Yule Wang

yule-profile-avatar.jpg

756 W Peachtree St NW

Atlanta, GA 30308

School of CSE, Georgia Institute of Technology

Email: yulewang [at] gatech [dot] edu

I am a fourth-year Ph.D. student in the Machine Learning Program and the CSE Department at Georgia Tech (GaTech). My advisor is Prof. Anqi Wu. I obtained my Master’s and B.Eng.’s degree from Shanghai Jiao Tong University majoring in Software Engineering. I also spent time as a research intern at Meta and Alibaba.

Research Interests

My ML research focuses on deep generative models and time-series analysis, with their applications in computational neuroscience. Working with multivariate time-series data, I develop ML algorithms to infer semantically meaningful latent structures and dynamics through advanced generative modeling approaches (e.g., diffusion models, disentangled variational auto-encoders).

I am open to collaborate! 💡 Feel free to drop me an email if you are interested!

News

Aug 15, 2025 I am fortunate to work as a Research Scientist Intern at Meta Reality Labs, in New York City during the summer of 2025.
Apr 16, 2025 I have been selected as a finalist for the Neuro Next Graduate Research Award.
Oct 15, 2024 I received the NeurIPS 2024 Scholar Award. Looking forward to seeing you in Vancouver, Canada!

Selected Publications

  1. arXiv
    Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion
    Yule Wang, Joseph Yu, Chengrui Li, Weihan Li, and Anqi Wu
    arXiv preprint arXiv:2510.02182 (ICLR’26 Submission), 2025
  2. ICML
    Learning Time-Varying Multi-Region Communications via Scalable Markovian Gaussian Processes
    Weihan Li, Yule Wang, Chengrui Li, and Anqi Wu
    International Conference on Machine Learning Oral, 2025
  3. NeurIPS
    Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
    Yule Wang, Chengrui Li, Weihan Li, and Anqi Wu
    Advances in Neural Information Processing Systems, 2024
  4. NeurIPS
    Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models
    Yule Wang, Zijing Wu, Chengrui Li, and Anqi Wu
    Advances in Neural Information Processing Systems Spotlight, 2023