Hang Jiang

Contact

Hi, I am a tenure-track Assistant Professor in AI at Northeastern University, with a joint appointment in Information Systems and Computer Science. I am also affiliated with Harvard University's Institute for Quantitative Social Science (IQSS). Previously, I was a postdoctoral AI researcher at the MIT-IBM Watson AI Lab. My research focuses on AI agents, LLMs/NLP, human–AI interaction, and AI for society. Through an interdisciplinary approach that integrates computational methods with social science insights, I aim to develop AI systems that foster a healthier and more connected society.

I completed my Ph.D. at MIT, advised by Deb Roy, where I studied the foundations of LLMs and their applications to human communication at scale, and was affiliated with the MIT Media Lab. Earlier, I earned an M.S. in Symbolic Systems from Stanford University, affiliated with the Stanford NLP Group, and a B.S. in Computer Science and a B.A. in Linguistics, Summa Cum Laude, from Emory University.

I welcome research collaboration and mentorship opportunities. Please reach out via email.

News

I'm Recruiting PhD Students and Research Assistants!

I am actively recruiting motivated PhD students to join my research group at Northeastern University starting Fall 2026. I am also looking for Research Assistants (RAs) for collaborative projects starting Spring 2026.

I welcome both undergraduate and graduate students who are interested in AI agents, LLMs, human-AI interaction, or AI for society to reach out via email (hang.jiang [AT] northeastern [DOT] edu) with your CV and a brief description of your research interests. Please include <husky> in your subject line.

See details below ↓

Research Areas

My research focuses on building intelligent AI systems that can effectively collaborate with humans in real-world settings. Key areas include:

AI Agents

Developing autonomous agents that can plan, reason, and execute complex tasks in real-world workplaces using tool-calling and multi-step reasoning.

LLMs / NLP

Understanding and improving the fundamental capabilities of large language models, including reasoning, knowledge representation, and alignment.

Human-AI Interaction

Designing systems that enable effective collaboration between humans and AI, studying how people interact with and are impacted by AI technologies.

AI for Society

Applying computational social science methods to understand social phenomena at scale, including political communication, public discourse, and societal impacts of AI.

Prospective Students

I'm excited to build a research group at Northeastern! Here's what you need to know:

How to Apply
  • PhD Applicants (Fall 2026): Apply through the Khoury College of Computer Sciences PhD program and mention my name in your application.
  • Research Assistants (Spring 2026): Email me (hang.jiang [AT] northeastern [DOT] edu) with your CV and a brief statement about your research interests. Please include <husky> in your subject line.
  • Strong in coding and ML: Solid programming skills (e.g., Python) and hands-on experience with deep learning frameworks (e.g., PyTorch)
  • Familiar with AI workflow: Familiar with AI coding assistants (e.g., Cursor, Claude Code, Codex) to facilitate research and development
  • Research-oriented: Prior research experience through publications, thesis work, or substantial projects is valued
  • From diverse backgrounds: I welcome students from various fields including computer science, linguistics, cognitive science, and related areas
  • Self-motivated: Curious, independent thinkers who can identify interesting problems and drive projects forward
  • Hands-on mentorship: Regular meetings to discuss research progress, provide feedback, and navigate challenges together
  • Student autonomy: I encourage students to develop their own research direction and take ownership of their projects
  • Industry connections: I help students build networks through internships, collaborations, and connections with industry research labs

Selected Publications

* indicates equal contribution. See full list on Google Scholar.

Leveraging Large Language Models for Learning Complex Legal Concepts through Storytelling
Hang Jiang, Xiajie Zhang, Robert Mahari, Daniel Kessler, Eric Ma, Tal August, Irene Li, Alex 'Sandy' Pentland, Yoon Kim, Deb Roy, Jad Kabbara
ACL 2024
Paper arXiv Code
PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits
Hang Jiang, Xiajie Zhang, Xubo Cao, Cynthia Breazeal, Deb Roy, Jad Kabbara
NAACL (Findings) 2024
Paper arXiv Code
Covered by Science, ACM
Bridging Dictionary: AI-Generated Dictionary of Partisan Language Use
Hang Jiang*, Doug Beeferman*, William Brannon, Andrew Heyward, Deb Roy
CSCW Demo 2024
Paper arXiv Demo
CommunityLM: Probing Partisan Worldviews from Language Models
Hang Jiang, Doug Beeferman, Brandon Roy, Deb Roy
COLING 2022
Paper arXiv Code Models
Contrastive Learning of Medical Visual Representations from Paired Images and Text
Yuhao Zhang*, Hang Jiang*, Yasuhide Miura, Christopher D. Manning, Curtis P. Langlotz
MLHC 2022
Paper arXiv
ConVIRT inspired OpenAI's CLIP
LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking
Hang Jiang*, Sairam Gurajada*, Qiuhao Lu, Sumit Neelam, Lucian Popa, Prithviraj Sen, Yunyao Li, Alexander Gray
ACL 2021
Paper arXiv Code

Teaching