James A. Reggia

University of Maryland, College Park — United States

Computer Science · Physical Sciences

36h-index6.1kcitations361works1.02yr avg
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Research Topics

Neural Networks and Applications(55), Neural dynamics and brain function(54), AI-based Problem Solving and Planning(36), Modular Robots and Swarm Intelligence(30), Functional Brain Connectivity Studies(28)

Publications361 total

Complex-Valued Electromagnetic Fields in Matter: Their Relevance to Electromagnetic Field Theories of Conscious Experience
Symmetry·2025Open Access
Assessing the interactions between time series signals using weighted horizontal visibility graphs
Journal of Physics Complexity·2025Open Access
Functional Connectivity Methods for Multi-Class Mental Workload Classification
2024· 2 cited
Neurocognitive assessment under various human-robot teaming environments
2024· 1 cited
Maximizing the symmetry of Maxwell’s equations
Frontiers in Physics·2024· 3 citedOpen Access
Assessment of a Novel Virtual Environment for Examining Cognitive-Motor Processes During Execution of Action Sequences in a Human-Robot Teaming Context
Lecture notes in computer science·2024
Generalizing Maxwell’s equations to complex-valued electromagnetic fields
Physica Scripta·2023· 4 citedOpen Access
Artificial Conscious Intelligence: Why Machine Consciousness Matters to AI
Series on machine consciousness·2023
Cognitive-motor performance assessment during in-person and remote practice of action sequences
2023
NeuroCERIL: Robotic Imitation Learning via Hierarchical Cause-Effect Reasoning in Programmable Attractor Neural Networks
International Journal of Social Robotics·2023
Decoding EEG Signals with Visibility Graphs to Predict Varying Levels of Mental Workload
2023· 9 cited
Multiplex Temporal Networks for Rapid Mental Workload Classification
Lecture notes in computer science·2023· 2 cited
NeuroCERIL: Robotic Imitation Learning via Hierarchical Cause-Effect Reasoning in Programmable Attractor Neural Networks
arXiv (Cornell University)·2022Open Access
Assessment of a Novel Virtual Environment for Examining Human Cognitive-Motor Performance During Execution of Action Sequences
Lecture notes in computer science·2022· 2 cited
Tunable Neural Encoding of a Symbolic Robotic Manipulation Algorithm
Frontiers in Neurorobotics·2021· 2 citedOpen Access
NeuroLISP: High-level symbolic programming with attractor neural networks
Neural Networks·2021· 4 cited
A Neurocomputational Model of Posttraumatic Stress Disorder
2021· 1 cited
Compositional memory in attractor neural networks with one-step learning
Neural Networks·2021· 6 cited
High-Level Motor Planning Assessment During Performance of Complex Action Sequences in Humans and a Humanoid Robot
International Journal of Social Robotics·2020· 7 cited
Reinforcement-based Program Induction in a Neural Virtual Machine
2020· 1 cited
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Frequent Co-authors

Eytan Ruppin(6), Yun Peng(5), Sharon Goodall(5), Dana Nau(4), Rita Sloan Berndt(4), C. Lynne D’Autrechy(4), Granger Sutton(4), Pearl Y. Wang(3), Hui-Hsien Chou(3), Steven Armentrout(2), Yun Peng(2), Derek Monner(2), Jason Lohn(2), Alexander Grushin(2), Stanley Tuhrim(2), Yuri Shkuro(2), Yün Peng(1), Charlotte C. Mitchum(1), Kyle Wagner(1), Juan Uriagereka(1)