Pengfei Hu

Department of Computer Science, Stevens Institute of Technology

prof_pic.jpg

Gateway South 433

1 Castle Point Terrace, Hoboken, NJ 07030

My name is Pengfei Hu. I’m a 3rd year Ph.D. student in Department of Computer Science at Stevens Institute of Technology, co-advised by Prof. Yue Ning and Prof. Ping Wang. Before that, I obtained my master’s degree from the Viterbi School of Engineering, University of Southern California in 2023, where I worked with Prof. Sze-chuan Suen.

My current research concentrates on predictive healthcare on electronic health records (EHR), with a specific focus on augmented (e.g. knowledge-guided and retrieval augmented) language models and their robustness under domain shifts. I have also worked on graph neural networks and llm agents.

Feel free to drop me an email (phu9 at stevens dot edu) if you have any questions about my research, or want to discuss about potential collaborations.

I am looking for internship/fulltime industrial opportunities, starting from Summer 2026. Feel free to reach out if there is a good fit!

Educations

Stevens Institute of Technology (2023 - Present)
Ph.D. in Computer Science
GPA: 3.95/4.00
Research Focus: EHR modeling, Clinical NLP, Large Language Models.
Advisor: Prof. Yue Ning & Prof. Ping Wang

University of Southern California (2021 - 2023)
M.S. in Industrial System Engineering
GPA: 4.00/4.00
Research Focus: Anomaly Detection by Wearable Sensor Devices.
Advisor: Prof. Sze-chuan Suen

Industrial Experience

Oak Ridge National Laboratory (May 2025- Aug. 2025)
Graduate Research Intern, Computational Sciences and Engineering Division
Topic: Reservoir Inflow Forecasting.
Mentor: Fan Ming

Alibaba Group (Mar. 2021 - Jul 2021)
Data Analyst Intern, Cainiao Network
Mentor: Hao Lin

Tencent (Apr. 2020 - Aug. 2020)
Product Analyst Intern, Tencent Music Entertainment Group (TME)
Mentor: Hongmin Liao

PricewaterhouseCoopers (Jan. 2019 - Mar. 2019)
Actuarial Assurance Intern
Manager: Congyan Liu


News

Nov 17, 2025 My intern paper AdaTrip and HydroDCM are accepted by the ICDM 2025 DMESS and the AAAI 2026 AI4ES (Oral) workshops. Extended versions are underreviewed by journals.
Aug 20, 2025 Our paper II-KEA is accepted by EMNLP 2025 Findings!
May 19, 2025 I will be joining the Oak Ridge National Lab as a summer graduate research intern.
Oct 10, 2024 I passed my oral qualification exam.
May 15, 2024 I passed my written qualification exam.

Selected Publications

  1. arXiv
    Bridging Stepwise Lab-Informed Pretraining and Knowledge-Guided Learning for Diagnostic Reasoning
    Pengfei Hu, Chang Lu, Fei Wang, and 1 more author
    arXiv preprint arXiv:2410.19955, 2024
    HTML
  2. arXiv
    UdonCare: Hierarchy Pruning for Unseen Domain Discovery in Predictive Healthcare
    Pengfei Hu, Xiaoxue Han, Fei Wang, and 1 more author
    arXiv preprint arXiv:2506.06977, 2025
    HTML
  3. AAAI 2026 AI4S
    Hydrodynamic DCM: A Physics-Informed Deep Learning Framework for Reservoir System Identification
    Pengfei Hu, Ming Fan, Xiaoxue Han, and 3 more authors
    AAAI 2026 AI for Environmental Sciences Workshop (Oral), 2025
    PDF
  4. ICDM 2025 DMESS
    Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction
    Pengfei Hu, Ming Fan, Xiaoxue Han, and 5 more authors
    ICDM 2025 workshop on Data Mining in Earth System Science, 2025
    HTML
  5. EMNLP 2025 Findings
    No Black Boxes: Interpretable and Interactable Predictive Healthcare with Knowledge-Enhanced Agentic Causal Discovery
    Xiaoxue Han, Pengfei Hu, Jun-En Ding, and 3 more authors
    In Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
    HTML