Vignesh Kothapalli

Hi , I’m a Senior Software Engineer, ML in the Foundation Models and Data team at LinkedIn AI. My current research focuses on post-training techniques for 360Brew, which is LinkedIn’s foundation model for recommendation.

Previously, I worked with Prof. Joan Bruna (NYU Courant), Prof. Yaoqing Yang (Dartmouth) and Prof. Rahul Mazumder (MIT) on topics related to the learning dynamics of neural networks. I also spent time at IBM as a TensorFlow contributor and TensorFlow-IO maintainer. I did my MSc in Computer Science at NYU Courant, and B.Tech in Electronics and Communication Engineering from IIT Guwahati.

Research

I’m primarily interested in understanding the computational aspects of learning in neural networks, and using these insights to develop novel modeling techniques.

• Foundation Models: Chain-of-Thought reasoning, In-Context Learning and Multi-Task Learning in Transformer based LLMs.
• Learning Dynamics: Understanding the interplay between feature evolution, weight matrix spectra and generalization in shallow and deep neural networks.
• Efficient Training/Inference: Developing low-level (randomized) algorithms for training and inference of large scale LLMs/GNNs.
  
  

Whats New

• [2025.02] Our tech-report on training and deploying production-grade LLMs at LinkedIn is available on arxiv!
• [2025.01] The 360Brew foundation model tech-report is available on arxiv!
• [2024.10] Our tech-report on Liger-Kernels is now available on arxiv. (GPU Mode/Lightning AI/AMD+Embedded LLM/Blog)
  
  

Academic Service

• Conference Reviewer: NeurIPS 2024, ICML 2025
• Journal Reviewer: : IEEE Transactions on Cybernetics, IEEE Access, IEEE Transactions on Industrial Informatics, TMLR