Ed H. Chi  紀懷新  Curriculum Vitae

email: chi@acm.org

http://www.edchi.net/

To lead world-class research on novel problems in AI, machine learning, human-computer interaction, and social computing.

Research Interests

Deep Learning / Machine Learning, Recommender Systems, Human-Computer Interaction & Social Computing

Professional Experience

Google Research / Google Brain / Google DeepMind

Apr 2021 -- Present: Distinguished Scientist and Sr. Lead in Google Brain / Google DeepMind

Oct 2017 -- Apr 2021: Principal Scientist and Team Lead in Google Brain.

May 2015 -- Oct 2017: Senior Staff Research Scientist and Team Lead.

Feb 2011 -- May 2015: Staff Research Scientist and Tech Lead.

Xerox Palo Alto Research Center (PARC)

Apr 2007 -- Feb 2011: Area Manager and Principal Scientist, Augmented Social Cognition Area.

Mar 1999 -- Apr 2007: Research Scientist, User Interface Research Area

Jun 1998 -- Sep 1998, Summer Intern, User Interface Research Area.

Jun 1997 -- Dec 1997, Summer Intern and Consultant, User Interface Research Area.

University of Minnesota

Mar 1997 -- Jun 1997, Instructor. Dept. of Computer Science.

Sep 1994 -- Mar 1997, Jan 1998 -- Jun 1998, Sep 1998 -- Mar 1999, Research Assistant. Dept. of Computer Science.

Jun 1994 -- Sep 1994, Apprentice. Geometry Center.

Jan 1994 -- Jun 1994, Undergrad Research Assistant, Dept. of Computer Science.

Oct 1993 -- Jun 1994, Research Programmer. Dept. of Cell Biology and Neuroanatomy.

Sep 1993 -- Jun 1994, Computer Lab Consultant. Distributed Computing Services.

Jun 1993 -- July 1993, Teaching Assistant. Geometry Center.

Education

Ph.D., Computer and Information Science, Sep. 1996 - Mar. 1999, University of Minnesota.

M.S., Computer Science with Graduate Minor in Scientific Computation, Sep. 1994 - Dec. 1996, University of Minnesota

Bachelor of Computer Science with Minor in Mathematics, Sep. 1992 - June, 1994, University of Minnesota

Minneapolis South High School, Sep. 1988 - June, 1992

Selected/Highly-Cited Publications 

Recommendation Systems

Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi. Top-K Off-Policy Correction for a REINFORCE Recommender System. ACM International Conference on Web Search and Data Mining, (WSDM), 2019. [arxiv] [ACM]

Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow.  Fairness in Recommendation Ranking through Pairwise Comparisons. KDD 2019. [arxiv]

Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, Ed H. Chi. Latent Cross: Making Use of Context in Recurrent Recommender Systems. WSDM 2018.

Alex Beutel, Ed H. Chi, Zhiyuan Cheng, Hubert Pham, John Anderson. Beyond Globally Optimal: Focused Learning for Improved Recommendations. WWW, 2017. [Google]

Jilin Chen, Rowan Nairn, Les Nelson, Michael Bernstein, Ed H. Chi. Short and Tweet: Experiments on Recommending Content from Information Streams. In Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI2010). April, 2010. Atlanta, GA. [slides]

Jilin Chen, Rowan Nairn, Ed H. ChiSpeak Little and Well: Recommending Conversations in Online Social Streams. In Proc. of CHI2011. Vancouver, Canada. [UMN]

Machine Learning

Tim Kraska, Alex Beutel, Ed H. Chi, Jeff Dean, Neoklis Polyzotis. The Case for Learned Index Structures. Dec. 2017. https://arxiv.org/abs/1712.01208

Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, Quoc Le. (2022). LaMDA: Language Models for Dialog Applications. arXiv preprint arXiv:2201.08239.

Alex Beutel, Jilin Chen, Zhe Zhao, Ed H. Chi.  Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.  KDD FATML Workshop, 2017. 

Jiaqi Ma, Zhe Zhao,  Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi.  Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. In Proc. of KDD 2018. [pdf]

Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi. Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS, 2020. [Appendix and Code]

Human-Computer Interactions: Crowdsourcing, UbiComp, Web Analytics, and InfoVis

Aniket Kittur, Ed H. Chi, Bongwon Suh. Crowdsourcing User Studies With Mechanical Turk. In Proc. of the ACM Conference on Human-factors in Computing Systems (CHI2008), pp.453-456. ACM Press, 2008. Florence, Italy. (18% acceptance rate) UMN

Brynn Evans, Ed H. Chi. Towards a Model of Understanding Social Search. In Proc. of Computer-Supported Cooperative Work (CSCW), pp. 485-494. ACM Press, 2008. San Diego, CA. [ACM]

Lichan Hong, Gregorio. Convertino, and Ed H. Chi. Language Matters in Twitter: A Large Scale Study. In Proc. of 2011 International AAAI Conference on Weblogs and Social Media (ICWSM'11). [AAAI]

Ed H. Chi. Introducing Wearable Force Sensors in Martial Arts. IEEE Pervasive Computing, Vol. 4, No. 3, pp. 47--53. July, 2005. IEEE Press.

Jeffrey Heer, Ed H. Chi. Separating the Swarm: Categorization Methods for User Access Sessions on the Web. In Proc. of ACM CHI 2002 Conference on Human Factors in Computing Systems, pp. 243--250. ACM Press, April 2002. Minneapolis, MN. (15% acceptance rate) UMN

Christopher Olston, Ed H. Chi. ScentTrails: Integrating Browsing and Searching on the Web. ACM Transactions on Computer-Human Interaction, Vol. 10, Part 3, pp. 177--197. Sept, 2003. ACM Press.

Ed H. Chi, John Riedl, Phillip Barry, Joseph Konstan. Principles for Information Visualization Spreadsheets. IEEE Computer Graphics and Applications (Special Issue on Visualization), pp. 30--38. July/August, 1998. IEEE CS Press.

Awards / Honors 

Keynote Talks

Mentorship of Students/Interns (chronological)

Teaching

Major Technical Artifacts and Systems

Press

Patents (Issued: 39)