Sotabase

Career

· Software Engineer, Google2020–
· Data Scientist, Meta2019–2019
· MS in Computer Science, University of California, Berkeley2017–2019
· Bachelor of Science in Computer Science, Stanford University2013–2017

Publications (24)

Single-Shot Pruning for Offline Reinforcement Learning
arXiv.org · 2021
26
cited
Off-Policy Adversarial Inverse Reinforcement Learning
arXiv.org · 2020
13
cited
Representation Learning in Deep RL via Discrete Information Bottleneck
International Conference on Artificial Intelligence and Statistics · 2022
11
cited
Efficient Reinforcement Learning by Discovering Neural Pathways
Neural Information Processing Systems · 2024
7
cited
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning
arXiv.org · 2021
7
cited
Metal nanoparticle enhanced light absorption in GaAs thin-film solar cell
Asia-Pacific Conference on Applied Electromagnetics · 2016
5
cited
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
arXiv.org · 2019
3
cited
ENF Based Grid Classification System: Identifying the Region of Origin of Digital Recordings by team "Fourier's Underlings"
2016
3
cited
Challenge ICLR 2019 REPRODUCIBILITY-CHALLENGE DISCRIMINATOR-ACTOR-CRITIC : ADDRESSING SAMPLE INEFFICIENCY AND REWARD BIAS IN ADVERSARIAL IMITATION LEARNING
2018
2
cited
Power file extraction process from bangladesh grid and exploring ENF based classification accuracy using machine learning
2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC) · 2017
2
cited
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts
arXiv.org · 2025
1
cited
Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
arXiv.org · 2025
1
cited
Offline Policy Optimization in RL with Variance Regularizaton
arXiv.org · 2022
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