About Me

I'm currently a postdoctoral research fellow at Harvard-MGB. Before that, I received a PhD in Information from University of Michigan, School of Information (UMSI) and a BS in Statistics from University of California, Los Angeles (UCLA) with a minor in Digital Humanities.

My research spans the following methodology areas including Artificial Intelligence, Data Technologies, Natural Language Processing, and Social Computing. I apply these methods to domains including Medical AI, Health Informatics, Science of Science, Social Media, and Digital Humanities.

Here’s a PDF of my CV.

Teaching

• SI 507. Intermediate Programming @University of Michigan, Winter 2024
• SI 671. Data Mining: Methods and Applications @University of Michigan, Fall 2023
• DH 199. Capstone: The Online Statistical Computing Reference (OSCR) for digital humanities and social sciences @UCLA, Winter 2020

Employment

• Postdoctoral Research Fellow @AI in Medicine Program, Harvard-MGB, Sep 2024 - Present
• Data Scientist Intern @Procter & Gamble, May - Aug, 2023
• Data Scientist & Pre-doctoral Researcher @UCLA Digital Humanities, Jun 2019 - Jul 2021

Get in Touch

Email is best.

Publications

For a complete list of my publications, please visit my Google Scholar page.

Data Technologies, Data Archives, and Science of Science

• Fan, L., Li, L., Ma, Z., Lee, S., Yu, H., & Hemphill, L. (2024) A Bibliometric Review of Large Language Models Research from 2017 to 2023. ACM Transactions on Intelligent Systems and Technology. doi: 10.1145/3664930
• Yu, H.*, Fan, L.*, Li, L., Zhou, J., Ma, Z., Xian, L., Hua, W., He, S., Jin, M., Zhang, Y., Gandhi, A., & Ma, X. (2024) Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis. Journal of Healthcare Informatics Research. doi: 10.1007/s41666-024-00171-8
• Hemphill, L., Thomer, A., Lafia, S., Fan, L., Bleckley, D., & Moss, E. (2024) A Dataset for Measuring the Impact of Research Data and their Curation. Scientific Data. doi: s41597-024-03303-2
• Fan, L., Lafia, S., Wofford, M., Thomer, A.K., Yakel, E., & Hemphill, L. (2023) Mining Semantic Relations in Data References to Understand the Roles of Research Data in Academic Literature. Proceedings of the ACM/IEEE Joint Conference on Digital Libraries. doi: 10.1109/JCDL57899.2023.00039
• Fan, L., Lafia, S., Li, L., Yang, F., & Hemphill, L. (2023) DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization. Proceedings of the Association for Information Science and Technology (ASIS&T). doi: 10.1002/pra2.820
• Hemphill, L., Xing, J., & Fan, L. (2023) Comparing Costs for Cloud-based Data Archives. Preprint
• Fan, L.†, Yin, Z., Yu, H., & Gilliland, A.J. (2022) Using Machine Learning to Enhance Archival Processing of Social Media Archives. Journal on Computing and Cultural Heritage. doi: 10.1145/3547146
• Lafia, S., Fan, L., & Hemphill, L. (2022) A Natural Language Processing Pipeline for Detecting Informal Data References in Academic Literature. Proceedings of the Association for Information Science and Technology (ASIS&T). doi: 10.1002/pra2.614
• Lafia, S., Fan, L., Thomer, A.K., & Hemphill, L. (2022) Subdivisions and Crossroads: Identifying Hidden Community Structures in a Data Archive’s Citation Network. Quantitative Science Studies. doi: 10.1162/qss_a_00209
• Fan, L., Lafia, S., Bleckley, D., Moss, E., Thomer, A.K., & Hemphill, L. (2022) Librarian-in-the-Loop: A Natural Language Processing Paradigm for Detecting Informal Mentions of Research Data in Academic Literature. Working paper for the ACM CHI'22 Workshop on Data Work Across Domains

