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Chang S. (CS) Nam is a Professor of Industrial and Systems Engineering at North Carolina State University, with affiliations in the UNC/NCSU Joint Department of Biomedical Engineering and the Department of Psychology. He holds editorial roles as Editor-in-Chief of Brain-Computer Interfaces journal and is a Fellow of the Human Factors and Ergonomics Society. His research focuses on advancing human-centered technologies through neuroergonomics, brain-computer interfaces (BCIs), and rehabilitation engineering, supported by grants from NSF, AFRL, AFOSR, and the Laboratory for Analytic Sciences. Education: Ph.D. in Industrial Engineering, Virginia Tech (2003) MSIE in Industrial Engineering, State University of New York at Buffalo (2000) Research Interests: His work spans neurorehabilitation, haptic interaction design, and BCI applications, aiming to bridge human cognitive and neural processes with technological systems. Key areas include adaptive human-computer interaction, EEG-based emotion recognition, and spatial augmented reality for skill training. Grants & Awards: Recipient of NSF CAREER Award (2010), Air Force Summer Faculty Fellowship (2018), and the Leland S. Kollmorgen Spirit of Innovation Award (2019) Editor of Brain-Computer Interfaces Handbook: Technological and Theoretical Advances (CRC Press) Advising & Labs: Advises students like Lingchao Mao and Priscille Koutouan Leads the Brain-Computer Interface and Neuroergonomics Lab, developing BCI systems for communication in vegetative states and neurorehabilitation

• Brain-Computer Interfaces
• Neurorehabilitation
• Haptic-User Interaction
• +4 more

Daniel Wolpert is a Professor of Neuroscience at Columbia University , where he is also Vice-Chair of the Department of Neuroscience and a key member of the Zuckerman Mind Brain and Behavior Institute . Additionally, he holds a part-time position as Director of Research at the Department of Engineering, University of Cambridge, and is a Fellow of the Royal Society and the Academy of Medical Sciences . Education: Medical Doctor (1989), D.Phil. in Physiology from the University of Oxford (1992) Previous Positions: Lecturer at Sobell Department of Motor Neuroscience (Institute of Neurology), Professor of Engineering at University of Cambridge (2005–2018) Wolpert is a world leader in sensorimotor control , combining computational neuroscience , Bayesian inference , and robotic/virtual reality technologies to reverse-engineer how the brain generates movements. His work emphasizes the brain's role in reducing sensorimotor uncertainty through predictive modeling and has implications for understanding disorders like autism and Parkinson’s disease. His awards include: Royal Society Ferrier Medal (2020) Minerva Foundation Golden Brain Award (2010) Royal Society Francis Crick Prize Lecture (2005) Daniel Wolpert actively contributes to public science communication, including a 2011 TED Talk on the computational role of the brain in movement, and leads the Wolpert Lab at Columbia, which investigates the neural basis of decision-making , motor learning , and reinforcement learning in both healthy and clinical populations.

• Neuroscience
• Computational Neuroscience
• Sensorimotor Control
• +4 more

Prof. Daniel Memmert is a Professor at the German Sport University Cologne, leading research in Sport Informatics and Sports Games within the Institute of Exercise Training and Sport Informatics. His work focuses on cognitive aspects of sports performance, decision-making, and data-driven analysis in football (soccer) and other sports. He has published extensively on topics like penalty kick strategies, home advantage dynamics, artificial intelligence applications in coaching, and route-setting in climbing. Memmert's research bridges sports science, computer science, and psychology, with over 550 publications and 41 projects to his name. He frequently engages with media, explaining complex sports phenomena to the public. Key Research Areas: Football analytics, cognitive psychology in sports, sports technology, decision-making under pressure Media Contributions: Over 50 media features discussing topics such as AI in coaching, referee bias, and athlete creativity Projects: Includes initiatives on sports data visualization, performance metrics, and prevention of sports betting addiction His work emphasizes translating academic findings into practical tools for athletes, coaches, and sports organizations, combining rigorous data analysis with real-world applications.

