Niao He
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Education
- Ph.D. in Operations Research, Georgia Institute of Technology, 2015
- M.S. in Computational Science and Engineering, Georgia Institute of Technology, 2015
- B.S. in Mathematics and Applied Mathematics, University of Science and Technology of China, 2010
Academic Positions
- Affiliate Assistant Professor, Department of Electrical and Computer Engineering, UIUC, August 2018-present
- Affiliate Assistant Professor, National Center for Supercomputing Applications, UIUC, June 2018-present
- Affiliate Assistant Professor, Coordinated Science Laboratory, UIUC, Feb 2016-present
- Assistant Professor, Department of Industrial and Enterprise Systems Engineering, UIUC, Jan 2015-present
Other Professional Employment
- Research Intern, Mitsubishi Electric Research Laboratories, Cambridge, Massachusetts, Summer 2013
- Research Intern, Microsoft Research Asia, Beijing, China, Summer 2009
Resident Instruction
- IE 598 Optimization Under Uncertainty, Spring 2020
- SE 494 Senior Design Project, Spring 2017, Spring 2018, Fall 2018
- IE 521 Convex Optimization, Spring 2017, Spring 2019
- IE 598 Big Data Optimization, Fall 2016, Spring 2018
- IE 300 Analysis of Data, Spring 2016, Fall 2017, Spring 2020
Research Interests
- Reinforcement Learning
- Optimization under Uncertainty
- Machine Learning
- Large-scale Optimization
Teaching Honors
- List of Teachers Ranked as Excellent, UIUC (Spring 2018)
- List of Teachers Ranked as Excellent, UIUC (Spring 2017)
- List of Teachers Ranked as Outstanding, UIUC (Fall 2016)
- Collins Scholar, UIUC (Spring 2016)
Research Honors
- Center for Advanced Study (CAS) Fellow (2020)
- National Center for Supercomputing Applications (NCSA) Fellow (2018)
- NSF CISE Research Initiation Initiative (CRII) Award (2018)
- SIAM Early Career Travel Award, Society of Industrial and Applied Mathematics (2017)
- Best Paper Award, Artificial Intelligence and Statistics 2016 (2016)
Courses Taught
- IE 300 - Analysis of Data
- IE 521 - Convex Optimization
- IE 598 - Big Data Optimization
- IE 598 - Optimization Under Uncertainty