Dr. Jingrui He

Professor

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Biography

Jingrui He is a professor at the School of Information Sciences, University of Illinois Urbana-Champaign, where he also serves as the MSIM Program Director. He received his PhD in Machine Learning from Carnegie Mellon University in 2010. His research interests focus on heterogeneous machine learning, active learning, neural bandits, self-supervised learning, and their applications in sustainability, agriculture, social network analysis, healthcare, and finance. He has published over 200 papers in top-tier conferences such as ICML, NeurIPS, ICLR, and KDD, as well as in prestigious journals including TMLR, TKDD, JMLR, and JAIR. He is an ACM Distinguished Member and a Senior Member of AAAI and IEEE. He has received numerous awards for his research including the NSF CAREER Award and multiple IBM Faculty Awards. In addition to his academic achievements, he has been recognized as a Top Reviewer at NeurIPS and ICML, and has received distinguished paper awards at conferences such as FAccT and ICCV.

Research Interests

Experience

Professor

2016-01-01 — Present

University of Illinois Urbana-Champaign • Champaign, IL

Professor at the School of Information Sciences, involved in teaching and research.

Awards

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Outstanding Paper Award

2025-01-01
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Top Reviewer

2025-01-01
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Amazon Research Award

2025-01-01
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ACM Distinguished Member

2023-01-01
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FAccT Distinguished Paper Award

2022-01-01
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Teachers Ranked Excellent by Students

2021-01-01

Requirements for University of Illinois

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:7
Reading
Required:7
Writing
Required:7
Speaking
Required:7
Overall
Required:7.5
TOEFL
Listening
Required:17
Reading
Required:19
Writing
Required:21
Speaking
Required:20
Total
Required:103
GRE General
Prerequisites
Mathematical background Linear Algebra Calculus
Application Checklist
  • Online application
  • Unofficial transcripts
  • 3 Letters of Recommendation
  • Academic Statement of Purpose
  • Resume/CV
Specialization Notes

GRE is optional for admission to all graduate programs in Statistics. Full status admission requires higher language scores than limited status.