About Me

I’m a PhD student in Machine Learning at University of Cambridge (Machine Learning Group, Computational and Biological Learning Lab) and Max Planck Institute for Intelligent Systems (Department of Empirical Inference), under the Cambridge-Tübingen PhD Fellowship in Machine Learning. My supervisors are José Miguel Hernández-Lobato, Bernhard Schölkopf, and Hong Ge.

I’m keen on basic research in machine learning and its scientific applications. My research interest lies at the intersection of deep learning and probabilistic methods. I’m exicted about developing efficient machine learning methods for robust prediction and realistic data generation.

Interests
  • Generative Modeling
  • Meta/Multi-Task Learning
  • Probabilistic Modeling
  • Sampling
  • Optimization
  • AI for Science
Education
  • PhD in Machine Learning

    University of Cambridge & Max Planck Institute for Intelligent Systems

  • MPhil in Machine Learning and Machine Intelligence, Distinction, 2021

    University of Cambridge

  • BSc (Hons) in Mathematics, First Class Honors, 2020

    University of Manchester

Experience

 
 
 
 
 
Research Intern - AI for Science
Mar 2024 – Present Haidian, Beijing, China
Molecular Dynamics and Machine Learning Force Field
 
 
 
 
 
Doctoral Fellow - Machine Learning
Oct 2021 – Present Cambridge, England, United Kingdom
Cambridge-Tübingen PhD Fellow in Machine Learning
 
 
 
 
 
Doctoral Fellow - Machine Learning
Oct 2021 – Present Tübingen, Baden-Württemberg, Germany
Cambridge-Tübingen PhD Fellow in Machine Learning
 
 
 
 
 
Research Intern - Optimization
Aug 2020 – Sep 2020 Remote
Federated Learning and Distributed Optimization
 
 
 
 
 
Research Engineer Intern - Deep Learning
Jun 2019 – Aug 2019 Kings Langley, England, United Kingdom
Efficient Deep Learning on Edge Devices

Awards

Cambridge-Tübingen PhD Fellowship in Machine Learning
The Royal Statistical Society Prize
International Mathematics Scholarship

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