Ph.D.
Department of Computer Science and Engineering
University of Minnesota
5-208, EE/CS Building
200 Union St SE
Minneapolis, MN 55455
Ph. 612-624-8372
arashid at cs.umn.edu
Hi, this is Al Mamunur Rashid. You can call me Mamun.
I am a graduate student in the Department of
Computer Science & Engineering,
University of Minnesota, Twin Cities. I'm also a member
of the great research group,
GroupLens
Research.
Prior to coming to UofM, I earned my B.Sc. in Computer Science & Engineering from
Bangladesh University of Engineering & Technology (BUET), Dhaka, Bangladesh.
Research & Interest
My current primary interest is in applying various Machine Learning and Data Mining
techniques into novel applications and problems, particularly
into Human Computer Interactions, so that applications as
well as the associated interfaces can behave and respond
intelligently. Novel applications of Statistical Decision
Theory and Information Theory are of interest as well.
Currently I research mostly on aspects of recommender systems.
Recommender systems are effective mechanisms
for reducing today's overwhelming information-overload to a manageable state.
Recommender systems sift through the vast information space and
present the user with the information of interest. Movielens,
a live movie recommender system, which has well over 100,000
users and more than 12 million ratings, enable me and my colleagues
to research on an amazingly wide range of areas: from Social Science
and CSCW research to algorithm design and Data Mining research.
Publications
- Al Mamunur Rashid. Mining Influence in Recommender Systems. Ph.D. Dissertation, University of Minnesota, Feb. 2007.
- Al Mamunur Rashid, Shyong K. Lam, Adam LaPitz, George Karypis, and John Riedl. Towards a Scalable k NN CF Algorithm: Exploring Effective Applications of Clustering. LNAI vol 4811/2007: Advances in Web Mining and Web Usage Analysis, pages 147-166, Springer.
- Al Mamunur Rashid, George Karypis, and John Riedl. Influence in Ratings-Based Recommender Systems: An Algorithm-Independent Approach. SIAM International Conference on Data Mining, 2005.
- Al Mamunur Rashid, Shyong K. Lam, George Karypis, and John Riedl. ClustKNN: A Highly Scalable Hybrid Model- & Memory-Based CF Algorithm. To appear in WEBKDD 2006, Web Mining and Web Usage Analysis, August 20, 2006, Philadelphia, Pennsylvania, USA.
- Al Mamunur Rashid, Kimberly Ling, Regina D Tassone, Paul Resnick, Robert Kraut, and John Riedl. Motivating Participation by Displaying the Value of Contribution . To appear in ACM Conference on Human-Computer Interactions, CHI, 2006.
- Shilad Sen, Shyong K. Lam, Al Mamunur Rashid, Dan Cosley, Dan Frankowski, Jeremy Osterhouse, Franklin Harper and John Riedl. tagging, communities, vocabulary, evolution. To appear on the Proceedings of the ACM 2006 Conference on CSCW.
- Joseph F. McCarthy, David W. McDonald, Suzanne Soroczak, David H. Nguyen and Al M. Rashid Augmenting the Social Space of an Academic Conference. ACM 2004 Conference on Computer Supported Cooperative Work (CSCW 2004), 6-10 November 2004.
- Joseph F. McCarthy, David H. Nguyen, Al Mamunur Rashid, and Suzanne Soroczak. Proactive Displays & The Experience UbiComp Project. Position paper UbiComp 2003 Conference Workshop: First International Workshop on Ubiquitous Systems for Supporting Social Interaction and Face-to-Face Communication in Public Spaces.
- Rashid, A. M., Albert, I., Cosley, D., Lam, S. K., McNee, S., Konstan, J. A., & Riedl, J. (2002). Getting to Know You: Learning New User Preferences in Recommender Systems. In Proceedings of the 2002 International Conference on Intelligent User Interfaces, San Francisco, CA, pp. 127-134.
- McNee, S., Albert, I., Cosley, D., Gopalkrishnan, P., Lam, S.K., Rashid, A.M., Konstan, J.A., & Riedl, J. (2002). On the Recommending of Citations for Research Papers. In Proceedings of ACM 2002 Conference on Computer Supported Cooperative Work (CSCW2002), New Orleans, LA, pp. 116-125.
- Rashid, A. M., Ali, M. M. (1997). On-Line Handwritten Character Recognition Using 1-Dim, 1-Dim DP Approach. In Proceedings of National Conference on Computer & Information Systems, Bangladesh. ISBN: 984-31-0083-2.