The University of Texas at Austin
Email: matthewfaw [at]

About Me

I am a final-year Ph.D. candidate in the ECE department at The University of Texas at Austin, where I am very fortunate to be advised by Sanjay Shakkottai and Constantine Caramanis.

Prior to joining UT Austin, I spent four years at Duke University, where I graduated with majors in Electrical & Computer Engineering, Computer Science, and Mathematics. During my time there, I had the great fortune of working with Ben Lee on designing economically sustainable algorithms for datacenter-level computational sprinting, Richard Fair on designing digital microfluidic devices capable of manipulating cells within a droplet, and Nick Buchler on using CRISPR technologies to create cells which perform logical operations.

Research Interests

My interests lie broadly in the design and analysis of stochastic optimization and sequential decision-making algorithms. I am particularly interested in:



Publications (see )

In Submission:

  • On Mitigating Unconscious Bias through Bandits with Evolving Biased Feedback
    F, Constantine Caramanis, Sanjay Shakkottai, Jessica Hoffmann
    Preliminary version: NeurIPS 2023 Workshop: Algorithmic Fairness through the Lens of Time, NeurIPS'23 Workshop, New Orleans, LA.


  • Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD
    F*, Litu Rout*, Constantine Caramanis, Sanjay Shakkottai
    Conference on Learning Theory, COLT'23, Bangalore, India.
  • The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance
    F*, Isidoros Tziotis*, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward
    Conference on Learning Theory, COLT'22, London, UK.
    Check out my Twitter thread on this paper.
    Here are some slides on this result, and an 18-minute recorded talk by Isidoros and me.
  • Learning To Maximize Welfare with a Reusable Resource
    F*, Orestis Papadigenopoulos*, Constantine Caramanis, Sanjay Shakkottai
  • Single Sample Prophet Inequalities via Greedy-Ordered Selection
    Constantine Caramanis, Paul Dütting, F, Federico Fusco, Philip Lazos, Stefano Leonardi, Orestis Papadigenopoulos, Emmanouil Pountourakis, Rebecca Reiffenhäuser
    ACM-SIAM Symposium on Discrete Algorithms, SODA'22, Alexandria, VA, USA (virtual).
    Supersedes and merges papers (i) and (ii)
  • Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions
    F, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
    Advances in Neural Information Processing Systems, NeurIPS'20, (virtual).
  • Computational Sprinting: Architecture, Dynamics, and Strategies
    Seyed Majid Zahedi, Songchun Fan, F, Elijah Cole, Benjamin C. Lee
    ACM Transactions on Computer Systems, TOCS'17, Volume 34 Issue 4, January 2017.
: Equal contribution, : Alphabetical ordering



My coauthors include: Constantine Caramanis, Elijah Cole, Paul Dütting, Songchun Fan, Federico Fusco, Jessica Hoffmann, Philip Lazos, Benjamin Lee, Stefano Leonardi, Aryan Mokhtari, Orestis Papadigenopoulos, Emmanouil Pountourakis, Rebecca Reiffenhäuser, Litu Rout, Rajat Sen, Sanjay Shakkottai, Karthikeyan Shanmugam, Isidoros Tziotis, Rachel Ward, and Seyed Zahedi.