Curriculum Vitae:
Kevin R. Canini
1. Personal Information
Full name: Kevin Robert Canini
Place of birth: Palm Beach Gardens, Florida, USA
Nationality: Citizen of the United States of America
Mailing address: 2435
Grant St. Apt. 8
Berkeley, CA 94703-1951
Telephone: +1 (510) 299-3291 (mobile)
E-mail: <firstname>@cs.berkeley.edu
Website: http://www.cs.berkeley.edu/~kevin/
2. Education
Ph.D. in Computer Science, University of California, Berkeley, pursuing
M.A. in Statistics, University of California, Berkeley, pursuing
M.S. in Computer Science, University of California, Berkeley, 2007
B.S. in Computer Science, Cornell University, 2006
3. Awards and Honors
2008 Honorable mention for National Science Foundation Graduate Research Fellowship Program. Of 8582 applicants, 913 received the award and 1640 received an honorable mention.
2006 Cornell University Computer Science Prize for Academic Excellence and Leadership. “Awarded annually to an outstanding senior who has excelled academically, demonstrating a strong commitment to the educational ideals of the University and the Department of Computer Science.”
2005 Field Honors in Computer Science, Cornell University. Awarded for graduating with a GPA above 3.50 and completing 8 credit-hours of graduate-level courses and 6 credit-hours of independent research with a faculty member.
2005 Summa cum laude distinction, Cornell University. Awarded to all graduating engineering students with a GPA above 4.0 (based on all credits taken at Cornell).
2005 Dean’s List, College of Engineering, Cornell University. Received for every semester attended, Fall 2002 through Fall 2005. Awarded for a semester-GPA above 3.40.
4. Publications
Conference papers
1. Kevin R. Canini, Lei Shi, and Thomas L. Griffiths (2009). “Online inference of topics with latent Dirichlet allocation”. Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS).
2. Thomas L. Griffiths, Kevin R. Canini, Adam N. Sanborn, and Daniel J. Navarro (2007). “Unifying rational models of categorization via the hierarchical Dirichlet process”. Proceedings of the 29th Annual Conference of the Cognitive Science Society.
Theses
3. Kevin R. Canini (2007). “Modeling categorization
as a Dirichlet process mixture”. Technical Report UCB/EECS-2007-69, EECS
Department, University of California, Berkeley.
Book chapters
4. Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, and Daniel J. Navarro (2007). “Categorization as nonparametric Bayesian density estimation”. In Mike Oaksford and Nick Chater (Eds.). The probabilistic mind: Prospects for rational models of cognition, Oxford: Oxford University Press.
Technical reports and other non-peer-reviewed papers
5. Peter Bodík, Michael P. Armbrust, Kevin R. Canini, Armando Fox, Michael I. Jordan, and David I. Patterson (2008). “A case for adaptive datacenters to conserve energy and improve reliability”. Technical Report UCB/EECS-2008-127, EECS Department, University of California, Berkeley.
6. Jacob Abernethy, Kevin R. Canini, John C. Langford, and Aleksandr Simma (2007). “Online collaborative filtering”.
5. Presentations
Invited talks
1. Kevin R. Canini (2009). “Online inference for topic models”. Augmented Social Cognition Research Group, Intelligent Systems Lab, Palo Alto Research Center (PARC). Palo Alto, CA, USA.
Conference posters
2. Kevin R. Canini and Thomas L. Griffiths (2009). Workshop on Nonparametric Bayes, Neural Information Processing Systems (NIPS) conference. Whistler, BC, Canada.
3. Kevin R. Canini, Lei Shi, and Thomas L. Griffiths (2009). “Online inference of topics with latent Dirichlet allocation”. 12th International Conference on Artificial Intelligence and Statistics (AISTATS). Clearwater Beach, FL, USA.
4. Kevin R. Canini and Thomas L. Griffiths (2008). “The hierarchical Dirichlet process as a model of human category learning”. Workshop on Machine Learning Meets Human Learning, Neural Information Processing Systems (NIPS) conference. Whistler, BC, Canada.
6. Teaching
2009 Psychology 128/290Q: Probabilistic models of cognition, spring (guest lecturer).
2008 Cognitive Science C131/Psychology C123: Computational models of cognition, fall (guest lecturer).
2005 Computer Science 280: Discrete Structures and Mathematics, fall (teaching assistant).
Computer Science 481: Honors Introduction to Theory of Computing, fall (teaching assistant).
Computer Science 211: Computers and Programming, spring (teaching assistant).
Computer Science 280: Discrete Structures and Mathematics, spring (teaching assistant).
2004 Computer Science 211: Computers and Programming, fall (teaching assistant).
Computer Science 280: Discrete Structures and Mathematics, fall (teaching assistant).
Computer Science 211: Computers and Programming, summer (teaching assistant).
Computer Science 211: Computers and Programming, spring (teaching assistant).
Computer Science 280: Discrete Structures and Mathematics, spring (teaching assistant).
2003 Computer Science 211: Computers and Programming, fall (teaching assistant).
Computer Science 280: Discrete Structures and Mathematics, fall (teaching assistant).
7. Reviewing
2009 Reviewed 2 papers for the 31st Annual Conference of the Cognitive Science Society.
8. Departmental service
2008 Social Committee officer, Computer Science Graduate Student Association (spring semester).
2007 Social Committee officer, Computer Science Graduate Student Association (fall semester).