Pengpeng Xiao

Pengpeng Xiao

Professional Summary

About Me

Hi! 😸 I’m Pengpeng Xiao (肖芃芃), a first-year PhD student in Physics at Yale University. I’m advised by Dr. Lu Lu in the Department of Statictics and Data Science. I’m honored to be supported by Gruber Science Fellowship at Yale.

My research interests lie in Scientific Machine learning (SciML), AI for Partial Differential Equations and AI for Science. I’m particularly interested in applying machine learning to PDE systems.

Education

PhD in Physics

Yale University

BSc in Physics

Fudan University

Interests

Scientific Machine Learning AI for PDEs Generative Model
🔬 My Research

My research journey began in high-energy phenomenology, where I explored fundamental physics and learned so much about the smallest scales of the universe. Over time, my interests expanded to the interplay between physics and AI, including the theoretical foundations of deep learning and quantum machine learning. Currently, I am also fascinated by the intersection of generative AI and PDEs, exploring how these techniques can enhance scientific computing and discovery.

I’m always open to collaborations! Feel free to reach out via email (p.xiao@yale.edu) or WeChat (luuuuuhan777) 😃

What’s New?

[Nov 1, 2025] 🎤 We organized a minisymposium Recent advances in quantum machine learning in SIAM NNP, where I presented a talk/poster on our Quantum DeepONet.

[May 9, 2025] 🎤 Our paper was presented as a poster in Envision AI at Yale Symposium.

[Feb 28, 2025] 🎤 I presented our Quantum DeepONet at the CRUNCH Seminar.

[Nov 28, 2024] 📄 Our paper LD-EnSF is now on arXiv!

[Oct 23, 2024] 🎤 I presented a poster on Quantum DeepONet at SIAM MDS in Atlanta.

[Oct 16, 2024] 🎤 I gave a talk on LD-EnSF at ROM+ML4LES+ at Emory.

[Sep 24, 2024] 📄 My first paper Quantum DeepONet is now on arXiv!

Recent Publications
LD-EnSF: Synergizing Latent Dynamics with Ensemble Score Filters for Fast Data Assimilation with Sparse Observations featured image
Latent Dynamics

LD-EnSF: Synergizing Latent Dynamics with Ensemble Score Filters for Fast Data Assimilation with Sparse Observations

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Quantum DeepONet: Neural operators accelerated by quantum computing featured image
Quantum Machine Learning

Quantum DeepONet: Neural operators accelerated by quantum computing

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Recent Talks
Quantum DeepONet featured image

Quantum DeepONet

Implementation, Applications, and Challenges in PDE Solving.

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Experience

  1. Research Intern

    Bosch
    • Working on AI for PDE research

  2. Visiting Student

    Georgia Institute of Technology
    • Working with Prof. Peng Chen on Latent Dynamics Ensemble Score Filter

  3. Visiting Student

    Yale University
    • Working with Prof. Lu Lu on Quantum DeepONet

  4. Visiting Student

    University of Utah
    • Working with Prof. Zhengkang Zhang on the Effective Field Theory of Deep Neural Network

Education

  1. PhD in Physics

    Yale University
    Advisor: Dr. Lu Lu and Dr. Daisuke Nagai

  2. BSc in Physics

    Fudan University

    Advisor: Dr. Jiayin Gu

    Courses included:

    • Quantum Field Theory, Particle Physics
    • Classical Mechanics, Quantum Mechanics, Electrodynamics, Thermodynamics
Skills & Hobbies
Hobbies
Hiking
Photography
Cats