About Me
I am the Iris & Howard Critchell Assistant Professor in the Mathematics Department at Harvey Mudd College. My research focuses are in mathematical data science, optimization, and applied convex geometry. I leverage mathematical tools, such as those from probability, combinatorics, and convex geometry, on problems in data science and optimization. Areas in which I have been active recently include randomized numerical linear algebra, combinatorial methods for convex optimization, tensor decomposition for topic modeling, network consensus and ranking problems, and community detection on graphs and hypergraphs. My research is supported by NSF DMS #2211318 “Tensor Models, Methods, and Medicine”.
Before starting at HMC, I received my PhD in the Graduate Group in Applied Mathematics at the University of California, Davis where I was fortunate to be advised by Professor Jesús A. De Loera, and then was a CAM Assistant Professor (post-doc) in the University of California, Los Angeles (UCLA) Mathematics Department where my exceptional postdoctoral mentor was Professor Deanna Needell.
Recent News
December ‘24: We (with collaborators Alejandra Castillo, Iryna Hartsock, Paulina Hoyos, Lara Kassab, Alona Kryshchenko, Kamila R. Larripa, Deanna Needell, Shambhavi Suryanarayanan, and Karamatou Yacoubou-Djima) submitted our paper Randomized Kaczmarz methods for t-product tensor linear systems with factorized operators! In this paper, we extend the randomized Kaczmarz method to solve a t-product tensor system where the measurement tensor is given in factorized form. We develop variants of the randomized factorized Kaczmarz method for matrices that approximately solve tensor systems in both the consistent and inconsistent regimes. We provide theoretical guarantees of the exponential convergence rate of our algorithms, accompanied by illustrative numerical simulations, including in image deblurring!
October ‘24: I am a SIAM representative on the Joint Taskforce on Data Science Modeling Curriculum, which is a shared effort between ACM, ASA, MAA and SIAM. The taskforce extends the efforts of the ACM Data Science Task Force towards a complete data science model curriculum, a multidisciplinary effort with representatives from computing, statistics, applied mathematics, and other possible societies. Our work on the forthcoming ACM-ASA-MAA-SIAM++ Competencies for Undergraduate Data Science Curricula was featured in SIAM News!
September ‘24: My co-PIs and I were awarded an NSF Major Research Instrumentation (MRI) grant for project “Equipment: MRI Consortium: Track 1 Acquisition of a High-Performance Computing Cluster for Interdisciplinary Research at the Claremont Colleges”! This grant will fund a new high-performance cluster to be housed at Claremont McKenna College (CMC) and shared between the Claremont Colleges consortium. This project is joint with PI Paul S Nerenberg (CMC) and co-PIs Shibu Yooseph (CMC), Bilin Zhuang (HMC), and Angela Vossmeyer (CMC). Very appreciative for the opportunity to bring new HPC tools to Harvey Mudd College!
September ‘24: We (with collaborators Minxin Zhang and Deanna Needell) submitted our paper Tensor Randomized Kaczmarz Methods for Linear Feasibility Problems! In this paper, we propose and analyze new efficient variants of the randomized Kaczmarz method for solving linear feasibility problems defined over tensors under the tensor t-product.
August ‘24: I joined the editorial board of Numerical Algorithms! Looking forward to being part of this great journal.
July ‘24: I was named the Iris & Howard Critchell Assistant Professor at Harvey Mudd College. This chair is awarded to a junior professor in advance of earning tenure as a way to recognize faculty, who in the early stages of their careers, have exhibited an unusual talent for mentoring and counseling students in all aspects of their lives: curricular, extracurricular, and personal. I am honored to hold this chair named after Iris and Howard Critchell, who were founding directors of the Harvey Mudd College Bates Aeronautics Program and amazing people!