Alejandro (Alex) Gomez-Leos

e-mail: alexgomezleos (at) utexas (dot) edu

Welcome to my professional / academic homepage. I recently earned a M.Sc. from the ECE Department at UT Austin, where my studies were generously supported by the Virginia & Ernest Cockrell, Jr. Fellowship in Engineering. At UT, I was lucky to work with Gustavo de Veciana and Sanjay Shakkottai in the Wireless Networking and Communications Group. Before that, I earned a B.Sc. in Electrical and Computer Engineering from Texas A&M University, working with Anoosheh Heidarzadeh.

I enjoy topics in the theory and practice of computer science. While at UT, my work has focused on problems in machine learning and algorithmic statistics: bandits & MDPs, robust regression, distribution testing, and low-rank tensor estimation. At Texas A&M, I fell in love with computing as a scientific and intellectual interest.

These days I like thinking about memory-efficiency and pseudorandomness for fun. Here is a research summary!

Publications

• Simple and Nearly-Optimal Sampling for Rank-1 Tensor Completion via Gauss-Jordan
  with Oscar Lopez
  Pre-print.
  Summary: We reduce rank-1 tensor completion to solving a special pair of random linear systems. This view allows us to bound the number of required samples for the original problem. The sample complexity of the latter is given by a matrix sketching problem over GF2, which can't be analyzed using leverage score sampling. To circumvent this, we study a random walk mixing time on a subspace graph.


• Single-Server Private Information Retrieval With Side Information Under Arbitrary Popularity Profiles
  with Anoosheh Heidarzadeh
  Information Theory Workshop (ITW), 2022. (conference version) (slides)
  Summary: Suppose you want to obtain some item from a database without revealing its identity. A common two-party protocol based on linear codes can ensure perfect privacy guarantees. In the prior work, these guarantees break down if the items are not equally likely to be queried. We developed a randomized protocol to solve the problem. A key technical ingredient was proving an extremal property of our codes.

Other Projects

• New! Progress on Envy-Free Cake-Cutting (pdf, slides) (TL;DR: smoothed EF cake-cutting likely admits a polyquery algorithm)
• Reversible Markov Decision Processes: Potential Applications? (slides) (TL;DR: policy iteration can be substantially faster)
• On Variance-Aware Bandits (pdf) (TL;DR: potential techniques for a new family with controllable but unknown variance)
• Learning Social Influence Functions (pdf) (TL;DR: "natural" graph epidemic processes are PAC-learnable)
• A Note on LinUCB's Smallest Eigenvalue (pdf) (TL;DR: open question - how well does LinUCB uniformly explore?)

Teaching

• Fall 2024: ECE 360C (UT): Algorithms (TA)
• Spring 2024: ECE 351K (UT): Probability & Random Processes (TA)
• Spring 2022: ECEN 325 (Texas A&M): Electronics (Peer Mentor)

Fun

My parents are from Ciudad Juárez. As an avid cook and musician, one of my favorite ways to learn about other cultures is through their culinary traditions and folkloric music. A few of my favorite reads include Solzhenitsyn's In the First Circle, Hofstadter's GEB, and Vonnegut's Slaughterhouse-Five. I enjoy board games with few rules and exponentially many configurations.

Last updated March 2025.

Website layout inspired by Kevin Tian's.