Scholar
Devin White
Google Scholar ID: 9sorVs8AAAAJ
Machine Learning Researcher, Army Educational Outreach Program
RLHF
Human Guided Reinforcement Learning
AI Alignment
Large Language Models
Small Language Model
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
43
H-index
3
i10-index
2
Publications
8
Co-authors
7
list available
Contact
Twitter
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GitHub
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LinkedIn
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Publications
4 items
Multi-Task Reward Learning from Human Ratings
2025
Cited
0
Too Big to Think: Capacity, Memorization, and Generalization in Pre-Trained Transformers
2025
Cited
0
RbRL2.0: Integrated Reward and Policy Learning for Rating-based Reinforcement Learning
2025
Cited
0
Performance Optimization of Ratings-Based Reinforcement Learning
2025
Cited
0
Resume (English only)
Academic Achievements
Paper accepted to AAAI 2024 (on RbRL)
Two papers accepted to AAAI 2025 Collaborative AI and Modelling of Humans Bridge Program
One paper accepted to AAAI 2025 Toward Knowledgeable Foundation Models Workshop
Work presented at ICML 2023 Many Facets of Preference Learning Workshop
Research presented at 2022 Army Research Labs Humans in Complex Systems Technical Advisory Board meeting (hosted by National Academy of Sciences)
Paper accepted to AIAA Guidance, Navigation, and Controls Conference 2024
Research Experience
Oct 2023–Present: Machine Learning Researcher at AEOP (Army Educational Outreach Program), working on RbRL optimization and LLM benchmarking in Atari
Sep 2022–Dec 2023: Graduate Research Assistant at UTSA, finalized RbRL research and worked on time-constrained intercept guidance
Jan 2022–Aug 2022: Technical Laboratory Assistant II at UTSA, designed IRB-approved user study and built custom Gymnasium environment for RL
Aug 2021–Dec 2021: Undergraduate Research Assistant at UTSA, led a team of four in implementing RbRL in Atari environments
Jun 2021–Aug 2021: NSF REU participant at UTSA, gained hands-on AI research experience through projects and lectures
Background
Machine Learning Researcher with an M.S. in Artificial Intelligence
Specializes in emergent capabilities of Large Language Models (LLMs) in interactive environments (e.g., Atari)
Expertise in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), particularly Rating-based RL (RbRL)
Demonstrated end-to-end research capability with 5 publications in top AI venues
Proficient in Python, PyTorch, TensorFlow, Stable Baselines3, and other AI/ML tools
Co-authors
7 total
Nicholas Waytowich
AI Research Scientist, U.S. Army Research Laboratory; Columbia University
Yongcan Cao
UT San Antonio
Vernon J. Lawhern
Army Research Laboratory
Mingkang Wu
PhD Candidate at The University of Texas at San Antonio
Vinicius G. Goecks
U.S. Army DEVCOM Army Research Laboratory
Co-author 6
Abhinav Sinha
Guidance, Autonomy, Learning, and Control for Intelligent Systems Lab; University of Cincinnati
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