Yucheng Xing

Biography

Ph.D. researcher at Stony Brook University with a dissertation successfully defended in May 2026, advised by Professor Xin Wang. Specialized in Efficient Generative AI (Diffusion Models) and Continuous-Time Modeling (Neural ODEs/SDEs). Expert in designing high-performance diffusion models and forecasting architectures with a focus on model compression and inference optimization. I received my M.S. in Electrical Engineering from Stony Brook University in 2021, also under the supervision of Professor Wang. Before that, I obtained my B.S. in Computer Science in 2017, from the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University.

News

• 05/2026 — Successfully defended my Ph.D. dissertation
• 09/2024 — Extended version of AGGDN is published in Intelligent and Converged Networks
• 08/2024 — One paper (∞-Net) on unsupervised online graph time-series denoising is accepted by ICONIP-2024
• 05/2024 — Passed oral preliminary examination
• 01/2024 — A book chapter on AI-enabled smart grid (co-authored) is published
• 08/2023 — One paper (AGGDN) on irregular graph time-series prediction is accepted by ICONIP-2023
• 07/2023 — One paper (HDG-ODE) on multi-person pose forecasting is accepted by ICCV-2023

Interests

• Computer Vision
• Adaptive Learning
• Time-Series Processing
• Generative Modeling

Education

• Ph.D. in Electrical Engineering, 2026
  Stony Brook University
• M.S. in Electrical Engineering, 2021
  Stony Brook University
• B.S. in Computer Science (IEEE Honor Class), 2017
  Shanghai Jiao Tong University