Assistant Professor

Assistant Professor, Department of Information Technology and Management (ITM)
Postdoc Scholar, Computational Science and Engineering, Georgia Institute of Technology
Ph.D., Computer Science, University of Texas at Dallas

Office:	IIT Galvin Tower #15E3-3, 10 West 35th Street, Chicago, IL 60616, USA Chicago, IL (Google Map Location)
Office Hour:	Thursday 2-4pm
Telephone:	Click to show
Email:	yhu89 [at] illinoistech [dot] edu
LinkedIn:

👉 Prospective Students

I am looking for highly motivated PhD students (Fall 2026). I also welcome inquiries from outstanding students and research interns/visiting researchers interested in working with my group. See more details →

About

Dr. Yibo Hu is an Assistant Professor in the Department of Information Technology and Management, College of Computing, at Illinois Institute of Technology. Before joining IIT, he was a Postdoctoral Scholar in the School of Computational Science and Engineering at the Georgia Institute of Technology. His research develops efficient and trustworthy AI methods for socially important domains where automated predictions influence public perception, policy, safety, or human well-being. His work studies robustness and uncertainty in socially embedded AI systems, with applications spanning global political events, social networks, and cybersecurity. More recently, his research examines safety and social dynamics in modern LLM- and agent-based AI systems.

Research Interests

• Trustworthy and robust AI
• LLM and Agent-Based Systems
• AI in Social and Security-Critical Domains

Selected Publications

Trustworthy & Robust AI

Yibo Hu, and Latifur Khan. Uncertainty-aware reliable text classification. KDD 2021. [link]

Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, and Feng Chen. Multidimensional Uncertainty-Aware Evidential Neural Networks. AAAI 2021. [link]

Yiqiao Jin, Mohit Chandra, Gaurav Verma, Yibo Hu, Munmun De Choudhury, Srijan Kumar. Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queries. WWW 2024. [link]

LLMs in Social & Political Contexts

Yibo Hu, Erick Skorupa Parolin, Latifur Khan, Patrick T. Brandt, Javier Osorio, Vito J. D'Orazio. Leveraging Codebook Knowledge with NLI and ChatGPT for Zero-Shot Political Relation Classification. ACL 2024. [link]

Yibo Hu, MohammadSaleh Hosseini, Erick Skorupa Parolin, Javier Osorio, Latifur Khan, Patrick Brandt, and Vito D'Orazio. ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence. NAACL 2022. [link]

Bing He, Yibo Hu, Yeon-Chang Lee, Soyoung Oh, Gaurav Verma, Srijan Kumar. A Survey on the Role of Crowds in Combating Online Misinformation: Annotators, Evaluators, and Creators. ACM TKDD 19, no. 1 (2024): 1-30 [link]

AI Safety & Deception

Yibo Hu, Yu Lin, Erick Skorupa Parolin, Latifur Khan, and Kevin Hamlen. Controllable Fake Document Infilling for Cyber Deception. EMNLP 2022 (Findings). [link]

Advising

I’m fortunate to work with the following students on research projects.

Master’s Students

• Illinois Tech
  • Suraj Babu Thimma Krishnaram – hate speech moderation
  • Bharath Raahul Murugesan – social event coding
  • Karthikeyan Saravanan – multi-agent LLM behaviors
• Visiting / Dual Program (Europe)
  UPC = Universitat Politècnica de Catalunya, Spain; UPM = Universidad Politécnica de Madrid, Spain.
  • Carlota Julbe (UPC) – robust machine learning
  • Diego Fernandez Arias (UPM) – tool-using agent security
  • Pablo Bote (UPM) – LLM vulnerability analysis

Teaching

• ITMD 524: Applied Artificial Intelligence and Deep Learning (Graduate), Illinois Tech, Fall 2025, Spring 2026
• ITMD 523: Advanced Topics in Data Management (Graduate), Illinois Tech, Spring 2026
• CSE 8803 DSN: Data Science for Social Networks (Graduate), Georgia Tech, Fall 2023

Service

Editorial Roles

• Co-Editor, Graph-Based Retrieval-Augmented Generation Systems, Frontiers in Big Data (2025-2026) [link]

Program Committee & Reviewing

• ACL (2023-), EMNLP (2022-), NAACL (2024-), WWW (2024-)
• IJCAI (Distinguished PC Member, 2023), KDD (2020-)
• SDM (2022-), DASFAA (2023), IJCNN (2024), DSAA (2025)
• Data4SoftSec 2026 (Workshop on Datasets for Software Security @ IEEE S&P)