Feng Ye

Feng Ye

Clemson University

👨🏻‍🎓 About Me

I am a tenure-track Assistant Professor in the Department of Industrial Engineering at Clemson University . Before joining Clemson, I received my Ph.D. in Industrial and Systems Engineering in 2025 and my M.Sc. in Statistics in 2023 from Rutgers University–New Brunswick .

My research focuses on AI/ML and statistical modeling for scientific and engineering systems. I develop methods that learn from data while incorporating domain knowledge and governing principles, with applications in weather, energy, and industrial applications.

Research interest:

  • Scientific Machine Learning
  • Spatio-temporal Modeling
  • Probabilistic Forecasting
  • Physics-guided Generative AI
  • Statistical Deep Learning
  • Forecast-informed Decision Making

🏆 Honors and Awards

📝 Publications

Journal Papers

  1. S.-T. Yang, F. Ye, X. Lu, D. Lin, and B. C. Martinez, “Physics-Guided Flow Matching: A Generative AI Framework for Global Total Electron Content Forecasting”, arXiv preprint, arXiv:2610.37159, 2026.
  2. F. Ye, X. Zhang, M. L. Stein, and A. A. Ezzat, “DeepMIDE: A Multi-Output Spatio-Temporal Method for Ultra-Scale Offshore Wind Energy Forecasting”, Technometrics, vol. 68, no. 3, pp. 452–468, 2026.
    • First Place, 2024 IISE Annual Meeting QCRE Track Best Student Poster Award
  3. M. C. Sahin, F. Ye, A. A. Ezzat, O. A. Kilic, and M. Yildirim, “Accessibility-Aware Stochastic Optimization of Maintenance Scheduling and Vessel Logistics for Offshore Wind Farms”, IEEE Transactions on Reliability, pp. 1–14, 2026.
  4. K. B. Walid, F. Ye, J. Ji, A. A. Ezzat, T. Miles, and Y. Jiang, “Economic and Reliability Value of Improved Offshore Wind Forecasting in Bulk Power Grid Operation: A Case Study of the New York Power Grid”, IEEE Access, vol. 14, pp. 148337–148357, 2026.
  5. J. Ji, F. Ye, T. Miles, and A. A. Ezzat, “A Horizon-Dependent Ensemble Method for Probabilistic Forecasting in Offshore Wind Farms”, INFORMS Journal on Data Science, accepted.
  6. C. Petersen, F. Ye, J. Ji, J. Kohut, A. A. Ezzat, D. Saginaw, A. Montanti, and J. Cammarota, “Accessibility and Serviceability Assessment to Inform Offshore Wind Energy Development and Operations off the US East Coast”, Wind Energy, vol. 29, no. 7, e70131, 2026.
  7. C. Petersen, J. Ji, F. Ye, A. A. Ezzat, J. Kohut, D. Saginaw, A. Montanti, and J. Cammarota, “Data-Driven Probabilistic Simulation of Vessel Operations to Support the Blue Economy”, Ocean Engineering, vol. 354, 124818, 2026.
  8. F. Ye, T. Miles, and A. A. Ezzat, “Improved Spatio-Temporal Offshore Wind Forecasting with Coastal Upwelling Information”, Applied Energy, vol. 380, 125010, 2025.
  9. F. Ye, J. Brodie, T. Miles, and A. A. Ezzat, “AIRU-WRF: A Physics-Guided Spatio-Temporal Wind Forecasting Model and Its Application to the U.S. Mid-Atlantic Offshore Wind Energy Areas”, Renewable Energy, vol. 223, 119934, 2024.
    • First Place, 2023 IISE Annual Meeting Energy Systems Track Best Paper Award
    • First Place, 2022 INFORMS Annual Meeting Sustainability Cluster Best Student Paper Award
  10. F. Ye and A. A. Ezzat, “Icing Detection and Prediction for Wind Turbines Using Multivariate Sensor Data and Machine Learning”, Renewable Energy, vol. 231, 120879, 2024.
  11. Z. Xia, F. Ye, M. Dai, and Z. Zhang, “Real-Time Fault Detection and Process Control Based on Multi-Channel Sensor Data Fusion”, The International Journal of Advanced Manufacturing Technology, vol. 115, no. 3, pp. 795–806, 2021.
  12. F. Ye, Y. Guo, Z. Xia, Z. Zhang, and Y. Zhou, “Feature Extraction and Process Monitoring of Multi-Channel Data in a Forging Process via Sensor Fusion”, International Journal of Computer Integrated Manufacturing, vol. 34, no. 1, pp. 95–109, 2021.
  13. Y. Guo, F. Ye, Y. Zhou, and Z. Zhang, “Fault Diagnosis of Multi-Channel Data in a Forging Process Using the Linear Support Higher-Order Tensor Machine”, International Journal of Computer Integrated Manufacturing, vol. 33, no. 8, pp. 810–822, 2020.
  14. F. Ye, Z. Zhang, Z. Xia, Y. Zhou, and H. Zhang, “Monitoring and Diagnosis of Multi-Channel Profile Data Based on Uncorrelated Multilinear Discriminant Analysis”, The International Journal of Advanced Manufacturing Technology, vol. 103, no. 9, pp. 4659–4669, 2019.

