Scholar
Scott Niekum
Google Scholar ID: 4wXYfSUAAAAJ
Associate Professor, University of Massachusetts Amherst
Imitation Learning
Reinforcement Learning
AI Safety
Robotics
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Citations & Impact
All-time
Citations
5,792
H-index
40
i10-index
64
Publications
20
Co-authors
48
list available
Contact
Email
sniekum@cs.umass.edu
CV
Open ↗
GitHub
Open ↗
Publications
9 items
Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models
2026
Cited
0
Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control
2026
Cited
0
Adaptive Margin RLHF via Preference over Preferences
2025
Cited
0
Evaluation-Aware Reinforcement Learning
2025
Cited
0
DeepFleet: Multi-Agent Foundation Models for Mobile Robots
2025
Cited
0
Pairwise or Pointwise? Evaluating Feedback Protocols for Bias in LLM-Based Evaluation
2025
Cited
0
Supervised Reward Inference
2025
Cited
0
Influencing Humans to Conform to Preference Models for RLHF
2025
Cited
0
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Resume (English only)
Background
Associate Professor at the College of Information and Computer Sciences, University of Massachusetts Amherst
Director of the Safe, Confident, and Aligned Learning + Robotics Lab (SCALAR)
Core member of the interdepartmental UMass robotics group
Amazon Scholar at Amazon Robotics
Research goal: ensuring AI systems are well-aligned with human objectives and can be safely deployed in the real world
Research areas include imitation learning, reinforcement learning, AI safety, and human factors; applications span large language models and robotics
Co-authors
48 total
Peter Stone
Professor of Computer Science, The University of Texas at Austin
Daniel S. Brown
Assistant Professor, Robotics Center and Kahlert School of Computing, University of Utah
Co-author 3
Co-author 4
George Konidaris
Brown
Co-author 6
Akanksha Saran
Sony AI
Philip S. Thomas
University of Massachusetts
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