Dr. Yun Huang

Associate Professor

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Biography

Yun Huang is an associate professor in the School of Information Sciences at the University of Illinois at Urbana-Champaign. He co-directs the Social Computing Systems (SALT) Lab and focuses on research in social computing systems, investigating context-driven approaches to designing crowdsourcing systems. His work examines how context impacts user contributions in these systems and leverages contextual effects to innovate social computing systems that engage users. Huang received his PhD from the Donald Bren School of Information and Computer Sciences at the University of California, Irvine, and holds a bachelor's degree from the Department of Computer Science and Technology at Tsinghua University in Beijing, China. Before joining Illinois, he was a faculty member at the School of Information Studies at Syracuse University and a postdoctoral fellow at Carnegie Mellon University.

Research Interests

Experience

Associate Professor

— Present

University of Illinois at Urbana-Champaign • Champaign, IL

Faculty member in the School of Information Sciences.

Faculty Member

— Present

School of Information Studies, Syracuse University • Syracuse, NY

Engaged in teaching and research.

Postdoctoral Fellow

— Present

Carnegie Mellon University • Pittsburgh, PA

Conducted advanced research in social computing.

Awards

#

Linowes Faculty Fellowship

#

OpenAI Researcher Access Program

#

Early Career Development Grant

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.