The Challenges of Using Scalp-EEG Input Signals for Continuous Device Control. - Garett D. Johnson; Nicholas R. Waytowich; Dean J. Krusienski (HCI (20), 2011)

Collaborative image triage with humans and computer vision. - Addison W. Bohannon; Nicholas R. Waytowich; Vernon J. Lawhern; Brian M. Sadler; Brent J. Lance (SMC, 2016)

Unsupervised adaptive transfer learning for Steady-State Visual Evoked Potential brain-computer interfaces. - Nicholas R. Waytowich; Josef Faller; Javier O. Garcia; Jean M. Vettel; Paul Sajda (SMC, 2016)

Cortically Coupled Computing: A New Paradigm for Synergistic Human-Machine Interaction. - Sameer Saproo; Josef Faller; Victor Shih; Paul Sajda; Nicholas R. Waytowich; Addison W. Bohannon; Vernon J. Lawhern; Brent J. Lance; David C. Jangraw (Computer, 2016)

EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces. - Vernon J. Lawhern; Amelia J. Solon; Nicholas R. Waytowich; Stephen M. Gordon; Chou P. Hung; Brent J. Lance (CoRR, 2016)

Multiclass Steady-State Visual Evoked Potential Frequency Evaluation Using Chirp-Modulated Stimuli. - Nicholas R. Waytowich; Dean J. Krusienski (IEEE Trans. Hum. Mach. Syst., 2016)

Development of an extensible SSVEP-BCI software platform and application to wheelchair control. - Nicholas R. Waytowich; Dean J. Krusienski (NER, 2017)

Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces. - Garrett Warnell; Nicholas R. Waytowich; Vernon Lawhern; Peter Stone 001 (AAAI, 2018)

Coordination-driven Learning in Multi-agent Problem Spaces. - Sean L. Barton; Nicholas R. Waytowich; Derrik E. Asher (AAAI Fall Symposium: ALEC, 2018)

Energy Efficient Convolutional Neural Networks for EEG Artifact Detection. - Mohit Khatwani; Morteza Hosseini; Hirenkumar Paneliya; Tinoosh Mohsenin; W. David Hairston; Nicholas R. Waytowich (BioCAS, 2018)

Measuring Collaborative Emergent Behavior in Multi-agent Reinforcement Learning. - Sean L. Barton; Nicholas R. Waytowich; Erin G. Zaroukian; Derrik E. Asher (IHSED, 2018)

Compact Convolutional Neural Networks for Classification of Asynchronous Steady-state Visual Evoked Potentials. - Nicholas R. Waytowich; Vernon Lawhern; Javier O. Garcia; Jennifer Cummings; Josef Faller; Paul Sajda; Jean M. Vettel (CoRR, 2018)

Cycle-of-Learning for Autonomous Systems from Human Interaction. - Nicholas R. Waytowich; Vinicius G. Goecks; Vernon J. Lawhern (CoRR, 2018)

Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time. - Vinicius G. Goecks; Gregory M. Gremillion; Vernon J. Lawhern; John Valasek; Nicholas R. Waytowich (AAAI, 2019)

Learning Behaviors from a Single Video Demonstration Using Human Feedback. - Sunil Gandhi; Tim Oates 001; Tinoosh Mohsenin; Nicholas R. Waytowich (AAMAS, 2019)

Investigating Evoked EEG Responses to Targets Presented in Virtual Reality. - Pawan Lapborisuth; Josef Faller; Jonathan Koss; Nicholas R. Waytowich; Jonathan Touryan; Paul Sajda (EMBC, 2019)

Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. - Bharat Prakash; Mohit Khatwani; Nicholas R. Waytowich; Tinoosh Mohsenin (FLAIRS, 2019)

On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. - Bharat Prakash; Mark Horton; Nicholas R. Waytowich; William David Hairston; Tim Oates 001; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2019)

Evaluating the Coordination of Agents in Multi-agent Reinforcement Learning. - Sean L. Barton; Erin G. Zaroukian; Derrik E. Asher; Nicholas R. Waytowich (IHSI, 2019)

Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learning. - Nicholas R. Waytowich; Sean L. Barton; Vernon Lawhern; Ethan Stump; Garrett Warnell (CoRR, 2019)

On Memory Mechanism in Multi-Agent Reinforcement Learning. - Yilun Zhou; Derrik E. Asher; Nicholas R. Waytowich; Julie A. Shah (CoRR, 2019)

