CV

Click here to download full CV (last updated: January 2024).

Education

Ph.D. in Mathematics, University of California, Los Angeles, 2025 (expected)
- Advisor: Deanna Needell
C.Phil. in Mathematics, University of California, Los Angeles, 2023
M.A. in Mathematics, University of California, Los Angeles, 2022
B.S. in Mathematics (Honors), Calvin University, 2020
B.A. in Chemistry, Calvin University, 2020

Preprints

Manifold Filter-Combine Networks

Chew, J.A., De Brouwer, E., Krishnaswamy, S., Needell, D., Perlmutter, M. Submitted for publication, 2023. [arxiv]

Curvature corrected tangent space-based approximation of manifold-valued data

Diepeveen, W., Chew, J.A., Needell, D. Submitted for publication, 2023. [arxiv]

Detecting and Mitigating Indirect Stereotypes in Word Embeddings

George, E., Chew, J.A., Needell, D. Submitted for publication, 2023. [arxiv]

Conference/Workshop Papers

Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis

Venkat, A., Chew, J.A., Rodriguez, F.C., Tape, C.J., Perlmutter, M., Krishnaswamy, S. Accepted to ICASSP 2024. [arxiv]

A Convergence Rate for Manifold Neural Networks

Chew, J.A., Perlmutter, M., Needell, D. Sampling Theory and Applications (in IEEE), 2023. [arxiv]

The Manifold Scattering Transform for High-Dimensional Point Cloud Data

Chew, J.A., Steach, H.R., Viswanath, S., Wu, H.-T., Hirn, M., Needell, D., Vesely, M.D., Krishnaswamy, S., Perlmutter, M. Topological, Algebraic and Geometric Learning Workshops 2022, volume 196, pages 67-78. PMLR, 2022. [arxiv]

Journal Papers

Geometric Scattering on Measure Spaces

Chew, J.A., Hirn, M., Krishnaswamy, S., Needell, D., Perlmutter, M., Steach, H.R., Viswanath, S., Wu, H.-T. Applied and Computational Harmonic Analysis, 2024. [arxiv]

Multi-scale Hybridized Topic Modeling: A Pipeline for Analyzing Unstructured Text Datasets using Topic Modeling

Cheng, K., Inzer, S., Leung, A., Shen, X., Perlmutter, M., Lindstrom, M., Chew, J.A., Presner, T., Needell, D. SIAM Undergraduate Research Online (SIURO), 2022. [arxiv]

Bootstrap methods for quantifying the uncertainty of binding constants in the hard modeling of spectrophotometric titration data

Kazmierczak, N.P., Chew, J.A., Vander Griend, D.A. Analytica Chimica Acta, 2022, 1227:339834.

Talks and Presentations

Uncovering Structure in High-Dimensional Data

February 16, 2023

Colloquium talk at Calvin University Mathematics Colloquium, Grand Rapids, MI

Geometric Scattering on Non-Euclidean Data

September 29, 2022

Conference talk at SIAM MDS 2022, San Diego, CA

NSF GRFP Workshop

August 12, 2022

Workshop at UCLA Department of Mathematics, Los Angeles, CA

Tension Induced Instabilities of Twisted Springs

July 25, 2019

Talk at Cornell University Undergraduate Research Forum, Ithaca, NY

Defining the Relationship: Computer-Driven Characterization of the Binding of Host and Guest Molecules

January 18, 2019

Poster at Joint Mathematics Meetings, Baltimore, MD

The Tie that Binds: Optimal Design of Equilibrium Spectrophotometric Titrations

November 10, 2018

Poster at West Michigan Regional Undergraduate Science Conference, Grand Rapids, MI

Characterizing the Grobner Bases of Generic Ideals

November 04, 2017