Conference Papers

  1. F. Ye and A. A. Ezzat, “An Integro-Difference Equation Model for Spatio-Temporal Offshore Wind Forecasting”, 2024 IEEE Power & Energy Society General Meeting (PESGM) Proceedings, pp. 1–5, 2024.

  2. F. Ye, J. Brodie, T. Miles, and A. A. Ezzat, “Ultra-Short-Term Probabilistic Wind Forecasting: Can Numerical Weather Predictions Help?”, 2023 IEEE Power & Energy Society General Meeting (PESGM) Proceedings, pp. 1–5, 2023.

Book Chapters

  1. F. Ye, T. Miles, and A. A. Ezzat, “Offshore Wind Energy Prediction Using Machine Learning with Multi-Resolution Inputs”, in Multimodal and Tensor Data Analytics for Industrial Systems Improvement, edited by N. Gaw, M. Reisi, and P. Pardalos, Cham: Springer International Publishing, pp. 167–183, 2024. (Invited chapter.)

Patents

  1. A. A. Ezzat, F. Ye, J. F. Brodie, and T. Miles, “Techniques to Provide Improved Wind Input for Operating Offshore Wind Turbines” (U.S. Patent No. 12,729,664, 2026).
  2. Z. Zhang, F. Ye, C. Zhen, and M. Dai, “Remote Data Acquisition and Analysis for Process Diagnosis in the Production Line” (Chinese Patent No. CN109086999B, 2021).

👨🏻‍🏫 Teaching

  • Instructor

    • @ Clemson
      • IE 4910/6910: Engineering Data Analytics, Spring 2026
      • IE 3610: Industrial Applications of Probability and Statistics II, Fall 2025/2026
    • @ Rutgers
      • 440 EOF Matlab Computer Programming, Summer 2022/2023

  • Teaching Assistant 01/2022 - 05/2022

    • 14:540:343: Engineering Economics

    • 14:540:462: Facilities Layout and Materials Handling

📚 Professional Service and Membership

  • Session Chair/Organizer:

    • “Modern Experimental Design”, ASA/IMS SRC, Clemson, SC, May 2026
    • “JQT Invited Session”, ASA/IMS SRC, Clemson, SC, May 2026
    • “Predictive Analytics for Wind Power Generation”, IISE, Montreal, Canada, May 2024
    • “Unique Directions in Energy Research”, IISE, Montreal, Canada, May 2024
    • “Forecasting and Data Science for Renewable Energy”, INFORMS, Indianapolis, IN, Oct. 2022

  • Contributed Program Committee: ASA/IMS Spring Research Conference 2026

  • Journal Reviewer for:

    Technometrics, IISE Transactions, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Sustainable Energy, Applied Energy, INFORMS Journal on Data Science, Journal of Quality Technology, International Journal of Forecasting, JGR: Machine Learning and Computation, Energy, Journal of Intelligent Manufacturing, Wind Energy Science, IEEE Open Access Journal of Power and Energy

  • Conference Reviewer for:

    • IEEE International Conference on Automation Science and Engineering (CASE) (2026)
    • IISE DAIS Best Track Paper Competition (2026)
    • ASA SPES + Q&P Student Paper Competition (2026)
    • INFORMS Data Mining Best Paper Competition (2026)
    • INFORMS QSR Best Student Paper Competition (2025, 2026)
    • INFORMS QSR Best Paper Competition (2025, 2026)
    • INFORMS Workshop on Data Mining and Decision Analytics (2026)

  • Vice President: Rutgers INFORMS Student Chapter (Cum Laude Award) 10/2022 - 06/2025

    Volleyball game between ISE faculty & students

    Joint seminar with Lehigh INFORMS Student Chapter

    Cum Laude Award from INFORMS

  • Memberships:

    • Institute of Industrial and Systems Engineers (IISE)
    • Institute for Operations Research and the Management Sciences (INFORMS)
    • Institute of Electrical and Electronics Engineers (IEEE)

🏃🏻 Personal

Outside research, I am all about sports and outdoor adventures! You’ll often find me running marathons,trails and mountains, climbing rocks, or hiking. 🏃🏻🧗🏻‍♂️🚀🏔️🔥

Jersey City Half Marathon -- 1:28