Artificial Intelligence

The Artificial Intelligence Group at UCSD engages in a wide range of theoretical and experimental research. Areas of particular strength include machine learning, probabilistic inference, neural computation, and cognitive modeling. Within these areas, students and faculty also pursue real-world applications to problems in computer vision, speech and audio processing, information retrieval, bioinformatics, brain-computer interfaces, and computer systems and networking. The Artificial Intelligence Group is part of a larger campus-wide effort in Computational Statistics and Machine Learning (COSMAL). Interdisciplinary collaborations are strongly supported and encouraged.

People

Core Faculty (CSE)

• Serge Belongie
• Kamalika Chaudhuri
• Gary Cottrell
• Sanjoy Dasgupta
• Charles Elkan
• Yoav Freund
• David Kriegman
• Lawrence Saul

Affiliated Faculty

• Virginia De Sa (CogSci)
• Gert Lanckriet (ECE)
• Roger Levy (Linguistics)
• Javier Movellan (INC)
• Alon Orlitsky (ECE)
• Nuno Vasconcelos (ECE)

Ph.D. Students

• Neil Alldrin
• Boris Babenko
• Luke Barrington (ECE)
• William Beaver
• Nicholas Butko
• Manmohan Chandraker
• Jie Cheng
• Youngmin Cho
• Emanuele Coviello (ECE)
• Sunhyoung Han (ECE)
• Evan Ettinger
• Arturo Flores
• Carolina Galleguillos
• Diane Hu
• Mayank Kabra (ECE)
• Christopher Kanan
• Samory Kpotufe
• Omer Lang (ECE)
• Ben Laxton
• Sebastian Magda
• Brian McFee
• Yonghahk Albert Park
• Satya Mallick
• Paul Ruvolo
• Honghao Shan
• Bharath Sriperumbudur (ECE)
• Matus Telgarsky
• Matthew Tong
• Nakul Verma
• Kai Wang
• Vijay Mahadevan (ECE)
• Hamed Masnadi-Shirazi (ECE)
• Nikhil Rasiwasia (ECE)
• Jacob Whitehill
• Tingfan Wu
• Wensong Xu

Postdocs

• Laurens Van Der Maaten

Recent alumni

• Daniel Hsu (Ph.D. 2010) → University of Pennsylvania
• Justin Ma (Ph.D. 2010) → UC Berkeley
• Lawrence Cayton (Ph.D. 2009) → Max Planck Institute
• Vincent Rabaud (Ph.D. 2009) → VideoSurf
• Antoni Chan (Ph.D. 2008) → City University of Hong Kong
• Dashan Gao (Ph.D. 2008) → General Electric Global Research
• Neel Joshi (Ph.D. 2008) → Microsoft Research
• Andrew Rabinovich (Ph.D. 2008) → Google
• Douglas Turnbull (Ph.D. 2008) → Swarthmore College
• Kristin Branson (Ph.D. 2007) → Caltech
• Piotr Dollár (Ph.D. 2007) → Caltech
• Sameer Agarwal (Ph.D. 2007) → University of Washington
• Eric Wiewiora (Ph.D. 2007) → University of Alberta
• Lingyun Zhang (Ph.D. 2007) → ID Analytics
• Janet Hsiao (postdoc 2006-2008) → University of Hong Kong
• Tim Marks (postdoc 2006-2008) → MERL
• Claire Monteleoni (postdoc 2006-2008) → CCLS, Columbia University
• Sanmay Das (postdoc 2006-2007) → Rensselaer Polytechnic Institute

Recent News

• Google Fellowship Awarded

  (07/27/10) Congratulations to Ph.D. student Boris Babenko, who has won a Google Fellowship for his work in computer vision. Boris was one of fifteen students in North America selected by Google for this award.

• 2010 IBM Faculty Award

  (06/18/10) ECE professor Gert Lanckriet is the recipient of a 2010 IBM Faculty Award. This is a worldwide award that distinguishes faculty who have made outstanding contributions to their field. The award recognizes Prof. Lanckriet's contributions to machine learning and music understanding.

• Welcome Kamalika Chaudhuri

  (05/28/10) Kamalika Chaudhuri will join the CSE department as an assistant professor in the fall of 2010. Kamalika's research interests include clustering, online learning, and privacy-preserving models of classification.

• Congratulations to Ph.D. Student Dr. Daniel Hsu

  (05/27/10) Congratulations to Ph.D. student Dr. Daniel Hsu, who successfully defended his dissertation "Algorithms for Active Learning". Daniel will be moving cross-country to do a joint postdoc at UPenn and Rutgers.

