Jingyuan Chen

Ph.D. Student University of Illinois Urbana-Champaign

Research Space 5080, 614 E Daniel Street

Education

  • MS Applied Mathematics: Algorithms & Optimization - UIUC 2025 - 2026
  • Mathematics AB - UC Berkeley 2022 - 2025
  • Statistics AB - UC Berkeley 2022 - 2025

Research Interests

Network Clustering • Network Flows • Information Retrieval • Automated Deduction • Graphons • Random Graphs • High-Dimensional Statistics • Random Matrix Theory • Spectral Methods for Statistics • Data Science • Scientific Computing • Statistical Education
About

I am currently focused on large random combinatorial structures, clustering and flows algorithms on complex networks. I also have interests in financial risk, information retrival problems in automated deduction, and statistical education.

I am currently a graduate student instructor for IS 445 Data Viz taught by my adviser Professor Matt Turk.

I am one of the test organizers for the Intercollegiate Math Tournament (registration open!).

For those thinking about majoring in Statistics at Berkeley I have a guide.

Friends & Mentors

Professor Steve Evans, Professor Andrew Bray, Professor Andrés R. Vindas Meléndez, Professor Lisa Goldberg, Professor Khalilah Beal-Uribe, Professor Emeritus Peter Zvengrowski, Dr. Winston Yin, Professor Matthew Turk, Aayna, Manahil, Arnav, Sophie, Mark, Yilin, Yiming, Cindy

Somewhere UAE

Al Madam, Sharjah

Teaching Assistantships / Course Staff

IS 445: Data Visualization Graduate Student Instructor (Fall 2025)

MATH 113: Abstract Algebra Reader ( Summer 2025 )

MATH 105: Multivariate Real Analysis & Measure Theory Reader (Spring 2025)

STAT 2: Introduction to Statistics Study Center Group Tutor (Spring 2025)

MATH 53: Multivariate and Vector Calculus Study Center Group Tutor (Summer 2024)

STAT 20: Introduction to Statistics and Probability Study Center Group Tutor (Spring 2024)

STAT 2: Introduction to Statistics Study Center Group Tutor (Spring 2024)

DATA C8: Foundations of Data Science Academic Intern (Fall 2023)

Course Development

Department of Mathematics Student Researcher IV (Spring 2025)

Developing Linear Algebra Education Tools for MATH 56: Linear Algebra, Prototype (here). Funded by the "Interactive Tools for Learning Linear Algebra" Instructional Technology and Innovation Grant.

Department of Physics Course Developer (Spring 2024 - 2025)

Developer for Nobel laureate in Physics Saul Perlmutter's L&S 22: Sense & Sensibility & Science course's data science lab on bad science.

DSUS Modules Developer (Fall 2023)

Developed ECON 148: Data Science for Economists' Prophet forecasting lab and converted IEOR 120: Engineering Economics' homeworks into autogradable notebooks.

Current Research

UC Berkeley College of Letters & Science: Research Fellow

Researching sparse graphons previously advised by Professor Steven Evans (Math/Stat, Berkeley). Currently collaborating with Ph.D. candidate Siddhi Kanta Mishra (IEMS, UCF), and Professor Jialie "Jerry" Shen (CS, SGUL) on applications of graphons towards information flow problems in neural networks.

Co-author

Co-authoring a paper on Risk Networks of Reinsurance with Elaine Shen Ph.D. Candidate at Berkeley Economics and Thomas Rutter Ph.D. Candidate at Stanford Economics.

Researcher at UC Berkeley Consortium for Data Analytics in Risk

Investigating high-dimensional covariance estimation and factor counting under Professor Lisa R Goldberg.

Past Research Assistantships

RA for Professor Diag Davenport at the Goldman School of Public Policy. Mathematically formalizing empirical work on the pivotal voter effect.

RA for Professor Luisa Cefala & Afras Sial Ph.D. Candidate at Berkeley Economics. Creating simulations and statistical estimations on earned wage accessed technology.

