Google DeepMind | MSCV @ CMU | B.E. CS @BITS Pilani
I’m a research engineer at Google Deepmind, working on problems such as synthetic data, personalization, reasoning, self-improvement, and inference time scaling. Previously, I graduated from the Computer Vision program at the Robotics Institute, Carnegie Mellon University (CMU).
I completed my undergraduate degree in Computer Science student from Birla Institute of Technology and Science (BITS Pilani), Goa Campus. My interests lie in the fields of Machine Learning and Deep Learning and their applications in the domain of Computer Vision. Previously, I worked as a pre-doctoral researcher at Google Research India where I was working in the MyHealth team on projects related to Assistive Healthcare to coach people to a healthy life using Computer Vision. Specifically, I worked on improving predictions with the help of hierarchical and multi-label information with a focus on making semantically better mistakes. Before that, I worked in the Data Science team at CommerceIQ to understand people's intent from their search language on retail platforms and to help brands grow in e-commerce by identifying digital shelves or market segments in which they are lagging. I have also worked as a research intern at Martinos Centre, Harvard Medical School, and MGH, where I worked on the problem of Universal Lesion Detection, Weakly supervised learning for Diabetic Retinopathy, Vessel Segmentation, and ROP classification in Retinal Imaging. I have also worked as a Research Intern at SHI Lab, University of Oregon working owww.ri.cmu.edu/n Video Understanding and Activity Recognition, and as an undergraduate researcher at Anuradha and Prashanth Palakurthi Centre for Artificial Intelligence Research (APPCAIR), BITS Goa where I worked on Knowledge Distillation.
In my previous experiences, I have worked on challenging problems such as Human Activity Recognition in sports, Static and Dynamic Gesture Recognition, Lesion detection in Medical Imagery, Recommendation Systems, etc. Apart from this, I also actively contribute to Open-source and am a core member of the Society for Artificial Intelligence and Deep Learning (SAiDL) . I've also taught courses related to Deep Learning and Computer Vision to freshmen students and was a Teaching Assistant at the Neuromatch Academy.
Email-1 / Email-2 / CV / Github / LinkedIn / Projects / Blog
Feb 2024: Joined Google DeepMind as a Research Engineer III.
May 2023: Joined Waymo as a summer intern.
August 2022: Joined the Masters in Computer Vision (MSCV) program at CMU.
June 2022: Our pre-print on Hierarchical Multi-label classification is up on arxiv and under submission! Link
December 2021: StraysCue will be a part of the Xartup Fellowship program. We have received credits worth $200,000 to grow and scale our product.
September 2021: Joined Google Research India as a pre-doctoral researcher in the MyHealth team.
August 2021: Worked as a Teaching Assistant for the Deep Learning Neuromatch Academy with over 3500+ students registered from all over the world.
June 2021: Started a social enterprise for Animal Welfare- StraysCue
June 2021: My paper "Empirical Study of Data-Free Iterative Knowledge Distillation" got accepted at ICANN 2021
March 2021: Started working in the Data Science team at CommerceIQ
March 2021: Submitted my undergraduate thesis as a full paper to MICCAI-2021.
January 2021: Completed my B.E. Computer Science degree from BITS Pilani.
October 2020: Two extended abstracts accepted to ML4H workshop at NeurIPS 2020.
October 2020: Three extended abstracts submitted to ML4H workshop at NeurIPS 2020.
August 2020: Selected for Google AI Summer School.
July 2020: My paper "An autoencoder-based approach for simulating sports games" got accepted at ECML 2020.
June 2020: Submitted my paper: "An autoencoder based approach for simulating sports games" at ECML 2020.
May 2020: Started my Open-source library Playground- A python library consisting of pipelines for visual analysis of different sports using Computer Vision and Deep Learning.
May 2020: I'll be doing my Undergraduate thesis at QTIM Lab, Martinos Centre, Harvard Medical School and MGH where I will work on improving contextual modeling in 3D Lesion detection.
Jan 2020: I'll be working on a sponsored research project on Knowledge Distillation with TCS Research and APPCAIR.
Jan 2020: Instructor for the course Deep Learning for Computer Vision. Link
June 2019: Runner up in LeadingIndia.AI's All India Artificial Intelligence Hackathon in which I created a tool to help differently-abled people communicate efficiently using improved sign language recognition and smart word/sentence recommendations.