• Qualcomm Innovation Fellowship Awarded

  (05/13/10) Luke Barrington (ECE) and Brian McFee have been awarded a Qualcomm Innovation Fellowship for work on music information retrieval. They are advised by Professor Gert Lanckriet in ECE. The goal of their project is to provide personalized, mobile music search and discovery through advances in machine learning and signal processing.

• Congratulations to Ph.D. Student Dr. Justin Ma

  (03/21/10) Congratulations to Ph.D. student Dr. Justin Ma, who successfully defended his dissertation "Learning to Detect Malicious URLs". The thesis describes work at the intersection of machine learning and computer security. Justin is now on the whirlwind talk circuit, but will shortly be joining UC Berkeley as a postdoc.

[News Archive]

Recent Publications

Cost-Sensitive Boosting, H. Masnadi-Shirazi, and N. Vasconcelos, Pattern Analysis and Machine Intelligence, IEEE Transactions on, March, Volume 33, Number 2, p.294 -309, (2011). PDF

• BibTex

Exploiting Feature Covariance in High-Dimensional Online Learning, Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul, and Fernando Pereira, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AI-STATS), May, Sardinia, Italy, (2010). PDF

• BibTex

covariance-aistats2010.pdf

Spatiotemporal Saliency in Dynamic Scenes, V. Mahadevan, and N. Vasconcelos, Pattern Analysis and Machine Intelligence, IEEE Transactions on, January, Volume 32, Number 1, p.171 -177, (2010). PDF

• BibTex

Modeling Music as a Dynamic Texture, L. Barrington, A. B. Chan, and G. Lanckriet, Audio, Speech, and Language Processing, IEEE Transactions on, March, Volume 18, Number 3, p.602 -612, (2010). PDF

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Sparse signal recovery in the presence of correlated multiple measurement vectors, Zhilin Zhang, and B. D. Rao, Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on, March, p.3986 -3989, (2010). PDF

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Context based object categorization: A critical survey, Carolina Galleguillos, and Serge Belongie, Computer Vision and Image Understanding, March, Volume 114, Number 6, p.712 - 722, (2010). [Special Issue on Multi-Camera and Multi-Modal Sensor Fusion] URL PDF

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Hilbert Space Embeddings and Metrics on Probability Measures, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, and Gert R. G. Lanckriet, J. Mach. Learn. Res., August, Volume 11, p.1517–1561, (2010). URL PDF

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Learning gene regulatory networks from only positive and unlabeled data, Luigi Cerulo, Charles Elkan, and Michele Ceccarelli, BMC Bioinformatics, May, Volume 11, Number 1, p.228, (2010). URL PDF

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On the relation between universality, characteristic kernels and RKHS embedding of measures, Bharath Sriperumbudur, Kenji Fukumizu, and Gert Lanckriet, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AI-STATS), May, Volume 9, (2010). Sardinia, Italy. PDF

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Convex Optimizations for Distance Metric Learning and Pattern Classification [Applications Corner], K. Q. Weinberger, Fei Sha, and L. K. Saul, Signal Processing Magazine, IEEE, May, Volume 27, Number 3, p.146 -158, (2010). PDF

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Non-parametric estimation of integral probability metrics, B. K. Sriperumbudur, K. Fukumizu, A. Gretton, B. Scholkopf, and G. Lanckriet, Information Theory Proceedings (ISIT), 2010 IEEE International Symposium on, June, p.1428 -1432, (2010). PDF

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Facial expression recognition using Gabor motion energy filters, Tingfan Wu, M. S. Bartlett, and J. R. Movellan, Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on, June, p.42 -47, (2010). PDF

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Toward real-time grocery detection for the visually impaired, T. Winlock, E. Christiansen, and S. Belongie, Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on, June, p.49 -56, (2010). PDF

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On the design of robust classifiers for computer vision, H. Masnadi-Shirazi, V. Mahadevan, and N. Vasconcelos, Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, June, p.779 -786, (2010). PDF

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Anomaly detection in crowded scenes, V. Mahadevan, Weixin Li, V. Bhalodia, and N. Vasconcelos, Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, June, p.1975 -1981, (2010). PDF

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[Publications Archive]

Affiliations

	CalIT2	Computational Statistics and Machine Learning Group
	Computer Audition Lab	Computer Vision Laboratory
	Institute for Neural Computation	Machine Perception Lab
	Statistical Visual Computing Lab	Temporal Dynamics of Learning Center