Alan Fern

Associate Professor
Computer Science

2004    Ph.D., Computer Engineering
Purdue University

2000    M.S., Computer Engineering
Purdue University   

1997    B.S., Electrical Engineering
University of Maine


Alan Fern is an Associate Professor of Computer Science at Oregon State University. He received his Ph.D (2004) and M.S (2000) in Computer Engineering from Purdue University, and his B.S (1997) in Electrical Engineering from the University of Maine. He received a National Science Foundation CAREER award in 2006, is an associate editor of the Machine Learning Journal, and currently serves on the editorial boards of the Journal of Artificial Intelligence Research and the Artificial Intelligence Journal. His research interests span a range of topics in artificial intelligence, including machine learning and automated planning/control.

Research Interests: 

Research Areas
Artificial intelligence, machine learning, automated planning and control, computer vision

Research Description
My research is centered around my interest in making machines “smarter.” Machines are very far from rivaling humans in tasks such as visual understanding, planning a trip, playing real-time strategy games, language processing, tutoring, etc. Nevertheless, I believe that even small steps toward solving such tasks will yield systems that people will soon take for granted and depend on in everyday life. My general career vision is to support this progress by studying the critical computational problems that arise.

My research interests are in the artificial intelligence areas of machine learning, automated planning, and knowledge representation. I am most interested in usefully integrating these complementary areas.

One of my research thrust is to develop algorithms that can learn to interpret complex data such as videos. As an example, in the Digital Scout Project, we are studying the use of machine learning for computing interpretations of American football video. Such interpretations will allow for coaches, analysts, and fans to easily pose queries against libraries of football video for indexing and collecting statistics.

A second research thrust is to develop techniques for integrating planning and machine learning. Our work has developed new planning algorithms that can learn to solve very large problems that were beyond the scope of previous techniques. We are now extending that work to richer settings, for example, multi-agent planning, where agents must cooperate to complete a task. As a testbed we are studying planning and learning in the context of real-time strategy games, a domain where humans are currently far better than computer players.

Joshi, S., R. Khardon, P. Tadepalli, A. Raghavan, and A. Fern, "Solving Relational MDPs with Exogenous Events and Additive Rewards", European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD-2013), vol. 8188, Prague, Czech Republic, Springer Berlin Heidelberg, pp. 178 - 193, 09/2013. Abstract
Senator, T. E., H. G. Goldberg, A. Memory, W. T. Young, B. Rees, R. Pierce, D. Huang, M. Reardon, D. A. Bader, E. Chow, et al., "Detecting insider threats in a real corporate database of computer usage activity", Proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining - KDD '13, Chicago, Illinois, ACM Press, pp. 1393, 08/2013. Abstract
Groce, A., A. Fern, M. Erwig, J. Pinto, T. Bauer, and A. Alipour, "Learning-Based Test Programming for Programmers", Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change, vol. 7609: Springer Berlin Heidelberg, pp. 572-586, 2012. Abstract
Wilson, A., A. Fern, and P. Tadepalli, "Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach", Journal of Machine Learning Research - Proceedings Track, vol. 27, pp. 217-227, 2012.
Zhu, P., J. Pinto, T. Nguyen, and A. Fern, "Achieving Quality of Service with Adaptation-based Programming for medium access protocols", IEEE Global Communications Conference (GLOBECOM), Anaheim, CA, IEEE, pp. 1932 - 1937, 12/2012. Abstract
Wilson, A., A. Fern, and P. Tadepalli, "A Bayesian Approach for Policy Learning from Trajectory Preference Queries", Advances in Neural Information Processing Systems (NIPS-2011) , Lake Tahoe, Nevada, pp. 1142–1150, 12/2012. Abstract
Groce, A., A. Fern, J. Pinto, T. Bauer, A. Alipour, M. Erwig, and C. Lopez, "Lightweight Automated Testing with Adaptation-Based Programming", IEEE 23rd International Symposium on Software Reliability Engineering (ISSRE), Dallas, TX, IEEE, pp. 161 - 170, 11/2012. Abstract
Bauer, T., M. Erwig, A. Fern, and J. Pinto, "Faster program adaptation through reward attribution inference", Proceedings of the 11th International Conference on Generative Programming and Component Engineering - GPCE '12, Dresden, Germany, ACM Press, pp. 103-111 , 09/2012. Abstract
Judah, K., A. Fern, and T. G. Dietterich, "Active Imitation Learning via Reduction to I.I.D. Active Learning", Uncertainty in Arti cial Intelligence: Proceedings of the Twenty-Eighth Conference (2012), Catalina Island, CA , pp. 428-437, 08/2012. Abstract
Hostetler, J., E. W. Dereszynski, T. G. Dietterich, and A. Fern, "Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games", Uncertainty in Arti cial Intelligence: Proceedings of the Twenty-Eighth Conference (2012), Catalina Island, CA, pp. 367-376, 08/2012. Abstract
Natarajan, S., P. Tadepalli, and A. Fern, "A relational hierarchical model for decision-theoretic assistance", Knowledge and Information Systems, vol. 32, no. 2: Springer-Verlag, pp. 329-349, 08/2012. Abstract
Azimi, J., A. Fern, X. Z. Fern, G. Borradaile, and B. Heeringa, "Batch Active Learning via Coordinated Matching", International Conference on Machine Learning (ICML), Edinburgh, Scotland, 07/2012. Abstract
Raghavan, A., S. Joshi, A. Fern, P. Tadepalli, and R. Khardon, "Planning in Factored Action Spaces with Symbolic Dynamic Programming", Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012), Toronto, Ontario, Canada, 07/2012. Abstract
Xue, S., A. Fern, and D. Sheldon, "Scheduling Conservation Designs via Network Cascade Optimization", Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012), Toronto, Ontario, Canada, 07/2012. Abstract
Doppa, J. R., A. Fern, and P. Tadepalli, "Output Space Search for Structured Prediction", 29th International Conference on Machine Learning (ICML 2012), Edinburgh, Scotland, 06/2012. Abstract
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Fern, A., "Speedup Learning", Encyclopedia of Machine Learning, New York, NY, Springer-Verlag, 2011.
Mehta, N., P. Tadepalli, and A. Fern, "Autonomous Learning of Action Models for Planning", Advances in Neural Information Processing Systems (NIPS-2011), Granada, Spain, pp. 2465-2473, 12/2011. Abstract
Azimi, J., A. Fern, and X. Z. Fern, "Budgeted Optimization with Concurrent Stochastic-Duration Experiments", Advances in Neural Information Processing Systems 24, Granada, Spain, pp. 1098–1106, 12/2011. Abstract
Zhu, P., J. Pinto, A. Fern, and T. Nguyen, "Adaptation-based programming for network protocol design: An 802.11x case study (abstract)", IEEE International Performance Computing and Communications Conference (IPCCC-2011), Orlando, FL, IEEE, pp. 1 - 2, 11/2011. Abstract
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