• Sports Science
• Football (Soccer) Analytics
• Cognitive Psychology in Sports
• +6 more

Dr. Hayriye Cagnan is a Senior Lecturer (equivalent to Associate Professor) at Imperial College London and Associate Unit Member at the MRC Brain Network Dynamics Unit. She holds a PhD in Neuroscience from the University of Amsterdam and Philips Research Laboratories (2010), an MSc in Engineering and Physical Science in Medicine from Imperial College London, and a BS in Electrical and Electronics Engineering from Cornell University as a Fulbright Scholar. Her research develops theory-driven strategies for selective modulation of brain rhythms using: Theoretical disease models and stimulation paradigms Dynamic neuromodulation approaches Wearable devices for remote therapy optimization Advanced signal processing techniques Her recent publications (2015-2025) demonstrate consistent focus on tremor pathophysiology, neural oscillations in Parkinson's disease, and advanced brain stimulation technologies. Research employs computational modeling, EEG, magnetoencephalography, and both invasive/non-invasive stimulation techniques. Awards & Fellowships: Fulbright Scholarship (2000-2004) British Chevening Scholarship (2004) MRC Skills Development Fellowship (2015) MRC Career Development Award (2018) Dr. Cagnan leads an independent research group originally established at the MRC Brain Network Dynamics Unit in 2018, maintaining close collaborations with clinical neuroscientists and engineers to translate basic research into therapeutic applications.

• Neuroscience
• Neuromodulation
• Brain Stimulation
• +4 more

Dr. José del R. Millán is a Professor and holds the Linda Steen Norris & Lee Norris Endowed Chair in Neuroengineering at The University of Texas at Austin's Chandra Family Department of Electrical and Computer Engineering. He also serves as a Professor in Dell Medical School's Department of Neurology, a courtesy Professor in Biomedical Engineering, and is affiliated with the Mulva Clinic for the Neurosciences, Institute for Neuroscience, Texas Robotics, and the UT CARE Initiative. His work focuses on brain-machine interfaces (BMI), neuroprosthetics, and translating BMI technologies for individuals with motor/cognitive disabilities and able-bodied users. Education: PhD in Computer Science (1992, Technical University of Catalonia). Previous roles include Defitech Foundation Chair in Brain-Machine Interface at EPFL (Switzerland) and visiting scholar positions at Berkeley, Stanford, and the International Computer Science Institute. Research Interests: Neuroengineering, BMI applications in healthcare and assistive robotics, statistical machine learning for neural signals, and neurorehabilitation. Key contributions include EEG-based BMI systems, closed-loop neurostimulation, and wearable neurotechnology. Awards: IEEE Fellow (2017), Norbert Wiener Award (2011), and Fellow of the International Academy of Medical and Biological Engineering (2020). Grants & Labs: Co-director of UT CARE, leader in clinical neuroprosthetics and neurorobotics. Active in developing BMI-driven wheelchairs, VR integration for BCI, and EEG-based speech prosthetics. Research outputs emphasize translational neurotechnology, with projects funded by industry and governmental agencies. Labs/Teams: Clinical Neuroprosthetics & Brain Interaction Lab, Texas Robotics, Wireless Networking and Communications Group (WNCG).

• Brain-machine Interfaces (BMI)
• Neuroengineering
• Neuroprosthetics
• +6 more

Barbara Gail Montero is the Rev. John A. O’Brien Professor of Philosophy at the University of Notre Dame, where she holds a faculty position in the Department of Philosophy within the College of Arts and Letters. She earned her BA from the University of California, Berkeley, and her PhD from the University of Chicago. Her research focuses on two core areas: the metaphysical relationship between mind and body, and the role of consciousness in expert action. Notably, she explores how physicalism interacts with abstract entities and how athletes defy skill plateaus through orthogonal models of attention and automaticity. Her key publications include Continuous Improvement: Intertwining Mind and Body in Athletic Expertise (2022, co-authored), A Very Short Introduction: Philosophy of Mind (2021), and Thought in Action: Expertise and the Conscious Mind (2016). She has also published influential papers on pain memory gaps, expertise-induced amnesia, and critiques of flow-state theories. Montero’s interdisciplinary work bridges philosophy with dance performance, as seen in collaborations like Curved Spacetimes: Where Friedrich Nietzsche Meets Virginia Woolf . Her teaching spans philosophy of mind, logic, and science, emphasizing neural plasticity and conscious engagement in expertise.

