Varun Gulshan
I've been with Google since 2013, working in the areas of Machine Learning, Computer Vision and Health Research. I lead the Earth Observation Sciences team, which is part of the Climate and Energy efforts within Applied Sciences. Our team's mission is to use Machine Learning and Earth Observation imagery to solve Geoscience research questions, motivated by applications in climate mitigation and adaptation. Prior to this role, I was the engineering co-founder of the medical imaging team within Google research, where we developed and deployed models for detecting diabetic retinopathy from retina images. Prior to Google I was part of the 6 people team at Flutter, building systems for real time gesture recognition. I completed my PhD from the Visual Geometry Group in Oxford, UK and Bachelors in Computer Science from the Indian Institute of Technology (IIT), Delhi. Link to my personal website.
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Google
Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping
Umangi Jain
Carl Elkin
Alex Wilson
Betty Peng
2024
Cross-modal distillation for flood extent mapping
Shubhika Garg
Gideon Dror
Ben Feinstein
Adi Gerzi Rosenthal
Shahar Timnat
Environmental Data Science (2023)
Multimodal contrastive learning for remote sensing tasks
Alex Wilson
Umangi Jain
Self-Supervised Learning - Theory and Practice, NeurIPS 2022 Workshop
Cross Modal Distillation for Flood Extent Mapping
Shubhika Garg
Gideon Dror
Ben Feinstein
Adi Gerzi Rosenthal
Shahar Timnat
Tackling Climate Change with Machine Learning, NeurIPS 2022 Workshop
Inundation Modeling in Data Scarce Regions
Zvika Ben-Haim
Sella Nevo
Vova Anisimov
Yusef Shafi
Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop (2019)
Performance of a Deep-Learning Algorithm vs Manual Grading for Detecting Diabetic Retinopathy in India
Renu P. Rajan
Rajiv Raman
Ramasamy Kim
Derek Wu
Lily Peng
Tyler Rhodes
Peter Wubbels
Kira Whitehouse
JAMA Ophthalmology (2019)
Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy
Ehsan Rahimy
Peter Karth
Lily Peng
Ophthalmology (2018)
