| Statistical Machine Learning | Design of Provable Learning Algorithms | Sparse Signal Processing | Optimization |
| Interpretability of Deep Learning Models |
| Spatiotemporal Data Analysis |
|| TensorNOODL to appear at NeurIPS 2020! My work on guaranteed exact factorization of a structured tensor (in collaboration with Xingguo Li and Jarvis Haupt), has been accepted to NeurIPS 2020.
|| Archipelago to appear at NeurIPS 2020! Our work on feature interaction detection and attribution (in collaboration with Michael Tsang and Yan Liu) has been accepted to NeurIPS 2020.
|| DRPCA accepted for publication in the IEEE Transactions on Signal Processing! My work (in collaboration with Xingguo Li, Jineng Ren, and Jarvis Haupt) on a dictionary-based generalization of robust PCA (DRPCA) with applications to target localization in Hyperspectral imaging has been accepted for publication in the IEEE Transactions on Signal Processing.
|| Starting as a Postdoctoral Research Associate at the Melady Lab, USC I am joining the Melady lab as a Postdoctoral Research Associate mentored by Prof. Yan Liu at the University of Southern California (USC) , Los Angeles.
|| Successfully defend my Doctoral Thesis! End of an era! I successfully defended my thesis work titled "Provably Learning from Data: New Algorithms and Models for Matrix and Tensor Decompositions". Grateful to Prof. Jarvis Haupt, my mentors, collegues and friends for the wonderful time at the University of Minnesota - Twin Cities and Minneapolis.
|| Poster Session at ICLR 2019! I'll be presenting NOODL at poster #22 in the Great Hall (Ernest N. Morial Convention Center, New Orleans) between 2:30 PM - 4:30 PM (PDT)s, looking forward to the insightful discussions!
|| Nominated to present my work in the Graduation Day session at ITA! I have been invited to present my work on provable online dictionary learning as part of the Graduation Day session at ITA.
|| NOODL to appear at ICLR 2019! My work on provable online dictionary learning (in collaboration with Xingguo Li, and Jarvis Haupt) which guarantees exact recovery of both factors of the dictionary learning model has been accepted for publication at ICLR 2019. Also, very excited to receive the Travel Award to attend the conference!