• Philosophy of Mind
• Philosophy of Body
• Expertise and Consciousness
• +3 more

Daniel M. Wolpert is a Professor of Neuroscience at Columbia University and Principal Investigator at the Zuckerman Institute. His research focuses on computational models of movement, integrating sensory cues and cognitive elements to understand motor control, memory, and rehabilitation strategies for cerebellar disorders. Key Research Areas: Sensorimotor integration, probabilistic inference, reinforcement learning, predictive modeling of movement, and aging effects on motor learning. Selected Awards: Royal Society Fellow (2012), Minerva Golden Brain Award (2010), Fulbright Scholarship (1992-1995). Recent publications highlight his work on contextual learning, motor memory formation, and the computational basis of sensorimotor uncertainty. His lab develops robotic interfaces to study human motor behavior and collaborates on clinical applications for movement disorders. Current opportunities include postdoctoral fellowships in sensorimotor control and decision-making.

• Motor Control
• Computational Neuroscience
• Sensorimotor Learning
• +4 more

Lerrel Pinto is an Assistant Professor of Computer Science at New York University's Courant Institute, where he leads the General-purpose Robotics and AI Lab (GRAIL). His research focuses on enabling robots to generalize and adapt in unstructured environments through advancements in robot learning, decision making, and multimodal sensing. Before joining NYU, he completed a postdoc at UC Berkeley, a PhD in Robotics at Carnegie Mellon University, and an undergraduate degree in Mechanical Engineering at IIT Guwahati. Key research areas include large-scale robot learning, representation learning for sensory data, reinforcement learning for adaptability, and open-source robotics hardware. Notable achievements include the Sloan Fellowship (2025), NSF CAREER Award (2024), and Best Paper Awards at multiple robotics conferences. Pinto's lab has developed influential systems such as the AnySkin tactile sensing framework and the OPEN TEACH teleoperation system. Education highlights include a PhD from CMU (2019) under Abhinav Gupta, a postdoctoral stint with Alexei Efros and Pieter Abbeel at Berkeley, and undergraduate studies at IIT Guwahati. He has authored over 65 publications in top conferences like ICRA, NeurIPS, and CVPR. Pinto teaches courses on robotics, reinforcement learning, and AI at NYU. His service contributions include roles on program committees for ICML, NeurIPS, and IROS, as well as organizing workshops on topics like Dexterous Manipulation and Vision-Language Models for Robotics. His team actively collaborates through the GRAIL lab, with current projects exploring tactile sensing, zero-shot policy deployment, and multimodal robot learning systems. Ongoing research emphasizes bridging the gap between human and robotic dexterity through novel reward structures and adaptive control frameworks.

• Robotics
• Artificial Intelligence
• Machine Learning
• +7 more

Dr. Sander Los is an Associate Professor at the Faculty of Behavioural and Movement Sciences (Department of Cognitive Psychology), Vrije Universiteit Amsterdam. He earned his PhD in 1994 with a thesis on 'On the origin of mixing costs: Exploring information processing in pure and mixed blocks of trials' under Prof. Andries Sanders. His research focuses on temporal dynamics of preparatory processes, co-developing the formalized Multiple Trace Theory (fMTP) to explain temporal preparation across time scales (seconds to days). His work integrates cognitive psychology, neuroscience, and computational modeling to explore attentional mechanisms, statistical learning, and spatiotemporal dynamics. Education: PhD in Cognitive Psychology (VU Amsterdam, 1994), postdoctoral research at VU Amsterdam, progressing to Assistant Professor before his current role. Key research areas include visual attention, response inhibition, and long-term memory. He has published over 40 peer-reviewed articles and serves on editorial boards for journals like Attention, Perception, and Psychophysics and Acta Psychologica . Research Interests: His studies investigate how humans prepare for upcoming events temporally and spatially, with recent work on statistical learning guiding visual attention and computational frameworks for temporal preparation. Collaborations emphasize interdisciplinary approaches to understanding attention allocation and neural underpinnings of timing. Grants & Advising: No explicit grants listed, but active in training students (1 supervised PhD thesis). His courses include Methodology, Research Methods, and Practical Skills for Researchers at VU Amsterdam. Labs/Teams: Works closely with colleagues on the fMTP model and statistical learning projects, emphasizing team-based computational and experimental psychology.

