) Lab. Dr. Seif El-Nasr earned her Ph.D. degree from Northwestern University in Computer Science. Her research focuses on the intersection between artificial intelligence, human computer interaction, and scientific driven game design and development. She has developed computational tools and models of emotions and believable characters. She also focuses on developing methods for evaluating and adapting interactive media and game experiences. She led several federal funded projects on game user behavior analytics, evaluation methodology of interactive experiences (narrative and media), and measurements of engagement. She worked collaboratively with industry partners, including Ingiteplay, Electronic Arts, and Bardel Entertainment. She recently published two co-edited books: Game Analytics: Maximizing the value of player data and Nonverbal Communication in Virtual Worlds.

Assessing the Longitudinal Impact of Games for Health using Game Analytics

Recent reports show that about 34.4% of the U.S. adults above 20 years old are overweight; it is projected that 86% of the adult population will be either at risk for obesity or obese by 2030. Major causes for such epidemic are a sedentary lifestyle and poor diet. In the past few years, many interventions have been proposed, including different kinds of exergames, social games, or other forms of mobile media apps. For the past three years we have formed a collaboration with a gaming company to develop and evaluate a social game environment called SpaPlay(tm) (IgnitePlay, 2011) built based on theoretical principles of Self-Determination theory. Players build and run a virtual "health Spa resort," and its growth and success is tied to health-based activities that players undertake in real life. Examples of activities include choosing a healthy snack, including vegetables in a diet, climbing stairs, and walking. Players engage in quests, which include long chain of activities taken alone or in a group. The online community of fellow players creates opportunities for vicarious learning, motivation, and mutual support. In this presentation I will (1) describe the game and the theory behind its design, (2) discuss current results showing sustained engagement in the game, and (3) discuss a new methodology that we developed to allow for effective assessment of a health game triangulating across in-game behavior data, motivational data, as well as interview data.

4 Mar. 2014
Tuesday
11am  
Fuller Labs, 320   Dong Wang, Univ. of Illinois at Urbana-Champaign -
7 Mar. 2014
Friday
11am  
Fuller Labs, 320   Petco Bogdanov, Univ. of California, Santa Barbara -
14 Mar. 2014
Friday
11am  
- Semester Break No Colloquium
21 Mar. 2014
Friday
11am  
Fuller Labs, 320   - -
28 Mar. 2014
Friday
11am  
Fuller Labs, 320   Manuel Garber, UMass Medical School -
4 Apr. 2014
Friday
11am  
Fuller Labs, 320   CS Faculty MQP Pitches

MQP projects that CS faculty are interested in advising are being pitched.

11 Apr. 2014
Friday
11am  
Fuller Labs, 320   Jacob C. Lindeman

Jacob Lindeman was most recently the Chief Technology Officer of MarketPrizm, a company that delivers fully managed trading infrastructure solutions in Europe and Asia to help financial institutions accelerate their trading and operational performance.

He was Vice President of Capital Markets Trading Architecture at Fidelity Investments. Jacob led the trading venue marketplace co-location and low-latency architecture deployment of smart order routers, order management systems and dark liquidity matching engines into New York City area data centers.

Jacob was a key contributor on dot-com distributed web content and on-line trading transaction application software development, systems design deployment, multi-site product availability and application performance.

In a previous life, he was Associate Partner at Shepley Bulfinch Richardson and Abbott Architects (SBRA) and focused on the evolution of Computer Aided Design and Drafting (CADD) technology.

Electronic stock markets and the design and construction of algorithmic trading engines

Financial electronic markets have become increasingly time sensitive and complex to design and deploy. We will consider multiple aspects of the environment including the actors (customers, brokers, markets), the data (sources, rates, latencies), the technology (stacks, topology, instrumentation), and markets (orders, books, inventory, liquidity, fragmentation, algorithms) to develop a holistic view of design decisions in the problem space.

18 Apr. 2014
Friday
11am  
Fuller Labs, 320   Ilknur Icke TBD
22 Apr. 2014
Tuesday
11am  
Fuller Labs, 320   Dr. Jie Yang, Oakland University

Jie Yang received his Ph.D. degree in Computer Engineering from Stevens Institute of Technology in 2011. He is currently an assistant professor in the Department of Computer Science and Engineering at Oakland University. His research interests include cyber security and privacy, and mobile and pervasive computing, with an emphasis on network security, smartphone security and applications, security in cognitive radio and smart grid, location systems and vehicular applications. His research is supported by National Science Foundation (NSF) and Army Research Office (ARO). He is the recipient of the Best Paper Runner-up Award from IEEE Conference on Communications and Network Security (CNS) 2013 and the Best Paper Award from ACM MobiCom 2011. His research has received wide press coverage including MIT Technology Review, The Wall Street Journal, NPR, CNET News, and Yahoo News.

Making Physical Inferences to Enhance Wireless Security

The ubiquity of wireless is redefining security challenges as the increasingly pervasive wireless networks make it easier to conduct attacks for new and rapidly evolving adversaries. There is an urgent need to seek security solutions that can be built into any wireless network stack to defend against attacks across the current heterogeneous mix of wireless technologies, which do not require extensive customization on wireless devices and cannot be undermined easily even when nodes are compromised. In particular, security solutions that are generic across all wireless technologies and can complement conventional security methods must be devised. My research efforts are centered around exploiting physical properties correlated with pervasive wireless environments to enhance wireless security and make inferences for context-aware applications. In this talk, I will present my research work in exploiting spatial correlation as a unique physical property inherited from any wireless device to address identity-based attacks including both spoofing and Sybil. These attacks are especially harmful as the claimed identity of a wireless device is often considered as an important first step in an adversary's attempt to launch a variety of attacks in different network layers. Our proposed techniques address several challenges include 1) detecting identity-based attacks in challenging mobile environments, (2) determining the number of attackers, and (3) localizing multiple adversaries. I will also present our work in secret key generation for facilitating secure data communication in the increasing dynamic wireless environments. Our work addressed the problem of collaborative secret key extraction for a group of wireless devices without relying on a key distribution infrastructure. Moreover, in order to provide efficient secret key generation, we exploit fine-grained physical layer information, such as the channel state information made available from OFDM system, to improve the secret key generation rate and make the secret key extraction approach more practical.

2 May 2014
Friday
11am  
Fuller Labs, 320   - -


Computer Science Department,
Worcester Polytechnic Institute,
100 Institute Road, Worcester, MA 01609-2280, USA.
(508) 831-5357

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