National Taiwan University

Computational Quantum Matter

Ying-Jer Kao
yingjerkao.gitlab.io

Research Field

Physics

Introduction

I am a condensed matter theorist focusing on developing numerical algorithms to understand  strongly-correlated many-body systems.

Our research interests involve strongly-correlated many-body systems, with a focus on emergent phenomena, exotic phases, and phase transitions.

We aim to understand the physics of materials through microscopic models using computational methods as our major theoretical tools. 
Our work has employed Monte Carlo simulations, and Tensor Network related methods to explore the physics of classical and quantum magnetic materials, cold atoms in optical lattices, bosonic fluids and low-dimensional systems.

We are also interested in working at the interface of physics and computer science to develop efficient algorithms for simulating quantum mechanical systems on classical computers, including tensor network algorithms, machine learning, and how the ideas from physics can be applied in computer science.



 


Research Topics
  1. Tensor Network States: Algorithms and Applications
  2. Interplay between Machine Learning and Physics
  3. Quantum Frustrated Magnets
  4. Quantum simulation of Many-body Physics

Honor
  • 2018 QuantEmX Scientist Exchange Award (sponsored by ICAM)
  • 2011 Ta-You Wu Memorial Award, National Science Council (吳大猷先生紀念獎)
  • 2010 Research Award for Junior Research Investigators, Academia Sinica ( 中央研究院年輕學者研究著作獎)
  • 2009 Young Theorist Award, National Center of Theoretical Sciences (國家理論科學研究中心年輕理論學者獎)
  • 2008 Young Investigator Merit Award, National Science Council (國家科學委員會傑出學者養成計畫)



 


Educational Background

Ph. D., University of Chicago, 2001

Positions

Professor, Department of Physics, National Taiwan University

Associate Professor, Department of Physics, National Taiwan University

Assistant Professor, Department of Physics, National Taiwan University

Postdoctoral Associate, University of Toronto

Postdoctoral Associate, University of Waterloo



 


2 Vacancies

Job Description

Specific Tasks

  • Development of machine learning models
  • Running the experiments
  • Performing  analysis and summarizing results

Preferred Intern Education Level

Bachelor/ Master's Level

Skill sets or Qualities

Experiences in programming and   machine learning frameworks such as Pytorch is preferred.