Welcome to Xuan’s Homepage!

I am an Assistant Professor in the Computer Science Department at Virginia Tech (VT). I am also a faculty member of the Sanghani Center for Artificial Intelligence and Data Analytics at VT.

I received my Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (UIUC) under the supervision of Dr. Jiawei Han. During my Ph.D. study, I also worked at IBM Research as a summer intern. I received my M.S. in Statistics and my M.S. in Biochemistry from UIUC. I received my B.S. in Biological Science from Tsinghua University, China.

Research Interests

My primary research interests are in the fields of Natural Language Processing (NLP) and Data Mining (DM). I am specifically interested in developing principled data-driven approaches with light human effort for effective and scalable model learning.

• Natural Language Processing (NLP):
  • Information extraction, knowledge graph construction, text classification, …
  • Weakly-supervised/few-shot/zero-shot learning
• Fact-checking and Trustworthy NLP:
  • Fact-checking for generative large language models
  • Trustworthy large language models: groundedness, confidence, explainability, …
• AI for Sciences; AI for Healthcare:
  • Large language models for sciences and healthcare
  • Brain large language models
  • Multi-omics large language models

News and Highlights

• (10/29/24) We are excited to present our tutorial of “AI for Science in the Era of Large Language Models” at AAAI’25. Looking forward to seeing everyone in Philadelphia!
• (10/26/24) One paper is accepted by IEEE-BigData’24. Congratulations to my student Hanwen for his work on EEG-to-text translation with multi-view Transformer!
• (10/2/24) We are grateful to receive yet another award from NSF NAIRR Pilot to support our research on network-regulated large language models for multi-omics data analysis.
• (9/20/24) We are excited to present our tutorial of “AI for Science in the Era of Large Language Models” at EMNLP’24. Looking forward to seeing everyone in Miami!
• (9/20/24) One paper is accepted by EMNLP’24. Congratulations to my student Meng for his work on better multi-agent collaboration for LLM-based clinical triage!
• (9/9/24) Congratulations to my student Daniel for receiving the Davenport Leadership Scholarship from CS@VT!
• (7/22/24) We are grateful to receive a new grant from the Amazon + VT Center for Efficient and Robust ML to support our research on long-context reasoning with large language models. (VT News)
• (6/28/24) We are grateful to receive a new grant from the Commonwealth Cyber Initiative (CCI) to support our research on EHR digital twin generation with large language models.
• (6/16/24) Three papers are accepted by ICML’24 AI4Science. Congratulations to my students, Meng whose paper was accepted as a spotlight, and Hanwen and Sindhura whose papers were accepted as posters!
• (5/21/24) We are excited and grateful to receive an award from NSF NAIRR Pilot to support our research on complex reasoning in large language models. (VT News)
• (5/17/24) One paper is accepted by ACL’24 and one paper is accepted by KDD’24. Congratulations to all the authors!
• (3/26/24) Check out our new survey paper on LLMs for diverse biomedical data! We explored three critical categories of biomedical data: 1) textual data (biomedical literature and health records), 2) biological sequences (DNA/RNA/protein sequences and multi-omics sequencing data), and 3) brain signals (time-series EEG data).

My Schedule

You can find my schedule here. The “Week” view will present you the details of slots.

Prospective Students

My lab at Virginia Tech has openings for PhD/Master students and Post-doc researchers and research internship opportunities for undergrad students. We are looking for students with a strong background in NLP, data mining, deep learning, or bioinformatics.

Please email me if you’re interested in working with me. In your email, please include the following items:

• Title as “Prospective Student: YourName - YourAffliation”
• Briefly introduce what research problem you are interested in.
• Briefly introduce yourself, including education background, research experiences, and programming skills.
• Briefly explain your motivations and expectations of working with me.
• Include a PDF version of your CV.

Due to the high volume of emails, I may not be able to respond to every one I receive.

• For prospective PhD/MS students outside of VT, please include my name as one of your interested faculty members in your graduate application. This will make it easier for me to locate your application during the review process.
• For current PhD/MS/undergraduate students at VT, the best way to learn more about our research is to attend my classes, visit my office hours, or engage with my graduate students in DDS 362 and 364.
• For prospective Post-docs, please check out this prestigious Virginia Tech Presidential Postdoctoral Fellowship. If you’re interested in joining our research group, I would be happy to help you with the application process.