Ed Chen.
computational science & maths
01. About
Hello! I am a Mathematics PhD at the Courant Institute of Mathematical Sciences at NYU. My research interests surround developing high-order numerical methods and their applications modeling natural phenomena and engineering environments.
I studied mathematical engineering at Stanford during my MS, and mathematics from Georgia Tech and UC Berkeley in undergrad. In the past, I have been fortunate to intern with Mitsubishi Electric, NASA Supercomputing, Julia Computing, and various university labs. An abbreviated vita can be found here.
I have primarily worked in numerical mathematics, parallel programming, and data science.
Check out the source code for this website! Picture is via the archives of the Mathematisches Forschungsinstitut Oberwolfach.
02. Recent News
11.20.2025
Attended Oberwolfach Seminar 2548B: Time Parallel Time Integration
08.06.2025
Interned at Mitsubishi Electric in Sendai (via UCLA IPAM & Tohoku MathCCS)
06.20.2025
Attended UH Manoa Computational Summer Intensive
04.15.2023
Accepted NYU Courant PhD offer in Mathematics
04.15.2022
Accepted Stanford MS offer in ICME
03. Research
My research interests lie broadly in numerical PDEs, scientific computing, and large-scale data science. My recent work centers around
Shock Capturing: Inviscid shock regularization techniques towards efficient and scalable shock capturing techniques for hyperbolic conservation laws, and their applications to design optimization problems.
Parallel Sparse Solvers: Parallel and efficient algorithm design for fill-reducing column reordering heuristics used in fast direct solvers and various incomplete factorizaton preconditioners.
In the past, I have worked on various other adjacent topics, particularly surrogate modeling, heterogeneous architecture parallel programming, discrete event simulation, and trajectory optimization.
04. Education
2023-Now
New York University
PhD Mathematics
2022-2023
Stanford University
MS Computational and Mathematical Engineering
2020-2022
Georgia Tech
BS Mathematics
2018-2020
UC Berkeley
05. Work
2025-Present
Teaching Assistant, Grader, Department of Mathematics
2025
Mitsubishi Electric
Research Intern (UCLA/Tohoku GRIPS)
2022-2023
Course Assistant, Department of CS
2021-2022
Modeling and Simulation Intern, JuliaSim
2021-2022
Teaching Assistant, Department of CSE
Course Grader, Department of Mathematics
2020-2021
Research Associate, Computational Aerosciences
2019-2021
Course Reader, Department of Mathematics
Research Assistant, Department of EECS
2018-2019
University of Arizona
Research Assistant, Department of Bioengineering
07. Teaching
New York University
Sp 2026
Math-UA 185
Teaching Assistant, Probability and Statistics (x2)
Fa 2025
Math-UA 131
Teaching Assistant, Math for Economics I (x2)
Sp 2025
Math-GA 2020
Grader, Numerical Methods II *
Stanford University
Sp 2023
Course Assistant, Mining Massive Datasets * †
Wi 2023
Course Assistant, Data Visualization *
Au 2022
Course Assistant, Parallel Computing †
Georgia Institute of Technology
Sp 2022
Math 6321
Grader, Complex Analysis *
Sp 2022
Head Teaching Assistant, Graduate Data and Visual Analytics * †
Fa 2021
CSE 6242
Teaching Assistant, Data and Visual Analytics * †
UC Berkeley
Fa 2021
Math 121A
Grader, Mathematical Methods for Physical Sciences
Sp 2021
Grader, Mathematical Methods for Physical Sciences
Fa 2020
Grader, Introduction to Complex Analysis
* Graduate Course † 100+ Students
08. Contact
ed.chen [at] cims [dot] nyu [dot] edu
Website
edhschen [dot] info
Last Update
Sep 02, 2025