Social Media, Inclusive Language, and Health Informatics

• Li, L., Fan, L., Atreja, S., & Hemphill, L. (2024) "HOT" ChatGPT: The Promise of ChatGPT in Detecting and Discriminating Hateful, Offensive, and Toxic Comments on Social Media. ACM Transactions on the Web. doi:10.1145/3643829
• Fan, L.†, Li, L., & Hemphill, L. (2024) Characterizing Online Toxicity During the 2022 Mpox Outbreak: A Computational Analysis of Topical and Network Dynamics. Journal of Medical Internet Research. Accepted.
• Li, L., Ma, Z., Fan, L., Lee, S., Yu, H., & Hemphill, L. (2023) ChatGPT in Education: A Discourse Analysis of Worries and Concerns on Social Media. Education and Information Technologies. doi: 10.1007/s10639-023-12256-9
• Fan, L., Yu, H., & Gilliland, A.J. (2022) Aggravated Anti-Asian Hate since COVID-19 and the #StopAsianHate Movement: Connection, Disjointness, and Challenges. In book Hate Speech on Social Media: A Global Approach. doi: 10.25768/654-916-9
• Yu, H., Fan, L., & Gilliland, A.J. (2022) Disparities and Resilience: Analyzing Online Health Information Provision, Behaviors and Needs of LBGTQ+ Elders During COVID-19. BMC Public Health. doi: 10.1186/s12889-022-14783-5
• Fan, L., Yu, H., Yin, Z., & Gilliland, A.J. (2021) #StopAsianHate: Archiving and Analyzing Twitter Discourse in the Wake of the 2021 Atlanta Spa Shootings. Proceedings of the Association for Information Science and Technology (ASIS&T). doi: 10.1002/pra2.475
• Fan, L., Yu, H., & Yin, Z. (2020) Stigmatization in Social Media: Documenting and Analyzing Hate Speech for COVID-19 on Twitter. Proceedings of the Association for Information Science and Technology (ASIS&T). doi: 10.1002/pra2.313
• Yin, Z.*, Fan, L.*, Yu, H., & Gilliland, A.J. (2020) Using a Three-step Social Media Similarity (TSMS) Mapping Method to Analyze Controversial Speech Relating to COVID-19 in Twitter Collections. Proceedings of the IEEE International Conference on Big Data (Big Data). doi: 10.1109/BigData50022.2020.9377930

Social Computing and Digital Humanities

• Presner, T. & Fan, L. (2024) Algorithmic Close Reading: Analyzing Vectors of Agency in Holocaust Testimonies. In book Ethics of the Algorithm: Holocaust Memory, the Distant Witness, and the Future of Testimony. Princeton University Press.
• Hua, W.*, Fan, L.*, Li, L., Hemphill, L., & Zhang, Y. (2024) War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars. Submitted to the Thirteenth International Conference on Learning Representations (ICLR 2025).
• Lin, S., Hua, W., Li, L., Chang, C., Fan, L., Ji, J., Hua, H., Jin, M., Luo, J., & Zhang, Y. (2024) BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024) Demo Track
• Fan, L. & Presner, T. (2022) Algorithmic Close Reading: Using Semantic Triplets to Index and Analyze Agency in Holocaust Testimonies. Digital Humanities Quarterly
• Presner, T., Bonazzi, A., Fan, L., Tóth, G., Deblinger, R., & Shepard, D. (2020) Digital Humanities Methods for Analyzing Holocaust and Genocide Testimonies. Panel Abstract for Digital Humanities Conference (DH2020)

