Suhail Sherif

Postdoctoral Researcher

LASIGE, University of Lisbon

I am currently a postdoctoral researcher at , a research unit at the University of Lisbon, working with Bruno Loff on the Hardness of Finding Good Algorithms.

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. I then did a postdoc at the University of Toronto with Toni Pitassi.

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
Lower Bounds

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

Lianna Hambardzumyan, Toniann Pitassi, Suhail Sherif, Morgan Shirley, Adi Shraibman (2023). An improved protocol for ExactlyN with more than 3 players.

Cite arXiv

Arkadev Chattopadhyay, Nikhil S. Mande, Suhail Sherif, Swagato Sanyal (2023). Lifting to Parity Decision Trees via Stifling. ITCS 2023.

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Nikhil S. Mande, Swagato Sanyal, Suhail Sherif (2022). One-Way Communication Complexity and Non-Adaptive Decision Trees. STACS 2022.

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Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif (2021). Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness. NeurIPS 2021.

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Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif (2021). No Quantum Speedup over Gradient Descent for Non-Smooth Convex Optimization. ITCS 2021.

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Arkadev Chattopadhyay, Ankit Garg, Suhail Sherif (2021). Towards Stronger Counterexamples to the Log-Approximate-Rank Conjecture. FSTTCS 2021.

Cite arXiv Talk Video