• Temporal Dynamics
• Cognitive Psychology
• Visual Attention
• +6 more

Yang (Gilbert) Ye is an Assistant Professor in the Department of Civil and Environmental Engineering at Northeastern University, joining in January 2025. His research focuses on human-AI/robot teaming, automation in engineering, and assistive technologies, with a particular emphasis on human-centric robotics and sensorimotor processes. He holds a PhD in Civil Engineering from the University of Florida (2024), advised by Dr. Eric Jing Du. **Affiliations**: Member of ASCE, IEEE, and HFES. His work integrates VR/AR, robotics (e.g., drones, exoskeletons), and AI to enhance civil engineering workflows and workforce training. He leads the Ye Lab, actively recruiting PhD students and postdocs with coding experience (Python/C++/C#) and backgrounds in engineering or computer science. **Key Research Themes**: Human-robot interaction, construction automation, exoskeleton training, and delayed feedback mitigation in teleoperation. Over 20 peer-reviewed publications in journals like ASCE JoCEN, IEEE Access, and Advanced Engineering Informatics. **Lab Opportunities**: PhD/postdoc applicants require strong academic records (GPA ≥3.5) and coding skills. Undergrad/master students can apply for thesis/research roles. Funding covers tuition, insurance, and stipends.

• Human-Robot Interaction
• Automation in Engineering
• AI in Construction
• +3 more

Véronique Perdereau is a Full Professor at Sorbonne Université's Institute of Intelligent Systems and Robotics (ISIR) , specializing in robotics and dexterous manipulation. She leads the ASIMOV research team and serves as a principal investigator for multiple European projects, including SOFTMANBOT, INDEX, and CORSMAL, focusing on tactile feedback, multimodal control, and human-robot interaction. Role: Full Professor (2024) Email: veronique.perdereau@sorbonne-universite.fr Office: H13, Campus Pierre et Marie Curie, Paris Research Focus Perdereau's work centers on tactile-driven robotic control systems, human-inspired manipulation strategies, and multimodal fusion for industrial automation. Her research bridges theoretical modeling (e.g., Cosserat mechanics, dual quaternions) with practical applications in manufacturing sectors. Key Themes: Tactile Feedback Systems Dexterous In-Hand Manipulation Human Motion Data Integration Autonomous Grasp Stability Flexible Object Handling Reproducibility in Robotic Experiments Notable Projects She has spearheaded projects like: SOFTMANBOT (2019–2023): Advanced robotic technology for handling soft materials in manufacturing. INDEX (2019–2022): Developing motor action dictionaries for robotic hands. CORSMAL (2019–2022): Multimodal fusion for collaborative object recognition. Scientific Leadership Perdereau has led work packages in 10+ international collaborations with institutions across Europe, including Decathlon, IIT, and Queen Mary University. Her research emphasizes safety, ethics, and industry 4.0 applications.

• Robotics
• Dexterous Manipulation
• Tactile Feedback Systems
• +4 more

John R Anderson is the Richard King Mellon University Professor of Psychology and Computer Science at Carnegie Mellon University (CMU), affiliated with the Department of Psychology within the Dietrich College of Humanities and Social Sciences. His research focuses on understanding higher-level cognition, particularly mathematical problem-solving, through the development of the ACT-R cognitive architecture—a computational framework simulating human cognitive processes. This architecture integrates behavioral, neural, and educational data to model learning and decision-making. Anderson’s work bridges cognitive science, neuroscience, and educational technology. He investigates how brain imaging (e.g., fMRI, EEG) can reveal the temporal dynamics of cognitive processes and improve instructional methods. His research emphasizes analyzing brain activity time courses to uncover underlying mechanisms of problem-solving and skill acquisition. Key Research Themes: Cognitive architectures, neural correlates of learning, computational models of memory, and intelligent tutoring systems. Notable Contributions: Development of the ACT-R architecture, integration of neuroimaging with cognitive modeling, and studies on skill transfer and learning strategies. Anderson’s publications include seminal books like Cognitive Psychology and Its Implications and How Can the Human Mind Occur in the Physical Universe? His work has advanced understanding of associative memory, strategic decision-making, and the application of cognitive models in educational technology. His lab, the ACT-R Research Group, collaborates across disciplines to model complex cognitive tasks and their neural foundations. Current projects analyze real-time brain activity to refine educational interventions and improve human-machine interaction.

