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Updated October 2026.

Education

Massachusetts Institute of Technology · September 2024–present
PhD in Computer Science, expected September 2029
Advisor: Jörn Dunkel, Professor of Mathematics

Master of Science (SM), earned en route to PhD · May 2026
Thesis: Algebra Discovery via Free Algebra Relations

Yale University · May 2023
BS Applied Mathematics; BS Chemistry

Research interests

I study how to infer interaction laws and governing dynamics from observations of biological and physical systems. I also develop mathematically interpretable representations of these systems using geometric algebra and geometric machine learning.

Selected research experience

Graduate Researcher, MIT

September 2024–present · Advisor: Jörn Dunkel

  • Investigating methods to infer interaction laws and governing dynamics of interacting systems, including animal behavior.
  • Developing interpretable representations of biological and physical systems using geometric algebra.
  • SM thesis: Developed a method to learn operator algebras from experimental data by constructing the ideal of relations from the null space of an experimental data matrix.

Post-baccalaureate Research Assistant, Yale

August 2023–August 2024 · Krishnaswamy Lab; advisor: Smita Krishnaswamy

  • Developed geometric deep learning methods for graph signals and high-dimensional biological data, including hypergraph wavelets for spatial transcriptomics.
  • Contributed to the mathematical development of DYMAG and implemented chaotic dynamics for graph message passing.

Sweeney Lab, Yale

September 2021–May 2023 · Advisor: Alison Sweeney

  • Used Monte Carlo simulations in C to study semiflexible polymers on cylindrical surfaces under confinement.
  • Developed image-processing algorithms to characterize polymer network topology in cryoEM images.

Technical skills

Programming: Python, C, MATLAB, R.
Tools: PyTorch, JAX, PyTorch Geometric, TensorFlow, Git, LaTeX.

Publications

DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms.
Bhaskar, D.*, Sun, X.*, Zhang, Y.*, Xu, C.*, Afrasiyabi, A., Viswanath, S., Fasina, O., Wolf, G., Perlmutter, M., and Krishnaswamy, S.
Topology, Algebra, and Geometry in Data Science (TAG-DS), 2025. Spotlight.
Proceedings of Machine Learning Research 321:236–268, 2026.

Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics.
Sun, X.*, Xu, C.*, Rocha, J. F., Liu, C., Hollander-Bodie, B., Goldman, L., DiStasio, M., Perlmutter, M., and Krishnaswamy, S.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.

Principal Curvatures Estimation with Applications to Single Cell Data.
Zhang, Y.*, Mezrag, L.*, Sun, X., Xu, C., Macdonald, K., Bhaskar, D., Krishnaswamy, S., Wolf, G., and Rieck, B.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.

BLIS-Net: Classifying and Analyzing Signals on Graphs.
Xu, C., Goldman, L., Guo, V., Hollander-Bodie, B., Trank-Greene, M., Adelstein, I., De Brouwer, E., Ying, R., Krishnaswamy, S., and Perlmutter, M.
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
Proceedings of Machine Learning Research 238:4537–4545.

*Equal contribution.

Teaching and mentoring

Tutor, Research Science Institute (RSI) · 2026
Mentored computational biology students on the research process, scientific writing, and presentations.

Undergraduate Mentor, MIT UROP · Fall 2024
Provided background instruction on graph neural networks for single-cell analysis through weekly meetings and instructional materials.

Teaching Assistant, Yale

  • Advanced Linear Algebra with Applications · Spring 2024
  • Probability and Statistics · Fall 2022
  • Deep Learning Theory and Applications · Spring 2022

Selected talks

“Why Do Plants Look Like That?” · April 2026
Simple Persons Applied Math Seminar (SPAMS), MIT

“Hyperedge Representations with Deep Hypergraph Wavelets: Applications to Spatial Transcriptomics” · June 2024
Graph Signal Processing Workshop, Delft, Netherlands

Service and leadership

  • Reviewer: NeurIPS (2024); Sampling Theory and Applications (2023).
  • Social Chair, MIT EECS Graduate Student Association · 2026–present
  • IT Chair, Edgerton Residence, MIT · April 2026–present
  • Mentor, MIT Graduate Application Assistance Program · 2024–present