Junfeng Wen 闻俊锋

Athabasca Hall 111
Department of Computing Science
University of Alberta
Edmonton, Alberta
Canada, T6G 2E8
Email: junfeng D-O-T wen A~T ualberta D-O-T ca
Curriculum Vitae


I am a Ph.D. candidate working with Prof. Russ Greiner and Prof. Dale Shuurmans in Amii. My primary research interests are Transfer Learning (especially Covariate Shift) and Representation Learning. Currently, I'm working as an intern in Borealis AI.

Education

Sep.2013 - Present Department of Computing Science, University of Alberta, Doctor of Philosophy
Sep.2011 - Jun.2013 Department of Computing Science, University of Alberta, Master of Science
Sep.2007 - Jun.2011 College of Computer Science and Technology, Chu Kochen Honors College, Zhejiang University, Bachelor of Engineering (with Honor)

Publications

C. Ma, J. Wen and Y. Bengio. Universal Successor Representations for Transfer Reinforcement Learning. In Sixth International Conference on Learning Representations (ICLR) Workshop, 2018. [pdf]
V. Ganapathiraman, X. Zhang, Y. Yu and J. Wen. Convex Two-Layer Modeling with Latent Structure. In Twenty-Ninth Neural Information Processing Systems (NIPS), 2016. [pdf]
J. Wen, N. Hassanpour and R. Greiner. Weighted Gaussian Process for Estimating Treatment Effect. In NIPS Workshop on Inference and Learning of Hypothetical and Counterfactual Interventions in Complex Systems, 2016.
J. Wen, R. Greiner and D. Schuurmans. Correcting Covariate Shift with the Frank-Wolfe Algorithm. In Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2015. [pdf] [code]
M. White, J. Wen, M. Bowling and D. Schuurmans. Optimal Estimation of Multivariate ARMA Models. In Twenty-Ninth Annual Conference on Artificial Intelligence (AAAI), 2015. Also invited to ICRA 2015. [pdf] [code]
J. Wen, C. Yu and R. Greiner. Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification. In International Conference of Machine Learning (ICML), 2014. [pdf] [code]

Teaching Experience

2016 Fall TA of CMPUT 466/551 Machine Learning, University of Alberta
2015 Fall Instructor of CMPUT 274 Introduction to Tangible Computing, University of Alberta
2012 Fall Head TA of CMPUT 101 Introduction to Computing, University of Alberta
2011 Winter Primary TA of CMPUT 101 Introduction to Computing, University of Alberta
2011 Fall Secondary TA of CMPUT 101 Introduction to Computing, University of Alberta

Selected Awards

2016 Alberta Innovates-Technology Futures Graduate Student Scholarship, AB, Canada
2015 Departmental Ph.D. Early Achievement Award Runner-up, Univ. of Alberta
2013 Univ. of Alberta Doctoral Recruitment Scholarship
2011 Univ. of Alberta Master's Scholarship (About Sixteen in Univ. of Alberta)

Professional Services

PC Member AAAI 2017, 2018; ACML 2018
Reviewer NIPS 2018; IJCAI 2016; JMLR

Relevant Courses

2013 Fall Statistical Inference (A+), University of Alberta, by Prof. Ivan Mizera. (Lecture notes. Let me know if you find any error or typo.)
2013 Fall Online Learning (A), University of Alberta, by Prof. Csaba Szepesvari and Dr. Andras Gyorgy.
2011 Winter Representation Learning (A+), University of Alberta, by Prof. Dale Shuurmans.
2011 Fall Machine Learning (A), University of Alberta, by Prof. Dale Shuurmans. (Lecture notes. Let me know if you find any errors or typos.)

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