Vijay Veerabadran
AI Research Scientist at Meta
Menlo Park, California, United States
Summary
👤
Senior🎓
Top SchoolVijay Veerabadran is an AI research scientist at Meta Reality Labs with 11 years of experience building learning systems that teach robots complex manipulation skills via deep imitation and reinforcement learning. He completed a PhD in Cognitive Science at UC San Diego where his work bridged human and machine vision, including computational models of early visual perception and evaluations of large multimodal foundation models for egocentric goal inference. His internships and collaborations span top labs—Facebook AI, Google Brain, Qualcomm, and Brown—where he contributed to self-supervised representation learning, biologically inspired neural modules, and generative video modeling. Based in Menlo Park, he combines rigorous academic training with hands-on production research, moving ideas from cognitive models and publications to deployed robot learning experiments. Outside core research, his background suggests a knack for translating neuroscience-inspired mechanisms into practical ML architectures that improve agent perception and behavior.
11 years of coding experience
7 years of employment as a software developer
University of California, San DiegoBachelor of Engineering (B.E.) Computer Science and Engineering, Bachelor of Engineering (B.E.) Computer Science and Engineering at SSN College of EngineeringHigher Secondary (School) Certificate (Class 12) Computer Science, Higher Secondary (School) Certificate (Class 12) Computer Science at Jawahar Higher Secondary School
Hindi, English, Tamil, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (16)
multimodal-deep-learning10
sequence-to-sequence10
seq2seq10
tensorflow9
convolutional-neural-networks8
jupyter-notebook8
natural-language-processing7
visualization7
deep-learning6
machine-learning6
pytorch4
neural-network4
bottom-up1
attention-model1
genome1
Programming languages (3)
Github contributions (5)
vijayvee/video-captioning
Mar 2017 - Oct 2019
This repository contains the code for a video captioning system inspired by Sequence to Sequence -- Video to Text. This system takes as input a video and generates a caption in English describing the video.
Contributions:36 commits, 15 pushes, 1 branch in 2 years 7 months
sequence-to-sequencevideo-captioningtensorflows2vtmultimodal-deep-learning
vijayvee/gilbert_contours
Mar 2018 - Aug 2022
Contributions:26 pushes, 2 branches in 4 years 6 months
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