I am an assistant professor at the Department of Computer Science and Data Science at the University of Chicago. I am also affiliated with the Harris School of Public Policy. I direct the Chicago Human+AI lab (CHAI) (). You can learn more about my life trajectory and find my official biography here.

My main research interests include

1. Human-centered machine learning, how we can use machine learning to empower humans and augment human intelligence in decision making and writing, including both generating explanations to explain machine learning models and developing novel interaction paradigms and evaluation setups.

2. Language and social dynamics.
   

   • The effect of wording, how language influences social interaction, e.g., persuasion, information sharing, media selection of highlights from presidential debates.
   • The ecosystem of ideas, how ideas relate to each other and evolve over time, e.g., idea relations and lost in propagation.

3. Multi-community engagement, how a person interacts with multiple communities and how communities relate to each other, e.g., the divergence of COVID communities and migrant integration in urbanization.

I am also broadly interested in natural language processing, computational social science, and artificial intelligence. Here is my CV.

News:

• I was selected as a Sloan Research Fellow in 2023.

Selected recent work:

• Check out my recorded talk, Three Lessions towards Human-Centered Explanations, for the AI & HCI workshop at ICML!
• Check out our recorded videos for a NAACL tutorial on human-centered evaluation of explanations!
• Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, and Chenhao Tan. Learning Human-Compatible Representations for Case-Based Decision Support. In Proceedings of ICLR 2023.
• Vivian Lai, Samuel Carton, Rajat Bhatnagar, Q. Vera Liao, Yunfeng Zhang, and Chenhao Tan. Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation. CHI 2022.
• Chao-Chun Hsu and Chenhao Tan. Decision-focused Summarization. EMNLP 2021.
• Han Liu, Vivian Lai, and Chenhao Tan. Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making. CSCW 2021.

Openings:

I have a postdoc opening on human-centered AI that can start any time. Please email me your CV and names of references. I am particularly open to students who have background in medicine and policy (e.g., MD/PhD and PhD students in economics).

I am always looking for motivated postdocs and PhD students who are interested in NLP, human-centered-AI, data science, computational social science, or machine learning! Please read this FAQ before contacting me.

Demo systems:

• Task delegability, should AI be used for X?
• Reddit genealogy, visualizing the genealogy between Reddit communities.
• retweetedmore, predicting which tweet is going to be retweeted more.

If you want to learn more about my research, check my papers. And kudos to all my collaborators!