Suhail Sherif

Suhail Sherif

Postdoctoral Researcher

Vector Institute

I am currently a postdoctoral researcher at Vector Institute working with colleagues at the Computer Science department in the University of Toronto.

I completed my PhD under the supervision of Arkadev Chattopadhyay at the Tata Institute of Fundamental Research. The work therein was awarded the 2021 ACM India Doctoral Dissertation Award. You can watch me defend my dissertation here.

On this page you can find my recent/featured publications and maybe even other things that I might feel comfortable sharing with strangers on the internet.

Interests
  • Query and Communication Complexity
  • Quantum Computing
Education
  • PhD in Theoretical Computer Science, 2021

    Tata Institute of Fundamental Research

  • BTech in Computer Science & Engineering, 2013

    Indian Institute of Technology, Guwahati

Recent Publications

Click here for all publications

(2022). One-Way Communication Complexity and Non-Adaptive Decision Trees. STACS 2022.

Cite arXiv

(2021). Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness. NeurIPS 2021.

Cite arXiv Talk Video

(2021). No Quantum Speedup over Gradient Descent for Non-Smooth Convex Optimization. ITCS 2021.

Cite arXiv Talk Video

(2021). Towards Stronger Counterexamples to the Log-Approximate-Rank Conjecture. FSTTCS 2021.

Cite arXiv Talk Video