Zhuan is a Ph.D. candidate in Physics at the University of Pittsburgh, mentored by Prof. Roger Mong. He specializes in scientific computing, data analysis, and machine learning, applying advanced statistical methods and computational techniques to complex theoretical and practical challenges.

Currently as a summer graduate intern at Los Alamos National Lab under the supervision of Dr. Andrey Lokhov, Zhuan focuses on enhancing modeling systems and optimizing large-scale sampling operations. At the University of Pittsburgh, he focuses on condensed matter theory, especially the topological phase of matter and its potential application to quantum computing. Utilizing various computational libraries, Zhuan performs in-depth simulations and data analyses to tackle intricate problems across diverse fields, including quantum error correction, quantum information, and superconducting devices.

Before joining UPitt, Zhuan studied physics at the University of Chinese Academy of Sciences, China (BSc). During his undergraduate study, he worked on low-rank approximation algorithms based on the tensor network under the supervisor of Prof. Pan Zhang, Institute of Theoretical Physics, Chinese Academy of Sciences.

With a robust background in theoretical physics and applied statistics, Zhuan is well-prepared to contribute to data science and machine learning projects, aiming to drive technological and industrial advancements through innovative approaches.

Download my CV.

Interests

- Statistical learning
- Scientific Computing
- Tensor network algorithm
- Machine Learning
- Quantum Computing

Education

PhD in Condensed Matter Physics, 2024

University of Pittsburgh, Pittsburgh, PA

BSc in Physics, 2019

University of Chinese Academy of Sciences, China

Visiting student, 2018

University of Bristol, UK

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I have been a Teaching Assistant at University of Pittsburgh for the following course:

**PHYS 0212 Introduction to laboratory physics**,*Fall 2019***PHYS 0212 Introduction to laboratory physics**,*Spring 2020,***PHYS 0111 Introduction to physics 2**,*Summer 2020***PHYS 0212 Introduction to laboratory physics**,*Spring 2021,***PHYS 0212 Introduction to laboratory physics**,*Spring 2022,*

I have given contributed talks on the following conferences:

2022

**APS March Meeting (Chicago)**- Contributed talk.
*Title: Detecting topological order from modular transformations of ground states on the torus.*

- Contributed talk.
2023

**APS March Meeting (Las Vegas)**- Contributed talk.
*Title: Estimating the reflected entropy from random matrices.*

- Contributed talk.
2024

**APS March Meeting (Minneapolis)**- Contributed talk.
*Title: Replica Topological Order and Error Correction.*

- Contributed talk.

- 2022 Thomas-Lain essay competition.
- 2023 Pittsburgh Quantum Institute Fellowship.

Summer student

Los Alamos National Lab

Explore new methods for a high-fidelity sampling using quantum annealers under the supervision of Dr. Andrew Lokhov.

PhD student

University of Pittsburgh

PhD in Physics. Study topological order and tensor network under the supervision of Prof. Roger Mong.

Visiting student

University of Bristol

Visiting student

Institute of Theoretical Physics, Chinese Academy of Sciences

Study low-rank approximation algorithms on tensor networks under the supervision of Prof. Pan Zhang.

BSc in Physics

University of Chinese Academy of Sciences