profile image

Shengyu Chen

Ph.D. Candidate at University of Pittsburgh

About Me

Hi, my name is Shengyu Chen (Kevin). I am a final year Ph.D. candidate at the University of Pittsburgh, advised by Dr. Xiaowei Jia. My research interests lie in spatio-temporal data mining, generative modeling, AI for science, foundation model and LLMs. Several of my works have been accepted by prominent conferences such as KDD, CIKM and scientific journal such as TIST, Frontier in Genetic. To gain a more comprehensive understanding of my background, you can visit my Curriculum Vitae.

I am on the 2024-2025 academic job market for a tenure-track faculty position and the industry job market for a research scientist position. Please kindly contact me if there is a good fit.

Recent Publications

For the full publication list please refer to Google Scholar or Curriculum Vitae

Shengyu Chen, Shihang Feng*, Yao Huang, Zhou Lei, Xiaowei Jia, Youzuo Lin, Estaben Rougier, "HOSSnet: an Efficient Physics-Guided Neural Network for Simulating Crack Propagation.", Computational Materials Science, 2024.

Shengyu Chen, Shihang Feng, Yi Luo, Xiaowei Jia, Youzuo Lin, "BrainPuzzle: A New Data-Driven Method for Ultrasound Brain Imaging.", SPIE. Medical Imaging, 2024.

Shengyu Chen, Nasrin Kalanat, Simon Topp, Jeffery Sadler, Yiqun Xie, Zhe Jiang, Xiaowei Jia, "Meta-Transfer-Learning for Time Series Data with Extreme Events: An Application to Water Temperature Prediction.", Conference on Information and Knowledge Management (CIKM), 2023.

Shengyu Chen, Tianshu Bao, Peyman Givi, Can Zheng, Xiaowei Jia, "Reconstruction of Turbulent Flows Using Physics-Guided Spatio-Temporal Dynamics.", ACM Transactions on Intelligent Systems and Technology (TIST), 2023.

(Best Paper Award) Shengyu Chen, Yiqun Xie, Xiang Li, Xu Liang, Xiaowei Jia, "Physics-Guided Meta-Learning Method in Baseflow Prediction over Large Regions.", In Proceedings of the 2023 SIAM International Conference on Data Mining (SDM), 2023.

Shengyu Chen, Nasrin Kalanat, Yiqun Xie, Sheng Li, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, Jordan Read, Xiaowei Jia, "Physics-Guided Machine Learning from Simulated Data with Different Physical Parameters.", Knowledge and Information Systems (KIS),~2023.

Shengyu Chen, Jacob A. Zwart, and Xiaowei Jia, "Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks.", In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.

Bao, Tianshu*, Shengyu Chen*, Taylor T. Johnson, Peyman Givi, Shervin Sammak, and Xiaowei Jia, "Physics Guided Neural Networks for Spatio-temporal Super-resolution of Turbulent Flows.", In The 38th Conference on Uncertainty in Artificial Intelligence (UAI). 2022.

Research and Industry Experience

Research Scientist Intern - NEC Laboratory America (May 2024 - Present)

● Design and apply a new multi cutomized agent framework to address the challenge of user coordination in the supply chain.

Research Scientist Intern - Nokia Bell Laboratory (Jan 2024 - May 2024)

● Design and apply new machine learning techniques to address the challenges for causal discovery and root cause analysis.

Ph.D. Student Researcher - Los Alamos National Laboratory (May 2022 - Dec 2023)

● Design and apply new machine learning models augmented with physics knowledge to address material science challenges, such as microcrack propagation, as well as medical imaging problems, including brain imaging.