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Xingli Fang

Ph.D. Candidate in Comp. Sci.
NC State University
xfang23 (at) ncsu.edu


Short Bio

I am Xingli Fang (方星力 in Chinese), a Ph.D. candidate at North Carolina State University advised by Dr. Jung-Eun Kim. Prior to that, I got my Master Degree (Computer Engineering) from Syracuse University and Bachelor Degree (Software Engineering) from Northeastern University (China).

My current research lies at Trustworthy ML (a.k.a., Responsible AI) – with a special focus on building privacy-safe and efficient ML. My research interests include privacy, efficient AI, semi-/self- supervised learning, and generative models.

News

Internship Experience

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AT&T Labs [2025 Jun - 2025 Aug]

Research Intern (Sr Associate Student Intern Technical II)

Worked in AT&T Lab Internship (Advanced Degree) research program with a focus on AI foundation model for AT&T 5G Cellular network big data.

Education

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North Carolina State University

Department of Computer Science

Ph.D. in Computer Science, [2023 Spring-Ongoing]

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Syracuse University

Department of Electrical Eng. and Computer Sci.

M.S. in Computer Engineering, [2021 Fall - 2022 Winter]

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Northeastern University

Software College

B.Eng. in Software Engineering, [2017 Fall - 2021 Summer]

Publications [Google Scholar]

    Conference


  1. AIES 24
    Representation Magnitude has a Liability to Privacy Vulnerability
    Xingli Fang, Jung-Eun Kim
    7th AAAI Conference on AI, Ethics, and Society, 2024.
    PDF Code

  2. UAI 24
    Center-Based Relaxed Learning Against Membership Inference Attacks
    Xingli Fang, Jung-Eun Kim
    Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence, 2024.
    PDF Code Project Page

    3. Workshop


  3. WANT@NeurIPS
    Cooperative Learning for Cost-Adaptive Inference
    Xingli Fang, Richard Bradford, Jung-Eun Kim
    Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization, 2023.
    PDF Project Page

    4. Journal


  4. Multi-Step Real-Time Prediction of Hard-Rock TBM Penetration Rate Combining Temporal Convolutional Network and Squeeze-And-Excitation Block
    Long Li, Zaobao Liu, Xingli Fang, Wenbiao Qi
    Scientific Reports, 2024.
    PDF Project Page

  5. Realtime Prediction of Hard Rock TBM Advance Rate using Temporal Convolutional Network (TCN) With Tunnel Construction Big Data
    Zaobao Liu,Yongchen Wang, Long Li, Xingli Fang, Junze Wang
    Frontiers of Structural and Civil Engineering, 2022.
    PDF Project Page

  6. Hard-rock Tunnel Lithology Prediction with TBM Construction Big Data using A Global-Attention-Mechanism-Based LSTM Network
    Zaobao Liu,Long Li, Xingli Fang, Wenbiao Qi, Jimei Shen, Hongyuan Zhou, Yulong Zhang
    Automation in Construction, 2021.
    PDF Project Page

    7. Preprint


  7. ArXiv
    Trustworthy AI on Safety, Bias, and Privacy: A Survey
    Xingli Fang, Jianwei Li, Varun Mulchandani, Jung-Eun Kim
    ArXiv, 2025.
    PDF

Teaching

Services

Conferences, Serve as Program Committee

Conferences, Serve as Reviewer

Honors / Grants / Awards

  • [Oct 2024] AIES'24 Student Travel Award, 7th AAAI Conference on AI, Ethics, and Society
  • [Jul 2024] Academic Travel Grants, Department of Comp. Sci., NC State University
  • [May 2024] Scholarship, The Conference on Uncertainty in Artificial Intelligence (UAI) 2024
  • [Nov 2023] Academic Travel Grants, Department of Comp. Sci., NC State University
  • [Apr 2023] Summer Graduate Award (SGA), Department of Comp. Sci., NC State University
  • [May 2021] Graduate Student Grant, EECS, Syracuse University

    • Contact

    Address: 890 Oval Dr, Raleigh, NC 27606
    Email: xfang23 (at) ncsu.edu



    2025 Xingli Fang