Mentoring

I have been a mentor for six different programs

1. REU via undergraudate Research Fellowships at Boston College 2025. I mentored a project on constrianted transformer. Preprint soon to follow. 

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.

5. Computation Applied Math REU at UCLA 2022 - I mentored four undergraduate and one graduate student. We have a published paper. 

6. Computation Applied Math REU at UCLA 2022 - I mentored four undergraduate students here. We have a published paper. 

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

1. Xinyue Cui - I mentored her from 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

   • Have one proceeding paper

   • Have one workshop paper

   • Have one preprint

2. Xinyue Li - I mentored her starting in 2022. She is now a Ph.D. student in applied math and statistics at Yale. As part of the mentoring, we

• Have one NeurIPS paper

3.  Praveen Bandla - I mentored him in 2023. He was an undergraduate student at UCLA. He is now doing a master's in Data Science at NYU. As part of the mentoring, we

• Have one preprint

Teaching

Classes Taught At 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

Past Teaching:

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