Sandeep Kumar is an assistant professor in the Department of Electrical Engineering and School of Artificial Intelligence (ScAI)  at the Indian Institute of Technology Delhi (IIT Delhi). He heads the Machine Intelligence Signals and Networks (MISN) lab at IIT Delhi. His current research focuses on graphical models, manifolds, semi-supervised learning, and large-scale optimization. He received his M.Tech and Ph.D. degrees from the Indian Institute of Technology (IIT), Kanpur, and completed his postdoc from the Hong Kong University of Science and Technology.

Research: I supervise the Machine Intelligence Signals and Networks (MISN) Lab at IIT Delhi. The overarching theme of our research efforts lies in the coherent interaction between optimization, machine learning, signal processing, and graphical models.  Specific problems of interest include:

• Graph Compression

• Machine Learning over non-Euclidean Spaces

• Fair Federated Personalized Graph Neural Networks

• Applications of Graph ML in Earth science, Neuroscience, Wireless communication, and Circuit Design

• Our Paper " UGC: Universal Graph Coarsening" got accepted to NeurIPS 2024 main track. Congratulations Mohit!

• Our paper "Optimization based Framework for Semi-Supervised Attributed Graph Coarsening" got accepted to UAI 2024. Congratulations to Manoj, Subhanu, and Archit!

• Our paper "No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation "got accepted to AAAI 2024. Congratulations to Nimesh and Anuj for their great efforts!

• Our paper " Linear Complexity Framework for Feature-Aware Graph Coarsening via Hashing", got accepted to NeurIPS Workshop in Frontiers in Graph Learning. Congratulations to Moohit, Aditi, and Rocktim. 

• Congratulations to Hemanthika and Subhanu for receiving the prestigious PMRF doctoral fellowship