Inferring and Learning Multi-Robot Policies by Observing an Expert. - Pietro Pierpaoli; Harish Ravichandar; Nicholas R. Waytowich; Anqi Li 001; Derrik E. Asher; Magnus Egerstedt (CoRR, 2019)

Learning from Observations Using a Single Video Demonstration and Human Feedback. - Sunil Gandhi; Tim Oates 001; Tinoosh Mohsenin; Nicholas R. Waytowich (CoRR, 2019)

Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Sparse Reward Environments. - Vinicius G. Goecks; Gregory M. Gremillion; Vernon J. Lawhern; John Valasek; Nicholas R. Waytowich (CoRR, 2019)

A Narration-based Reward Shaping Approach using Grounded Natural Language Commands. - Nicholas R. Waytowich; Sean L. Barton; Vernon Lawhern; Garrett Warnell (CoRR, 2019)

Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. - Bharat Prakash; Nicholas R. Waytowich; Ashwinkumar Ganesan; Tim Oates 001; Tinoosh Mohsenin (SafeAI@AAAI, 2020)

PODNet: A Neural Network for Discovery of Plannable Options. - Ritwik Bera; Vinicius G. Goecks; Gregory M. Gremillion; John Valasek; Nicholas R. Waytowich (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1), 2020)

Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Dense and Sparse Reward Environments. - Vinicius G. Goecks; Gregory M. Gremillion; Vernon J. Lawhern; John Valasek; Nicholas R. Waytowich (AAMAS, 2020)

Yesterday's Reward is Today's Punishment: Contrast Effects in Human Feedback to Reinforcement Learning Agents. - Divya Ramesh; Anthony Z. Liu; Andres J. Echeverria; Jean Y. Song; Nicholas R. Waytowich; Walter S. Lasecki (AAMAS, 2020)

Energy-Efficient Hardware for Language Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Nitheesh Kumar Manjunath; Houman Homayoun; Avesta Sasan; Nicholas R. Waytowich; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2020)

Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation. - David Watkins-Valls; Jingxi Xu 002; Nicholas R. Waytowich; Peter K. Allen (IROS, 2020)

The Autoregressive Linear Mixture Model: A Time-Series Model for an Instantaneous Mixture of Network Processes. - Addison W. Bohannon; Vernon J. Lawhern; Nicholas R. Waytowich; Radu V. Balan (IEEE Trans. Signal Process., 2020)

An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Bharat Prakash; Arnab Neelim Mazumder; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (AICAS, 2021)

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. - Stephanie Milani; Anssi Kanervisto; Karolis Ramanauskas; Sander Schulhoff; Brandon Houghton; Sharada P. Mohanty; Byron Galbraith; Ke Chen; Yan Song; Tianze Zhou; Bingquan Yu; He Liu; et al. (NeurIPS (Competition and Demos), 2021)

Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. - Rohin Shah; Steven H. Wang; Cody Wild; Stephanie Milani; Anssi Kanervisto; Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash; Edmund Mills; Divyansh Garg; Alexander Fries; et al. (NeurIPS (Competition and Demos), 2021)

Gaze-Informed Multi-Objective Imitation Learning from Human Demonstrations. - Ritwik Bera; Vinicius G. Goecks; Gregory M. Gremillion; Vernon J. Lawhern; John Valasek; Nicholas R. Waytowich (CoRR, 2021)

Interactive Hierarchical Guidance using Language. - Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2021)

On games and simulators as a platform for development of artificial intelligence for command and control. - Vinicius G. Goecks; Nicholas R. Waytowich; Derrik E. Asher; Song Jun Park; Mark R. Mittrick; John T. Richardson; Manuel Vindiola; Anne Logie; Mark Dennison; Theron Trout; Priya Narayanan; Alexander Kott (CoRR, 2021)

Automatic Goal Generation using Dynamical Distance Learning. - Bharat Prakash; Nicholas R. Waytowich; Tinoosh Mohsenin; Tim Oates 001 (CoRR, 2021)

Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. - Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins; Bharat Prakash (CoRR, 2021)

Improving Autonomous Robotic Navigation Using Imitation Learning. - Brian Cesar-Tondreau; Garrett Warnell; Ethan Stump; Kevin Kochersberger; Nicholas R. Waytowich (Frontiers Robotics AI, 2021)

