Hau Chan
Assistant Professor
Department of Computer Science and Engineering
University of Nebraska-Lincoln
Office: Avery 363
e-mail: hchan3 [at] unl.edu
Phone: 402-472-5091
(Short) Bio:
2018 - Current: Assistant Professor, University of Nebraska-Lincoln
2017 - 2018: Postdoctoral Fellow, Laboratory for Innovation Science at Harvard (Advisors: David Parkes and Karim Lakhani)
2017 May - August: Postdoctoral Fellow, USC Center for Artificial Intelligence in Society (Advisors: Milind Tambe and Eric Rice)
2015 - 2017: Postdoctoral Research Associate, Trinity University (Advisor: Albert Jiang)
2010 - 2015: Ph.D. Candidate in Computer Science, Stony Brook University (Advisor: Luis Ortiz)
2013 May - August: NSF EAPSI Fellow, Nanyang Technological University (Advisor: Edith Elkind)
2006 - 2010: B. S. Candidate in Computer Science and Mathematics, College of Charleston (Advisor: Dinesh Sarvate)
2009 May - August: NSF REU Student, Georgia Institute of Technology (Advisor: Plamen lliev)
2009 August: Summer Program Student in Analysis and Geometry, Princeton University
(Selected) Awards:
Distinguished PC Member, 27th International Joint Conference on Artificial Intelligence (IJCAI 2018)
Best Student Research Paper Award, Autonomous Agents and Multiagent Systems (AAMAS 2016)
Best Research Paper Award, 2015 SIAM International Conference on Data Mining (SDM 2015)
National Science Foundation Graduate Research Fellowship, 2012 - 2015
Funding Acknowledgement (Thanks!):
USCYBERCOM (through NSRI) 2018-2019
UNL Collaboration Initiative Planning Grant 2020-2021 and UNL Collaboration Initiative Seed Grant 2020-2022
Artificial Intelligence Journal (AIJ) and NSF (for supporting AAMAS DC and Student Scholarship) 2021
(Selected) Conference/Workshop Organizations:
Co-Chair, Doctoral Consortium, Autonomous Agents and Multiagent Systems (AAMAS 2021)
Co-Chair, Scholarship, Autonomous Agents and Multiagent Systems (AAMAS 2021)
Invited Speaker, 3rd Workshop on Data Science for Social Good (SoGood 2018), 2018 The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2018)
Teaching:
Spring 2016: CSCI-1311 Introduction to Programming Logic (at Trinity University)
Fall 2016: CSCI-1311 Introduction to Programming Logic (at Trinity University)
Fall 2018: CSCE 990 Networks, Crowds, and Markets
Spring 2019: CSCE 496/896 Computational Game Theory and Its Applications
Fall 2019: CSCE 310H Honors Data Structures and Algorithms
Spring 2020: CSCE 496/896 Computational Game Theory and Its Applications
Fall 2020: CSCE 310H Honors Data Structures and Algorithms
Spring 2021: CSCE 496/896 Computational Game Theory and Its Applications
Learning:
AAMAS 2019: Tutorial on Solving Games with Complex Strategy Spaces (with A. Jiang and F. Fang)
IJCAI 2019: Tutorial on Solving Games with Complex Strategy Spaces (with F. Fang)
AAMAS 2020: Tutorial on Computational Game Theory and Its Applications (with A. Sinha and M. Irfan)
IJCAI 2020: Tutorial on Computational Game Theory and Its Applications (with A. Sinha and M. Irfan)