Junior Seminar Poster Session

Posted by admin on April 21, 2014
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The Department of Computer Science will be hosting a poster session on Thursday, April 24 from 11:00 AM to 12:15 PM in Alden Hall. The students in CMPSC 580, Junior Seminar: Topics and Research Methods in Computer Science, will be presenting posters for their proposed research topics and will be available to answer questions. Please join us in the Alden Hall lobby for refreshments and exciting research ideas.

Second Faculty Candidate Research Presentation

Posted by David Wagner on March 29, 2013
Guest Lectures, News, Research / Comments Off

The second candidate for the position of Assistant Professor of Computer Science, Mohammad Irfan, will be on campus on Monday, April 1. All are invited to attend a research presentation in Alden Hall, Room 101 at 4:00 PM.

Monday, April 1, 2013
Alden Hall, Room 101
4:00 PM

Mohammad T. Irfan <>

Computational Problems in Social Sciences:  Using Game Theory to Connect the Dots

Who are the most influential senators in Congress? Is there a small coalition of senators who are influential enough to prevent filibusters? Moving from Congress to a different setting, can we model microfinance markets to help policy-makers take critical decisions, such as setting a cap on interest rates or subsidizing microfinance banks?

The above questions may seem to be unrelated at first, but as I will show, these can indeed be knit together by the same needle of game theory. A common element in these questions is that many agents strategically interact with each other within a network-structured complex system in order to make their decisions. I will exploit this game-theoretic element to connect the dot of artificial intelligence with the dots of sociology and microfinance economies. I will end my talk by outlining an array of exciting interdisciplinary research avenues, many of which can be explored in senior projects or theses.

Mohammad T. Irfan is a PhD Candidate in the Department of Computer Science at Stony Brook University. He is advised by Professor Luis E. Ortiz. His interests lie in the interdisciplinary areas that combine artificial intelligence with sociology (e.g., influence in social networks), economics (e.g., microfinance markets), and arts (e.g., computer-aided authentication of Jackson Pollock’s drip paintings). His research has been published at the AAAI Conference on AI, ACM Symposium on Computational Geometry, Discrete & Computational Geometry Journal, and SPIE Electronic Imaging. His research on influence among the senators has also been reported in Science News. One of Mohammad’s career goals is to integrate his interdisciplinary interests into teaching, curriculum development, and collaborative research.

Assistant Professor Candidate Research Presentation

Posted by admin on March 26, 2013
Guest Lectures, News, Research / Comments Off

Janyl Jumadinova, a candidate for the position of Assistant Professor of Computer Science will be on campus on Thursday, March 28.  All are invited to attend a research presentation in Alden Hall, Room 101 at 4:00 PM.

Thursday, March 28, 2013
Alden Hall, Room 101
4:00 PM

Janyl Jumadinova <>

FORETELL: Aggregating Distributed, Heterogeneous Information from Diverse Sources Using Market-based Techniques


Predicting the outcome of uncertain events that will happen in the future is a frequently indulged task by humans while making critical decisions. The process underlying this prediction and decision making is called information aggregation, which deals with collating the opinions of different people, over time, about the future event’s possible outcome. The information aggregation problem is non-trivial as the information related to future events is distributed spatially and temporally, the information gets changed dynamically as related events happen, and, finally, people’s opinions about events’ outcomes depends on the information they have access to and the mechanism they use to form opinions from that information. This talk will discuss how we address the problem of distributed information aggregation by building computational models and algorithms for different aspects of information aggregation so that the most likely outcome of future events can be predicted with utmost accuracy. We have employed a commonly-used market-based framework called a prediction market to formally analyze the process of information aggregation. The behavior of humans performing information aggregation within a prediction market is implemented using software agents which employ sophisticated algorithms to perform complex calculations on behalf of the humans, to aggregate information efficiently. We have considered different yet crucial problems related to information aggregation and have verified our proposed techniques through analytical results and experiments while using commercially available data from real prediction markets within a simulated, multi-agent based prediction market.

RICCS presentation by Phil McMinn

Posted by David Wagner on October 24, 2012
ACM, Guest Lectures, News, Research / Comments Off

You are cordially invited to attend the upcoming session of the Research in Computer Science Seminar (RICSS), jointly sponsored by the Allegheny College Student Chapter of the ACM.

Please pass this invitation on to other students, staff, and faculty members who would be interested in attending the upcoming talk.  Since the session is at lunch time, all attendees are encouraged to bring their lunch to the presentation.

Light refreshments will be provided!

Wednesday, October 31, 2012
Campus Center Rooms 301 and 302
12:00 noon – 1:00 pm


Phil McMinn, University of Sheffield <>


Search-based Software Testing: Automating Software Testing Using Heuristic Algorithms


Software testing is a demanding, laborious and expensive process that involves tasks that are difficult to automate. This talk introduces search-based testing, a technique which reformulates testing problems as fitness functions, so that classical optimization techniques such as Genetic Algorithms may be used to address them. Instead of exhaustively enumerating the set of possible solutions to a problem or attempting to solve a limited version of it perfectly, search-based approaches instead seek to evolve solutions that are ‘fit for purpose’ — as dictated by the fitness function.

Presenter Biography:

Phil McMinn is a Senior Lecturer in Computer Science at the University of Sheffield, UK, where he has been a faculty member since October 2006. He was awarded his PhD from Sheffield in January 2005, which was funded by DaimlerChrysler Research and Technology.  McMinn’s research interests cover software testing in general, program transformation, and agent-based systems and modelling.  He has published many papers in the field of search-based testing, including a survey paper that, according to Google Scholar, has been cited nearly 600 times.

All are welcome to attend!

More details about RICSS are available at:

Recent Publications

Posted by David Wagner on July 07, 2010
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Alexander P. Conrad, Robert S. Roos, and Gregory M. Kapfhammer.  Empirically Studying the Role of Selection Operators During Search-Based Test Suite Prioritization. In the Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference, Portland, Oregon, July 2010.

Zachary Williams and Gregory M. Kapfhammer.  Using Synthetic Test Suites to Empirically Compare Search-Based and Greedy Prioritizers. In the Proceedings of the Late Breaking Abstracts Workshop at the ACM SIGEVO Genetic and Evolutionary Computation Conference, Portland, Oregon, July 2010.

James Kukunas, Robert D. Cupper, and Gregory M. Kapfhammer.  A Genetic Algorithm to Improve Linux Kernel Performance on Resource-Constrained Devices. In the Proceedings of theLate Breaking Abstracts Workshop at the ACM SIGEVO Genetic and Evolutionary Computation Conference, Portland, Oregon, July 2010.