Research Areas

Large Language Models & Generative AI

Leading research in applying LLMs to command and control planning, with focus on human-guided AI systems that can be steered and aligned through human feedback.

Human-Guided Machine Learning

Developing algorithms that learn from human feedback, demonstrations, and interventions to create more intuitive and controllable AI systems for complex decision-making tasks.

Reinforcement Learning & Multi-Agent Systems

Exploring deep reinforcement learning techniques for multi-agent coordination, human-robot collaboration, and autonomous systems in tactical environments.

Featured Projects

COA-GPT

Generative pre-trained transformers for accelerated Course of Action development in military operations. A groundbreaking application of LLMs for Command and Control planning.

LLMs Generative AI C2 Planning

Publication

DisasterResponse-GPT

Large language models for accelerated plan of action development in disaster response scenarios. Applying AI to critical emergency response planning.

LLMs Emergency Response NLP

arXiv

StarCraftImage Dataset

A dataset for prototyping spatial reasoning methods for multi-agent environments. Enables research in AI-driven strategic decision-making.

Multi-Agent RL Computer Vision Dataset

Publication

DIP-RL: Demonstration-Inferred Preference Learning

Novel approach to learning from human demonstrations in Minecraft environments. Bridges the gap between human intuition and AI learning.

Reinforcement Learning Human Feedback Minecraft

arXiv

Rating-based Reinforcement Learning

Published at AAAI 2024. A novel framework for incorporating human ratings into reinforcement learning algorithms.

Reinforcement Learning Human-in-the-Loop AAAI

Publication

Brain-Computer Interfaces

Development of practical visual evoked potential based brain-computer interfaces. My PhD work focused on creating practical BCIs for real-world applications.

BCI Neuroscience EEG

Dissertation

Collaborations & Competitions

• MineRL BASALT 2022 Competition - Contributed to solving fuzzy tasks with human feedback in Minecraft environments
• NeurIPS 2021 Competition - Retrospective on learning from human feedback
• AAAI, ICML, NeurIPS, AAMAS - Regular presenter and contributor to top-tier AI/ML conferences

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