Cordova: Web-based management of genetic variation data. - Sean S. Ephraim; Nikhil Anand; Adam P. DeLuca; Kyle R. Taylor; Diana L. Kolbe; Allen C. Simpson; Hela Azaiez; Christina M. Sloan; A. Eliot Shearer; Andrea R. Hallier; Thomas L. Casavant; Todd E. Scheetz; et al. (Bioinform., 2014)

Statistical Model Checking for Dynamical Processes on Networks: A Healthcare Application. - Yenda Ramesh; Nikhil Anand; M. V. Panduranga Rao (COMSNETS, 2019)

DyNeMoC: Statistical Model Checking for Agent Based Systems on Graphs. - Yenda Ramesh; Nikhil Anand; M. V. Panduranga Rao (PRIMA, 2019)

Influence Scores at Scale for Efficient Language Data Sampling. - Nikhil Anand; Joshua Tan; Maria Minakova (EMNLP, 2023)

Comprehensive Benchmarking of Entropy and Margin Based Scoring Metrics for Data Selection. - Anusha Sabbineni; Nikhil Anand; Maria Minakova (CoRR, 2023)

Dataset Difficulty and the Role of Inductive Bias. - Devin Kwok; Nikhil Anand; Jonathan Frankle; Gintare Karolina Dziugaite; David Rolnick (CoRR, 2024)

Mixture of Parrots: Experts improve memorization more than reasoning. - Samy Jelassi; Clara Mohri; David Brandfonbrener; Alex Gu; Nikhil Vyas 001; Nikhil Anand; David Alvarez-Melis; Yuanzhi Li; Sham M. Kakade; Eran Malach (ICLR, 2025)

Loss-to-Loss Prediction: Scaling Laws for All Datasets. - David Brandfonbrener; Nikhil Anand; Nikhil Vyas 001; Eran Malach; Sham M. Kakade (Trans. Mach. Learn. Res., 2025)

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? - Tian Qin; Core Francisco Park; Mujin Kwun; Aaron Walsman; Eran Malach; Nikhil Anand; Hidenori Tanaka; David Alvarez-Melis (CoRR, 2025)

Characterization and Mitigation of Training Instabilities in Microscaling Formats. - Huangyuan Su; Mujin Kwun; Stephanie Gil; Sham M. Kakade; Nikhil Anand (CoRR, 2025)