Sandpile prediction on a tree in near linear time. - Akshay Ramachandran; Aaron Schild (SODA, 2017)

MLNoC: A Machine Learning Based Approach to NoC Design. - Nishant Rao; Akshay Ramachandran; Amish Shah (SBAC-PAD, 2018)

The Paulsen problem, continuous operator scaling, and smoothed analysis. - Tsz Chiu Kwok; Lap Chi Lau; Yin Tat Lee; Akshay Ramachandran (STOC, 2018)

Near optimal sample complexity for matrix and tensor normal models via geodesic convexity. - Cole Franks; Rafael Mendes de Oliveira; Akshay Ramachandran; Michael Walter 005 (CoRR, 2021)

Spectral Analysis of Matrix Scaling and Operator Scaling. - Tsz Chiu Kwok; Lap Chi Lau; Akshay Ramachandran (SIAM J. Comput., 2021)

Strongly Polynomial Frame Scaling to High Precision. - Daniel Dadush; Akshay Ramachandran (SODA, 2024)

Hidden Convexity, Optimization, and Algorithms on Rotation Matrices. - Akshay Ramachandran; Kevin Shu; Alex L. Wang (Math. Oper. Res., 2025)

Computational aspects of the trace norm contraction coefficient. - Idris Delsol; Omar Fawzi; Jan Kochanowski; Akshay Ramachandran (CoRR, 2025)