Xiaohan Ding
Postdoctoral Researcher, Georgia Institute of Technology
HCI · NLP · Computational Social Science
I am a Postdoctoral Researcher in the School of Interactive Computing at Georgia Institute of Technology, working with my advisor Dr. Munmun De Choudhury. My research focus includes Computational Social Science (CSS), Human Computer Interaction (HCI), AI Mediated Communication (AIMC), and use of Natural Language Processing (NLP). I explore decades of closed caption data from major news outlets, online community interactions, and public health or mental health issues.
I received my Ph.D. in Computer Science from Virginia Tech, advised by Dr. Eugenia Rho, and an MS in Computer Science from George Mason University under instruction from Dr. Gheorghe Tecuci.
Research Interests
Education
Postdoctoral Researcher, School of Interactive Computing
Georgia Institute of Technology · Dr. Munmun De Choudhury
Ph.D. in Computer Science
Virginia Tech · Dr. Eugenia Rho
M.S. in Computer Science
George Mason University · Dr. Gheorghe Tecuci
B.E. in Software Engineering
Jinan University · Dr. Kun Liu & Dr. Lin Wang
Talks
Human-Centered NLP for Social Media Understanding
Research Talk, University at Buffalo
From Principles to Practice: Teaching Innovation with UDL and Artificial Intelligence
VT UDL Days, Virginia Tech
When Language Shapes Behavior: That Understands, Predicts, and Intervenes
Postdoc Research Talk, University of Washington
When Language Shapes Behavior: That Understands, Predicts, and Intervenes
Faculty Job Talk, Texas State University
Bridging Understanding and Intervention: AI-Mediated Interactions for Online Communication
Postdoc Research Talk, Georgia Institute of Technology
Designing Human-AI Collaboration to Support Learning in Counterspeech Writing
IEEE VL/HCC 2025, North Carolina
Future of GenAI: Designing Human-AI Collaboration
OpenAtom Foundation & Alibaba
Experiences, Barriers, and Challenges for Engaging International Students in STEM
Universal Design for Learning Day, Virginia Tech
Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language
ACM CHI 2024, Honolulu, Hawaii