Mentoring

I have been a mentor for six different programs

1. REU via undergraduate Research Fellowships at Boston College 2025. I mentored a project on constrianted transformer. 

   • Geometry-Preserving Neural Architectures on Manifolds with Boundary. 2026
     Karthik Elamvazhuthi, Shiba Biswal, Kian Rosenblum, Arushi Katyal, Tianli Qu, Grady Ma, Rishi Sonthalia
     [Preprint]

2. London Geometry and Machine Learning at Imperial College London 2024 - I mentored a project on using geometry to design graph neural networks. 

3. Summer Geometry Institute at MIT 2023 - I mentored a project combining geometry and optimization. I also mentored four undergraduate students and one graduate student. 

4. Michigan Research Experience for Graduate Students at Michigan 2022 - I mentored a project on random matrix theory and generalization error for denoising. Here, I mentored four graduate students. With two of the students, over the next year, we wrote a paper that was published in TMLR. 

   • Generalization Error without Independence: Denoising, Linear Regression, and Transfer Learning. Transactions of Machine Learning Research. 2024
     Chinmaya Kausik, Kashvi Srivastava, and  Rishi Sonthalia
     [Code][Published Version]

5. Computation Applied Math REU at UCLA 2022 - I mentored four undergraduate and one graduate student.

   • Knowledge Graphs of the QAnon Twitter Network. IEEE BigData Conference 2022.
     Clay Adams, Malvina Bohzidarova, James Chen, Andrew Gao, Zhengtong Liu, Hunter Priniski, Junyuan Lin, Rishi Sonthalia, Andrea Bertozzi, and Jeffrey Brantingham
     [Code][Published Version]

6. Computation Applied Math REU at UCLA 2021 - I mentored four undergraduate students here. 

   • An Analysis of COVID-19 Knowledge Graphs Construction and Applications. IEEE BigData Conference 2021.
     Dominic Flocco, Bryce Palmer-Toy, Ruixiao Wang, Hongyu Zhu, Rishi Sonthalia, Junyuan Lin, Andrea L Bertozzi, P Jeffrey Brantingham
     [Code][Published Version]

I have also mentored the following students in research outside the above programs. 

1. Xinyue Cui (2021 - 2023). During this time, she was a senior at UCLA and then a master's student at USC. She is now a Ph.D student in Computer Science at USC. As part of the mentoring, we 

   • Won a competition at ICLR 2022

   • ICLR 2022 Challenge for Computational Geometry and Topology. Proceedings of Machine Learning Research Volume: Topological, Algebraic, and Geometric Learning. 2022
     Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, S\oren Hauberg, Dmitriy Nielsen, Stefan Sommer, David Klindt, Erik Hermansen, Melvin Vaupel, Benjamin Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe’er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane.
     [Code][Published Version]

   • Hyperbolic and Mixed Geometry Neural Networks. NeurIPS Workshop on Symmetry and Geometry in Neural Representations. 2022
     Xinyue Cui and Rishi Sonthalia
     [Published Version]

2. Xinyue Li (2022 - 2024).  During this time, she was a student at UCLA. She is now a Ph.D. student in applied math and statistics at Yale. As part of the mentoring, we

• Least Squares Regression Can Exhibit Under-Parameterized Double Descent. Neural Information Processing Symposium (NeurIPS) 2024
  Xinyue Li, Rishi Sonthalia
  [Code][Published Version]

3.  Praveen Bandla (2023). He was an undergraduate student at UCLA. He is now doing a master's in Data Science at NYU. 

Teaching

Current Appointment:

Boston College

• Math 4480 - Math for Machine Learning. Spring 2025

• Math 2216 - Introduction to Abstract Mathematics. Fall 2025

• Math 4480 - Reading mu-P papers - Part 1. Fall 2025

• Math 4426 - Probability. Spring 2026

• Math 4484 - Reading mu-P papers - Part 2. Spring 2026

Past Appointment:

University of California, Los Angeles

• Math 170S - Statistics

• Math 170E - Probability for Engineers

• Math 131A - Analysis

• Math 270B - Graduate Class - Numerical Linear Algebra

• Math 270A - Graduate Class - Introduction to Scientific Computing

• Math 135 - Ordinary Differential Equations

• Math 164 - Optimization

University of Michigan (As a Graduate Student Instructor):

• Fall 2019: GSI for EECS 505 - Computational Data Science and Machine Learning

• Fall 2018: Course Co-coordinator for Math 116: Calculus 2

• Summer 2018: EECS 203 - Discrete Mathematics

• Winter 2018: MATH 116 - Calculus 2

• Fall 2017: MATH 526 - Discrete Stochastic Processes

• Winter 2017: MATH 116 - Calculus 2

• Fall 2016: MATH 115 - Calculus 1

Carnegie Mellon University:

• (TA) Spring 2015: Math 122 - Integration, Differential Equations and Approximation

• (Grader) Fall 2014: Math 237 - Mathematical Studies Algebra 1

• (Grader) Fall 2014: Math 301 - Combinatorics

• (Grader) Spring 2014: Math 127 - Concepts of Mathematics

• (Grader) Spring 2014: Math 301 - Combinatorics

• (Grader) Fall 2013: Math 301 - Combinatorics

• Peer Tutor hired by the university for a variety of Mathematics and Computer Science courses Spring 2013 - Spring 2016