A Flexible Multichannel EEG Artifact Identification Processor using Depthwise-Separable Convolutional Neural Networks. - Mohit Khatwani; Hasib-Al Rashid; Hirenkumar Paneliya; Mark Horton; Nicholas R. Waytowich; W. David Hairston; Tinoosh Mohsenin (ACM J. Emerg. Technol. Comput. Syst., 2021)

An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning. - Nitheesh Kumar Manjunath; Aidin Shiri; Morteza Hosseini; Bharat Prakash; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Open J. Circuits Syst., 2021)

Combining Learning From Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. - Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash (AAAI Spring Symposium: MAKE, 2022)

An Optimization Framework for Efficient Vision-Based Autonomous Drone Navigation. - Mozhgan Navardi; Aidin Shiri; Edward Humes; Nicholas R. Waytowich; Tinoosh Mohsenin (AICAS, 2022)

PerMTL: A Multi-Task Learning Framework for Skilled Human Performance Assessment. - Indrajeet Ghosh; Avijoy Chakma; Sreenivasan Ramasamy Ramamurthy; Nirmalya Roy; Nicholas R. Waytowich (ICMLA, 2022)

Mobile Manipulation Leveraging Multiple Views. - David Watkins-Valls; Peter K. Allen; Henrique Maia; Madhavan Seshadri; Jonathan Sanabria; Nicholas R. Waytowich; Jacob Varley (IROS, 2022)

TagTeam: Towards wearable-assisted, implicit guidance for human-drone teams. - Kasthuri Jayarajah; Aryya Gangopadhyay; Nicholas R. Waytowich (SmartWear@MobiCom, 2022)

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. - Rohin Shah; Steven H. Wang; Cody Wild; Stephanie Milani; Anssi Kanervisto; Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash; Edmund Mills; Divyansh Garg; Alexander Fries; et al. (CoRR, 2022)

Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II. - Nicholas R. Waytowich; James Zachary Hare; Vinicius G. Goecks; Mark R. Mittrick; John T. Richardson; Anjon Basak; Derrik E. Asher (CoRR, 2022)

TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human-Drone Teams. - Kasthuri Jayarajah; Aryya Gangopadhyay; Nicholas R. Waytowich (CoRR, 2022)

Multiple View Performers for Shape Completion. - David Watkins-Valls; Peter E. Allen; Krzysztof Choromanski; Jacob Varley; Nicholas R. Waytowich (CoRR, 2022)

Towards an Interpretable Hierarchical Agent Framework using Semantic Goals. - Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2022)

A Hardware Accelerator for Language-Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Houman Homayoun; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Des. Test, 2022)

Efficient Language-Guided Reinforcement Learning for Resource-Constrained Autonomous Systems. - Aidin Shiri; Mozhgan Navardi; Tejaswini Manjunath; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Micro, 2022)

Towards Fully Autonomous Negative Obstacle Traversal via Imitation Learning Based Control. - Brian Cesar-Tondreau; Garrett Warnell; Kevin Kochersberger; Nicholas R. Waytowich (Robotics, 2022)

E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Uttej Kallakuri; Hasib-Al Rashid; Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (ACM Trans. Design Autom. Electr. Syst., 2022)

StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. - Sean Kulinski; Nicholas R. Waytowich; James Zachary Hare; David I. Inouye (CVPR, 2023)

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. - Stephanie Milani; Anssi Kanervisto; Karolis Ramanauskas; Sander Schulhoff; Brandon Houghton; Sharada P. Mohanty; Byron Galbraith; Ke Chen; Yan Song; Tianze Zhou; Bingquan Yu; He Liu; et al. (CoRR, 2023)

Learning Flight Control Systems from Human Demonstrations and Real-Time Uncertainty-Informed Interventions. - Prashant Ganesh; J. Humberto Ramos; Vinicius G. Goecks; Jared Paquet; Matthew Longmire; Nicholas R. Waytowich; Kevin M. Brink (CoRR, 2023)

DisasterResponseGPT: Large Language Models for Accelerated Plan of Action Development in Disaster Response Scenarios. - Vinicius G. Goecks; Nicholas R. Waytowich (CoRR, 2023)

DIP-RL: Demonstration-Inferred Preference Learning in Minecraft. - Ellen R. Novoseller; Vinicius G. Goecks; David Watkins; Josh Miller; Nicholas R. Waytowich (CoRR, 2023)

