|Publications||Awards and Grants||Google Scholar||Writing|
I am a Postdoctoral researcher in GML, working with Prof. Pavan Turaga at Arizona State Univeristy. I defended my PhD in Oct, 2020 from IIIT-Delhi under the guidance of Dr. Saket Anand. My dissertation title is “Exploring Geometric Constraints for Learning Representations for Visual Data”. During my PhD, I also worked as a visiting research scholar with Prof. Pavan Turaga for 6 months in 2019 (Feb - Aug) as well as during the summer of 2017. I received my Master’s degree from IIIT-Delhi. I was awarded Best Thesis Award for my thesis titled “Signal Processing Techniques to Reduce Energy Consumption in EEG Acquisition and Transmission for WBAN” under the guidance of Dr. Angshul Majumdar.
My research interests lie in deep learning and machine learning approaches for visual and time series data, topological data analysis, differential geometry and geometry driven approaches for learning. From the applications point of view, I focus on AI for Good, specifically towards wildlife conservation and human health applications.
Reach me at email@example.com or firstname.lastname@example.org
Updates and News
- Organizing the DiffCVML 2020 Workshop, held in conjunction with CVPR 2020.
- Recieved travel grant from WiML 2019 to present my work titled “Ignorance is Bliss: Semantic Pairing for Fine-grained Visual Recognition” in the workshop.
- Paper titled “A hybrid approach for tiger re-identification” is accepted at Computer Vision for Wildlife Conservation Workshop in challenge paper track at ICCV 2019.
- “Paper titled “PrOSe: Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning” is accepted to BMVC 2019.
- Paper titled ”Primate Identification in the Wild” accepted to PRICAI 2019.
- Work titled “Geometry of Deep Generative Models for learning Disentangled Representations” accepted as poster at workshop WiCV 2019 organized in CVPR 2019.
- Selected to attend the NSF-CBMS Conference on Topological Methods in Machine Learning and Artificial Intelligence.