Debidatta Dwibedi
Senior Research Scientist at Google DeepMind
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolDebidatta Dwibedi is a Senior Research Scientist based in Mountain View with 13 years of experience applying deep learning to computer vision, 3D scene understanding, robotics, and action recognition. A Carnegie Mellon-trained roboticist, he progressed from internship and residency roles into research scientist positions at Google and now Google DeepMind, blending academic rigor with production-focused ML engineering. He has contributed to high-profile open research—modifying Google Research codebases for TF2 compatibility, swapping base models to ResNet50V2, and adding visualization tools for nearest-neighbor analysis—demonstrating both systems-level and experimental depth. Known for shipping end-to-end training and evaluation refinements, he pairs strong model-building skills with practical dataset and pipeline engineering. Colleagues value his ability to translate complex vision tasks into reproducible, scalable experiments that inform real-world robotics and perception systems.
13 years of coding experience
8 years of employment as a software developer
Indian Institute of Technology KanpurMaster’s Degree Robotics, Master’s Degree Robotics at Carnegie Mellon University
Hindi, Odia, English
Github Skills (6)
machine-learning10
tensorflow10
python10
ai10
keras9
computer-vision9
Programming languages (5)
Github contributions (5)
google-research/google-research
Jul 2019 - Sep 2021
Google Research
Role in this project:
ML Engineer
ML EngineerContributions:25 commits, 23 comments in 2 years 2 months
Contributions summary:Debidatta primarily contributed to the Google Research repository by modifying and adapting existing code related to machine learning research. Their work involved switching the base model for the project to ResNet50V2 and updating the dataset preparation scripts for TF2 compatibility. They also introduced visualization tools and modified the code to handle the visualization of nearest neighbors. The user focused on refining the training and evaluation pipeline.
googlemachine-learningai
debidatta/debidatta.github.io
Aug 2018 - Mar 2024
Contributions:19 pushes, 2 branches in 5 years 8 months
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