I am a postdoctoral fellow at HKUST. I am hosted by Prof. Daniel P. Palomar. Prior to that, I received my Ph.D. and M.Tech in Electrical Engineering from the Indian Institute of Technology (IIT), Kanpur, under the guidance of Prof. Ketan Rajawat and Prof. Govind Sharma, respectively. My current research interests include graphical models, non-convex optimization, and non-Gaussian statistics.

Some recent news

• (Nov 19) Received NeurIPS travel grant.
• (Nov 19) Presented paper at the Asilomar conference on signals and computers, CA, U.S.
• (Sep 19) Conference paper - Structured Graph Learning via Laplacian Spectral Constraints got accepted for Neural Information Processing (NeurIPS), Vancouver, Canada.
• (Aug 19) Invited talk at IIT Madras -A Unified Framework for Structured Graph Learning via Spectral Constraints.
• (Aug 19) Conference paper - Bipartite Structured Gaussian Graphical Modelling via Adjacency Spectral Priors, accepted for Asilomar Conference on Signals, Systems, and Computers, California, U.S.
• (July 19) Invited talk at IIT Kanpur - A Unified Framework for Structured Graph Learning via Spectral Constraints.
• (June 19) Journal paper - Optimization Algorithms for Graph Laplacian Estimation via ADMM and MM, accepted for IEEE Trans. on Signal Processing.
• (Feb 19) Invited talk at IIIT Hyderabad - A Unified Framework for Structured Graph Learning via Spectral Constraints.
• (Feb 19) Journal paper - Parameter Estimation of Heavy-Tailed AR Model With Missing Data Via Stochastic EM, accepted for IEEE Trans. on Signal Processing.