Rating-Based Reinforcement Learning. - Devin White; Mingkang Wu; Ellen R. Novoseller; Vernon J. Lawhern; Nicholas R. Waytowich; Yongcan Cao (AAAI, 2024)

COA-GPT: Generative Pre-Trained Transformers for Accelerated Course of Action Development in Military Operations. - Vinicius G. Goecks; Nicholas R. Waytowich (ICMCIS, 2024)

Scalable Interactive Machine Learning for Future Command and Control. - Anna Madison; Ellen R. Novoseller; Vinicius G. Goecks; Benjamin T. Files; Nicholas R. Waytowich; Alfred Yu; Vernon J. Lawhern; Steven Thurman; Christopher Kelshaw; Kaleb McDowell (ICMCIS, 2024)

GUIDE: Real-Time Human-Shaped Agents. - Lingyu Zhang; Zhengran Ji; Nicholas R. Waytowich; Boyuan Chen 001 (NeurIPS, 2024)

Adversarial Attacks on Reinforcement Learning Agents for Command and Control. - Ahaan Dabholkar; James Zachary Hare; Mark R. Mittrick; John T. Richardson; Nicholas R. Waytowich; Priya Narayanan; Saurabh Bagchi (CoRR, 2024)

Atari-GPT: Investigating the Capabilities of Multimodal Large Language Models as Low-Level Policies for Atari Games. - Nicholas R. Waytowich; Devin White; MD Sunbeam; Vinicius G. Goecks (CoRR, 2024)

Augmenting Personalized Memory via Practical Multimodal Wearable Sensing in Visual Search and Wayfinding Navigation. - Indrajeet Ghosh; Kasthuri Jayarajah; Nicholas R. Waytowich; Nirmalya Roy (UMAP, 2025)

RbRL2.0: Integrated Reward and Policy Learning for Rating-based Reinforcement Learning. - Mingkang Wu; Devin White; Vernon Lawhern; Nicholas R. Waytowich; Yongcan Cao (CoRR, 2025)

Performance Optimization of Ratings-Based Reinforcement Learning. - Evelyn Rose; Devin White; Mingkang Wu; Vernon Lawhern; Nicholas R. Waytowich; Yongcan Cao (CoRR, 2025)

Hybrid Team Tetris: A New Platform For Hybrid Multi-Agent, Multi-Human Teaming. - Kaleb McDowell; Nicholas R. Waytowich; Javier O. Garcia; Stephen M. Gordon; Bryce Bartlett; Jeremy Gaston (CoRR, 2025)

"New" Challenges for Future C2: Commanding Soldier-Machine Partnerships. - Anna Madison; Kaleb McDowell; Vinicius G. Goecks; Jeff Hansberger; Ceili M. Olney; Claire Ahern; Amar R. Marathe; Nicholas R. Waytowich; Christian Kenney; Christopher Kelshaw (CoRR, 2025)

Learning Multi-Robot Coordination through Locality-Based Factorized Multi-Agent Actor-Critic Algorithm. - Chak Lam Shek; Amrit Singh Bedi; Anjon Basak; Ellen R. Novoseller; Nicholas R. Waytowich; Priya Narayanan; Dinesh Manocha; Pratap Tokekar (CoRR, 2025)

Memento: Augmenting Personalized Memory via Practical Multimodal Wearable Sensing in Visual Search and Wayfinding Navigation. - Indrajeet Ghosh; Kasthuri Jayarajah; Nicholas R. Waytowich; Nirmalya Roy (CoRR, 2025)

Multi-RAG: A Multimodal Retrieval-Augmented Generation System for Adaptive Video Understanding. - Mingyang Mao; Mariela M. Perez-Cabarcas; Utteja Kallakuri; Nicholas R. Waytowich; Xiaomin Lin; Tinoosh Mohsenin (CoRR, 2025)

EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment. - Mikolaj Walczak; Romina Aalishah; Wyatt Mackey; Brittany Story; David L. Boothe; Nicholas R. Waytowich; Xiaomin Lin; Tinoosh Mohsenin (CoRR, 2025)

Multi-Task Reward Learning from Human Ratings. - Mingkang Wu; Devin White; Evelyn Rose; Vernon Lawhern; Nicholas R. Waytowich; Yongcan Cao (CoRR, 2025)

CREW-WILDFIRE: Benchmarking Agentic Multi-Agent Collaborations at Scale. - Jonathan Hyun; Nicholas R. Waytowich; Boyuan Chen (CoRR, 2025)