Ashvin Nair Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

John Brown University

faculty

14 h-index 29 pubs 1,308 cited

Research Areas

Reinforcement Learning in Robotics Robot Manipulation and Learning Domain Adaptation and Few-Shot Learning Muscle activation and electromyography studies Adversarial Robustness in Machine Learning

Is this your profile? Verify and claim your profile

OverviewAI-generated summary

Ashvin Nair's research is centered on the intersection of reinforcement learning and robotics, with a focus on enabling robots to learn complex manipulation tasks. He explores techniques such as offline reinforcement learning and domain adaptation to improve the efficiency and robustness of robot learning algorithms. Nair's work addresses challenges in robot manipulation through methods like composing goals in latent space for online fine-tuning. He also investigates self-rewarding offline-to-online finetuning strategies, particularly in the context of industrial applications such as connector insertion from visual data. Additionally, Nair contributes to the study of adversarial robustness in machine learning.

Metrics

  • h-index: 14
  • Publications: 29
  • Citations: 1,308

Selected Publications

  • Traceless Peptide Backbone Editing via Bio-inspired Cysteine to Thiazole Conversion (2025) DOI

Collaborators

Researchers in the database who share publications

William H. Bancroft John Brown University 1 shared publication Meg Shieh John Brown University 1 shared publication Hongye Wang John Brown University 1 shared publication

Similar Researchers

Based on overlapping research topics

Eric Hsiung John Brown University
Reinforcement Learning in Robotics Robot Manipulation and Learning Adversarial Robustness in Machine Learning
Good match
Josh Roy John Brown University
Reinforcement Learning in Robotics Domain Adaptation and Few-Shot Learning Adversarial Robustness in Machine Learning
Good match
Serena Booth John Brown University
Reinforcement Learning in Robotics Robot Manipulation and Learning Adversarial Robustness in Machine Learning
Good match
Samuel Lobel John Brown University
Reinforcement Learning in Robotics Adversarial Robustness in Machine Learning
Good match
Jeffrey Zhu John Brown University
Domain Adaptation and Few-Shot Learning Adversarial Robustness in Machine Learning
Related
Semanti Basu John Brown University
Reinforcement Learning in Robotics Robot Manipulation and Learning
Related