Natural Language Processing, Large Language Models, and Medical AI

• Fan, L.*, Hua, W.*, Li, L., Ling, H., & Zhang, Y. (2024) NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).
• Fan, L.*, Hua, W.*, Li, X.*, Zhu, K., Jin, M., Li, L., Ling, H., Chi, J., Wang, J., Ma, X., & Zhang, Y. (2024) NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models. Submitted to the 2025 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2025).
• Hua, W.*, Zhu, K.*, Li, L., Fan, L., Jin, M., Xue, H., Li, Z., Wang, J., & Zhang, Y. (2024) Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities. Preprint.
• Yu, H., Zhou, J., Li, L., Chen, S., Gallifant, J., Shi, A., Li, X., Jin, M., Hua, W., Chen, G., Zhou, Y., Li, Z., Gupte, T., Chen, M.-L., Azizi, Z., Zhang, Y., Assimes, T. L., Ma, X., Bitterman, D. S., Lu, L., & Fan, L.†, AIPatient: Simulating Patients with LLM-Powered Agentic Workflows. Journal of the American Medical Association (JAMA). Under review.
• Chen, S., Gao, M., Sasse, K., Hartvigsen, T., Anthony, B., Fan, L., Aerts, H., Gallifant, J., & Bitterman, D., Wait, but Tylenol is Acetaminophen... Investigating and Improving Language Models' Ability to Resist Requests for Misinformation. Preprint.
• Li, X.*, Fan, L.*, Wu, H., Chen, K., Yu, X., Chao, C., Cai, Z., Niu, X., Cao, A., & Ma, X. (2024) Enhancing Autism Spectrum Disorder Early Detection with the Parent-Child Dyads Block-Play Protocol and an Attention-enhanced GCN-xLSTM Hybrid Deep Learning Framework. Engineering Applications of Artificial Intelligence. Under review.
• Lv, C.*, Fan, L.*, Li, H.*, Ma, J., Jiang, W., & Ma, X. (2024) Leveraging Multimodal Deep Learning Framework and a Comprehensive Audio-Visual Dataset to Advance Parkinson’s Early Detection. Biomedical Signal Processing and Control. doi: 10.1016/j.bspc.2024.106480
• Wang, X.*, Fan, L.*, Li, H.*, Jiang, W., Bi, X., & Ma, X. (2024) Skip-AttSeqNet: Leveraging Skip Connection and Attention-Driven Seq2seq Model to Enhance Eye Movement Event Detection in Parkinson's Disease. Biomedical Signal Processing and Control. doi: 10.1016/j.bspc.2024.106862
• Li, L., Zhou, J., Gao, Z., Hua, W., Fan, L., Yu, H., Hagen, L., Zhang, Y., Assimes, T. L., Hemphill, L., & Ma, S. (2024) A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs). npj Digital Medicine. Under review.
• Jin, M., Yu, Q., Dong, S., Zhang, C., Fan, L., Hua, W., Zhu, S., Meng, Y., Wang, Z., & Zhang, Y. (2024) Health-LLM: Personalized Retrieval-Augmented Disease Prediction System. Submitted to the 31st International Conference on Computational Linguistics (COLING 2025) System Demonstration Track.

Presentations and Invited Talks

• Fan, L. (2024) Large Language Model-powered Multi-agent Systems for Health and Social Informatics. Invited talk at UCLA Digital Humanities Program and Information Studies Department.
• Fan, L. (2024) War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars. Invited talk at the Wolfram Colloquium: LLM Agents for Modeling Group Dynamics.
• Fan, L. (2024) Advancing Medical AI: Auxiliary Diagnosis, LLM Reasoning, and AI Agents. Job talk at the Artificial Intelligence in Medicine (AIM) Program at Mass General Brigham and Harvard Medical School.
• Hua, W., & Fan, L. (2024) War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars. Invited talk at the BAAI Young Scientist Association (Qingyuan Club).
• Fan, L., & Hua, W. (2023) NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes. Invited talk at the BAAI Young Scientist Association (Qingyuan Club).
• Fan, L. (2021) Archival Data Thinking. A guest lecture for UCLA Information Studies (Management of Digital Records, Fall 2021).

One More Thing

I'd like to acknowledge my junior high school math teacher Chunhong Hu, who kindly and patiently oriented me for doing research and writing academic articles in his leisure time. It is my honor to include the two high school math research papers advised by him in 2010-2011, on my Google Scholar page.