RA for Professor Ofer Eldar at Berkeley Law. Automating the extraction of net operating loss numbers from unstructured 10-K files.

Previous Work

Officer at Berkeley's Mathematics Undergraduate Student Association

Summer Camp Instructor at Berkeley's department of Industrial Engineering and Operations Research

Intern Statistician at Gilead Sciences

Summer Analyst ING Group N.V. Corporate Banking

Marketing & Recruitment Director at Berkeley Math Tournament

Finance Lead & Avionics Engineer at Space Technologies and Rocketry @ Berkeley

Education

I am currently a PhD student at UIUC under Professor Matthew Turk.

University of Illinois Urbana-Champaign | 2025 - 2030

School of Information Sciences: PhD Information Sciences, Statistics Minor

College of Liberal Arts & Sciences: MS Applied Mathematics: Algorithms & Optimization

University of California, Berkeley | 2022 - 2025

College of Letters & Science: Mathematics AB Honours

College of Computing, Data Science & Society: Statistics AB Honours

Selected Coursework

Here's some selected coursework I've taken throughout the years.

Graduate Division Coursework (Illinois):

MATH 595: Representation-theoretic Methods in Quantum Information Theory - Felix Leditzky Ph.D.
STAT 578: Spectral Methods, Network Analysis & Nonconvex Optimization - Joshua Agterberg Ph.D.
CS 576: Computer-aided Methods for Formal Deduction - Talia Ringer Ph.D.
IS 509: History and Foundations of Information Science - Michael Twidale Ph.D.

Graduate Division Coursework (Berkeley):

ECON 217: Risk - Lisa R Goldberg Ph.D.
STAT 244: High Powered Statistical Computing in Julia - Chris Paciorek Ph.D.
STAT C205A: Measure Theoretic Probability - Steven N Evans Ph.D.
STAT 210A: Theoretical Statistics - Will Fithian Ph.D.
MATH 250A: Groups, Rings and Fields - Richard Borcherds Ph.D.
MATH C223: Eigenvalues of Random Matrices - Vadim Gorin Ph.D.
MATH 221: Advanced Matrix Computations - Jim Demmel Ph.D.

Selected Upper Division Coursework:

ENGIN 183: Engineering Leadership - Carrie Requist MBA
ECON 157: Health Economics - Ryan Edwards Ph.D.
ECON 141: Mathematical Econometrics - Demian Pouzo Ph.D.
ECON C110: Game Theory - Tyler Maxey Ph.D.
INFO 190: Skepticism in a Data-Driven World - Jevin West Ph.D.
COMPSCI 169A: Software Engineering - Armando Fox Ph.D.
STAT H195: Honors Thesis (History of STAT 2 & Intro Stats Courses) - Advised by Andrew Bray Ph.D.
STAT 165: Forecasting - Will Fithian Ph.D.
STAT 158: Experimental Design - Andrew Bray Ph.D.
STAT 134: Concepts of Probability - Adam Lucas Ph.D.
MATH 130: Groups and Geometry: Matroid Theory - Andres Vindas-Melendez Ph.D.
MATH 128A: Numerical Analysis - Per-Olof Persson Ph.D.
MATH 113: Abstract Algebra - Dan-Virgil Voiculescu Ph.D.
MATH 110: Abstract Linear Algebra - Olga Holtz Ph.D.
MATH 105: Multivariate Analysis & Measure Theory - Khalilah Beal Ph.D.
MATH 104: Real Analysis - Khalilah Beal Ph.D.

Lower Division Coursework:

COMPSCI 61B: Data Structures (Java) - Justin Yokota M.S.
COMPSCI 61A: Program Structures (Python, Lisp) - Satish Rao Ph.D.
DATA C8: Data Science Foundations - Joseph Gonzalez Ph.D.
STAT 33B: Advanced R Programming - Gaston Sanchez Ph.D.
MATH 55: Discrete Mathematics - Sylvie Corteel Ph.D.

Prior Education

I did my high school at Dubai American Academy, junior high at Webber Academy (Calgary), and primary years at Jakarta International School.