• Cognitive Neuroscience
• Cognitive Science
• Computational Psychology
• +3 more

Dr. Kanwaljeet S. Anand is a dual-appointed Professor of Pediatrics (Pediatric Critical Care) and Anesthesiology, Perioperative & Pain Medicine at Stanford University School of Medicine. As director of the Pain/Stress Neurobiology Lab and Jackson Vaughan Critical Care Research Fund, he serves as Editor-in-Chief of Pediatric Research and maintains active membership in Bio-X, MCHRI, and Wu Tsai Neurosciences Institute. Rhodes Scholar with D.Phil from University of Oxford Harvard postdoctoral fellowship and Boston Children's Hospital residency Founded Harmony Health Clinic - Arkansas' largest charitable medical-dental facility A translational researcher with 30+ years of impact, Dr. Anand established the first scientific framework for infant pain perception and developed novel pain assessment methodologies. Current research focuses on: Hair biomarker analysis for stress and social affiliation (cortisol/oxytocin) Machine learning systems for objective pain detection in non-verbal infants Biopsychosocial interventions for stress reduction in disadvantaged youth Neurotoxicity mechanisms of sedatives in developing brains Global NICU opioid usage patterns through the NeoOpioid Consortium His work has yielded over 260 publications and significant advances in: Pediatric pain management protocols Neonatal stress biomarker development Critical care neurobiology insights Community health initiatives AI-driven clinical decision support systems Scientific Recognition 9th Annual 'In Praise of Medicine' Public Address, Erasmus University (2014) Nightingale Excellence Award (2016) Honorary Doctorate from University of Örebro (2019) NIH SBIB-H82 Study Section Chair (2018) Multiple IASP and American Pain Society awards Swedish Academy of Medicine's Nils Rosén von Rosenstein Award (2009) St. Jude Endowed Chairholder (2010) As mentor to Med Scholar Anjali Gupta and advisor to numerous professional bodies, Dr. Anand maintains active clinical leadership in Pediatric Intensive Care while advancing computational approaches to pain detection through collaborations with Stanford's AI researchers.

• Pediatric Pain and Stress Neurobiology
• Neonatal and Fetal Pain Assessment
• Biomarker Development
• +3 more

Andrea Mason is a Professor and Department Chair in the Department of Kinesiology at the University of Wisconsin-Madison. Her research focuses on motor control, particularly in autism spectrum disorder, aging, and virtual environments. She holds the Conway Professorship of Kinesiology (2021) and has received the NSF Career Award (2004). Education: Ph.D. in Human Motor Systems from Simon Fraser University (under Dr. Christine MacKenzie). Her work examines bimanual coordination, gait analysis, and balance training. She leads a lab (visit lab webpage) and collaborates on projects involving robotic-assisted motor assessments and VR feedback for clinical populations. Key research themes include: Motor control in autism Age-related changes in locomotion and grasping Virtual environment interaction Developmental coordination disorders Recent studies explore gait variability in dual-task scenarios, sensory feedback effects in VR, and biofeedback-based balance training for children with autism. Her work bridges kinesiology, neuroscience, and clinical applications. Awards: Conway Professorship (2021), Best Paper (2013), NSF Career (2004) Lab: Accessible via dedicated webpage CV: Downloadable from her portal

• Motor Control
• Autism Spectrum Disorder
• Gait Analysis
• +5 more

Maurice Smith serves as the Gordon McKay Professor of Bioengineering at Harvard University's School of Engineering and Applied Sciences (SEAS), where he leads the Neuromotor Control Lab. His primary appointment resides within the Department of Bioengineering, focusing on the computational and neural mechanisms underlying human movement control. Smith's research centers on sensorimotor learning , motor adaptation , and neuromotor control systems . He investigates how the brain forms and retains motor memories, particularly examining cerebellar contributions to long-term sensorimotor memory and the dissociation between implicit and explicit learning pathways. His work frequently employs computational modeling to dissect neural tuning properties and motor variability regulation. Analysis of his recent publications reveals a strong emphasis on temporal dynamics in motor learning , cerebellar function in memory consolidation , and Bayesian frameworks for understanding sensorimotor adaptation . His research demonstrates consistent focus on how error processing, uncertainty, and neural plasticity shape motor memory formation across multiple timescales. Smith maintains active collaborations with researchers including Wilsaan M. Joiner, Yohsuke R. Miyamoto, and Nathan Sandholtz, as evidenced by frequent co-authorship patterns. His laboratory investigates fundamental questions in motor control with implications for neurorehabilitation and adaptive robotics.

• Motor Control
• Sensorimotor Learning
• Neuromotor Adaptation
• +3 more