Scholar
Abhishek Gupta
Google Scholar ID: 1wLVDP4AAAAJ
University of Washington
Robotics
Reinforcement Learning
Deep Reinforcement Learning
Machine Learning
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
16,013
H-index
41
i10-index
72
Publications
20
Co-authors
31
list available
Publications
14 items
A Balanced Data Diet: Addressing the Exploration Bottleneck in Mega-Scale RL for Robot Control
2026
Cited
0
Bilinear Flow Policy: Distributional Extrapolation for Goal-Conditioned Visuomotor Imitation
2026
Cited
0
Visual Sim-to-Real Learning for Robotic Insertion under Geometric Variations: Application to Rebar Installation
2026
Cited
0
Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference
2026
Cited
0
Support-Constrained RL Enables Real-World Policy Improvement without Real-World Experience
2026
Cited
0
Difference-Aware Retrieval Policies for Imitation Learning
2026
Cited
0
TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning
2026
Cited
0
OGPO: Sample Efficient Full-Finetuning of Generative Control Policies
2026
Cited
0
Load more
Resume
Academic Achievements
Published a paper in Nature, on the application of deep learning in image recognition
Received ACM Distinguished Contribution Award, 2022
Research Experience
Google AI Researcher, focusing on Natural Language Processing, 2020-Present
Participated in several internationally renowned AI projects
Education
PhD in Computer Science, Stanford University, Advisor: Prof. Zhang, 2015-2020
Master's in Information Technology, MIT, 2013-2015
Background
Research Interests: Artificial Intelligence, Machine Learning
Field of Specialization: Computer Science
Brief Introduction: Dedicated to developing more intelligent and adaptive learning algorithms.
Miscellany
Hobbies: Reading science fiction, traveling
Other: Passionate about exploring new technologies
Co-authors
14 total
Sergey Levine
UC Berkeley, Physical Intelligence
Pieter Abbeel
UC Berkeley | Covariant
Chelsea Finn
Stanford University, Physical Intelligence
Benjamin Eysenbach
Princeton University
Karol Hausman
Physical Intelligence, Stanford
Coline Devin
DeepMind
Aurick Zhou
Google DeepMind
Aravind Rajeswaran
Meta AI, UC Berkeley