Vignesh Kothapalli

vk_prof_pic.jpeg

Hi :wave:, I’m a first year CS PhD student at Stanford University. I’m primarily interested in understanding the computational aspects of learning in neural networks, and using these insights to develop novel modeling techniques.

Previously, I was a senior ML engineer at LinkedIn AI building recommendation foundation models. I earned my MSc in Computer Science at NYU Courant, and had an amazing time being a part of the Math and Data Group. I have also contributed to TensorFlow and served as a maintainer for TensorFlow-IO during my time at IBM. I hold a B.Tech in Electronics and Communication Engineering from IIT Guwahati.

Whats New

Academic Service

  • Conference Reviewer: NeurIPS 2024 (Top-Reviewer), ICML 2025, ICLR 2026
  • Journal Reviewer: IEEE Transactions on Cybernetics, IEEE Access, IEEE Transactions on Industrial Informatics, TMLR

Selected Publications

See full list at Google Scholar.
  1. ACL
    cot_icl_intro.png
    CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations
    Vignesh Kothapalli, Hamed Firooz, and Maziar Sanjabi
    Proceedings of Association for Computational Linguistics, 2025
  2. ICML
    liger.gif
    Liger-Kernel: Efficient Triton Kernels for LLM Training
    Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, and 8 more authors
    Championing Open-source DEvelopment in ML Workshop @ ICML25, 2025
  3. NeurIPS
    graphnc.gif
    A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
    Vignesh Kothapalli, Tom Tirer, and Joan Bruna
    Advances in Neural Information Processing Systems, 2023
  4. ICML
    rlap.png
    Randomized Schur Complement Views for Graph Contrastive Learning
    Vignesh Kothapalli
    In International Conference on Machine Learning , 2023