cv

Contact Information

Name Ke Liao
Location New Haven, CT
Website https://nickirk.github.io/

Professional Summary

Postdoctoral researcher building GPU-accelerated machine learning systems for scientific discovery. I develop high-performance algorithms in JAX that combine deep learning with quantum many-body physics — neural quantum states, transcorrelation, and quantum embedding — to push what is computationally tractable in ab initio simulation of strongly correlated electrons.

Experience

  • 2025 - Present

    Postdoctoral Associate
    Yale University
    Leading development of PyTC, a JAX-based GPU-accelerated framework for transcorrelated electronic structure. Building neural quantum state methods and quantum embedding workflows for strongly correlated materials.
    • JAX, GPU acceleration, Neural Quantum States, Quantum Embedding, Machine Learning, Scientific Computing
  • 2025 - 2025

    Visiting Postdoctoral Researcher
    Max Planck Institute for Solid State Research, Stuttgart, Germany
    • Density Fitting, Transcorrelation
  • 2023 - 2024

    Teaching Assistant
    Ludwig-Maximilians-Universität München, Munich, Germany
    Teaching assistant to Quantum Information Theory course.
    • Quantum Information Theory, Quantum Computing
  • 2023 - 2024

    Postdoctoral Researcher
    Ludwig-Maximilians-Universität München, Munich, Germany
    Combining quantum information theory and quantum chemistry into a general orbital optimization algorithm that compactifies the quantum state representation.
    • Quantum Information Theory, Orbital Optimization, Tailored Coupled Cluster, Quantum Chemistry
  • 2022 - 2023

    Postdoctoral Researcher
    California Institute of Technology, Pasadena, USA
    Developed the transcorrelated densitry matrix renormalization group (TC-DMRG) which solves non-Hermitian Hamiltonians for ground and excited states. Implemented the canonical transformation theory and transcorrelated equation-of-motion coupled cluster singles and doubles.
    • TC-DMRG, Canonical Transformation, TC-EOM-CCSD
  • 2021 - 2022

    Postdoctoral Researcher part-time 80%
    Max Planck Institute for Solid State Research, Stuttgart, Germany
    Implemented the transcorrelated integrals for periodic solids in TCHInt library.
    • TC, periodic systems, TCHInt
  • 2021 - 2022

    External Scientific Consultant part-time 20% (remote)
    ByteDance, Beijing, China
    Worked at the intersection of quantum chemistry and machine learning. Evaluated and scoped industry ML research projects applying deep learning to quantum chemical problems; advised on algorithmic and methodological choices.
    • Machine Learning
    • Deep Learning
    • AI for Science
    • Quantum Chemistry
  • -

    Peer Reviewer
    Academic Journals
    Reviewer for Physical Review X (PRX), Quantum, and Physical Review B (PRB)

Education

  • 2017 - 2021

    Stuttgart, Germany

    PhD
    International Max Planck Research School for Condensed Matter Science
    Quantum Chemistry
  • 2015 - 2017

    Stuttgart, Germany

    Master
    International Max Planck Research School for Condensed Matter Science
    Physics
  • 2014 - 2015

    London, UK

    Exchange Student
    King's College London
    Physics
  • 2011 - 2015

    Wuhan, China

    Bachelor
    Wuhan University
    Physics

Skills

Machine Learning & AI: JAX, PyTorch, Deep Learning, Neural Quantum States, Scientific Machine Learning, GPU Computing
Scientific Computing: HPC, Numerical Methods, Python, C++, Fortran, NumPy, MPI, CUDA
Quantum Many-Body Methods: Coupled Cluster, DMRG, Transcorrelation, Quantum Embedding, Electronic Structure

Languages

Chinese : Native speaker
English : Advanced
German : Intermediate