Jingyuan Chen

I am a mathematics and statistics student studying the theory and applications of large random combinatorial structures. Currently, I am interested in graphical models for problems in financial risk, behavioral decision making and neural networks.

I am currently TA'ing IS 445 Data Viz with Professor Turk

I am hosting a LaTeX Workshop at UIUC

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

Teaching Assistantships / Course Staff

IS 445: Data Visualization Teaching Assistant (Fall 2025)

MATH 113: Abstract Algebra Reader (Summer 2025)

MATH 104: Real Analysis Reader (Summer 2025)

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

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

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

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

STAT 2: Introduction to Statistics 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. 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

DSUS Modules Developer (Fall 2023)

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

Ongoing Research @ Berkeley

College of Letters & Science: Research Fellow

Researching sparse graphons with Professor Steven Evans

Co-author

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

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 Luisa Cefala Ph.D. & 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

Mathematics Undergraduate Student Association @ Berkeley Officer

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 California, Berkeley | 2022 - 2025

College of Letters & Science: Mathematics A.B. w/ Honours

College of Computing, Data Science, and Society: Statistics A.B. w/ 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 Ph.D.
STAT 578: Spectral Methods, Network Analysis & Nonconvex Optimization - Joshua Agterberg Ph.D.
CS 576: Computer-aided Methods for Formal Deduction - Felix Leditzky 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 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.