Dr. Shimei Pan

Associate Professor · Tenured

Department of Information Systems

College of Engineering and Information Technology

About

Dr. Pan is an Associate Professor at the Information Systems Department of UMBC. Before joining UMBC, Dr. Pan was a research scientist at IBM Watson Research Center. Her research interests include Natural Language Processing (NLP), Social Media Analytics, Bias and Fairness in AI and Human-AI Interaction. Dr. Pan has served on the program committees of major international conferences (e.g., ACL, EMNLP, NAACL, IJCAI). She was the program chair of 2015 and conference chair of 2019 ACM IUI. She was the program chair of IEEE ICTAI 2020. Currently, she is an associate editor of ACM Transactions on Interactive Intelligent Systems (TIIS) and a member of the steering committee of IUI. Dr. Pan received a Ph.D. in Computer Science from Columbia University

Research interests

Natural Language Processing (NLP), Social Media Analytics , Artificial Intelligence (AI), Machine Learning (ML), Big Data, Computational Social Science, Computational Psychology, Speech Processing, Dialogue Systems, Fair AI and Machine Learning, Human-AI Interaction, User Modeling and Personalization.

Teaching interests

Artificial Intelligence (AI), Natural Language Processing (NLP), Social Media Analytics, Information Extraction (IE), Machine Learning (ML), Data Mining (DM) and Database Systems.

Education

  • Ph D, Computer Science — Columbia University (2002)
    Prosody Modeling for Concept to Speech Generation
  • Other, Computer Science — Columbia University (1998)
  • BS, Computer Science — Tsinghua University (1991)
    Corpus-based Chinese Parsing

Publications

  • Developing Problem-Solving Competency in Data Science: Exploring A Case-Based Approach 2025 Provost's Teaching & Learning Symposium Lujie Chen, Maryam A Alomair, Muhammad Ali Yousuf, Shimei Pan
  • Can generative AI be egalitarian? 2024 IEEE CTSoc News on Consumer Technology (NCT) · IEEE James Foulds, Shimei Pan, Philip Feldman
  • RAGged edges: the double-edged sword of retrieval-augmented chatbots 2024 ArXiv preprint arXiv:2403.01193v2 [cs.CL] · Submitted James Foulds, Philip Feldman, Shimei Pan
  • When Biased Humans Meet Debiased AI: A Case Study in College Major Recommendation 2023 ACM Transactions on Interactive Intelligent Systems (TiiS) · 13 (3) Clarice Wang, Kathryn Wang, Andrew Y Bian, Rashidul Islam, Kamrun Naher Keya, James Foulds, Shimei Pan
  • Do humans prefer debiased AI algorithms? A case study in career recommendation 2022 27th Annual Conference on Intelligent User Interfaces (IUI) Clarice Wang, Kathryn Wang, Andrew Y Bian, Rashidul Islam, Kamrun Naher Keya, James Foulds, Shimei Pan
  • Causal feature selection with dimension reduction for interpretable text classification 2022 9th Mid-Atlantic Student Colloquium on Speech, Language and Learning (MASC-SLL 2022). ArXiv preprint arXiv:2010.04609v1 [cs.LG] Guohou Shan, Arpita Roy, James Foulds, Shimei Pan
  • Machine Learning and Student Performance in Teams 2020 Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science · Springer International Publishing · 12164 · pp. 301-305 Rohan Ahuja, Daniyal Khan, Sara Tahir, Magdalene Wang, Danilo Symonette, Shimei Pan, Simon Stacey, Donald Engel
  • An Intersectional Definition of Fairness 2020 36th IEEE International Conference on Data Engineering (ICDE) · IEEE James Foulds, Rashidul Islam, Kamrun Keya, Shimei Pan
  • Mitigating Socio-lingustic Bias in Job Recommendation 2020 Mid-Atlantic Student Colloquium on Speech, Language and Learning (MASC-SLL) · Accepted Ketki Deshpande, Shimei Pan, James Foulds
  • Differential Fairness 2019 NeurIPS 2019 Workshop on Machine Learning with Guarantees James Foulds, Rashidul Islam, Kamrun Keya, Shimei Pan
  • Fair inference for discrete latent variable models ArXiv preprint arXiv:2209.07044v1 [cs.LG] · Submitted Rashidul Islam, Shimei Pan, James Foulds
  • Tell me something that will help me trust you: A survey of trust calibration in human-agent interaction ArXiv preprint arXiv:2205.02987 [cs.HC], 2022 · Submitted George J Cancro, Shimei Pan, James Foulds
  • Polling latent opinions: A method for computational sociolinguistics using transformer language models ArXiv preprint arXiv:2204.07483 [cs.CL] · Submitted Philip Feldman, Aaron Dant, James Foulds, Shimei Pan
  • An Intersectional Definition of Fairness ArXiv preprint arXiv:1807.08362 [CS.LG]. Submitted to International Joint Conference on Artificial Intelligence (IJCAI) 2019 · Under Review James Foulds, Kamrun N Keya, Rashidul Islam, Shimei Pan

Presentations

  • Can Generative AI be Egalitarian? 2025 1st Workshop on Preparing Good Data for Generative AI: Challenges and Approaches, AAAI 2025, (GOOD-DATA @ AAAI 2025) · The Association for the Advancement of Artificial Intelligence · Keynote/Plenary Address Shimei Pan, James Foulds
  • SDM 2023 tutorial: “How to Design a Fair Data Mining System: Navigating the Trade-Offs,” April 2023 2023 Society of Industrial and Applied Mathematics (SIAM) Data Mining (SDM 2023) · Society of Industrial and Applied Mathematics (SIAM) · Oral Presentation James Foulds (Presenter), Shimei Pan (Presenter)
  • Differential Fairness for Machine Learning and Artificial Intelligence Systems: Unbiased Decisions with Biased Data 2018 National Institute of Standards (NIST) AI Community of Interest Seminar · National Institute of Standards (NIST) · Oral Presentation James Foulds, Shimei Pan

Grants and Contracts

  • AI-DCL: Fairness for the Allocation of Healthcare Resources 2019 NSF · Grant · Funded James Foulds (Principal), Shimei Pan (Co-Principal), Ian J Stockwell (Co-Principal)
  • Assessing the Reliability and Robustness of Generative AI: Humans and AI Each Hold up Half the Sky ONR · Grant · Not Funded James Foulds, Shimei Pan, Md Osman Gani
  • III: Small: Social Media-based Large Scale Personal Persuasion National Science Foundation · Grant · Not Funded Hamed Pirsiavash (Co-Principal), Shimei Pan (Principal)
  • NSF-CSIRO: Analyzing and Mitigating Sociolingustic AI-Bias (SLAB) in Natural Language Processing NSF · Grant · Not Funded Shimei Pan, James Foulds, Christine Mallinson
  • Video Storytelling with Generative Adversarial Networks Laboratory for Analytic Sciences · Grant · Not Funded James Foulds (Principal), Shimei Pan (Co-Principal), Edward Raff (Co-Principal), Hamed Pirsiavash (Co-Principal)
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