Michael J. Shelley is the Lilian and George Lyttle Professor of Applied Mathematics and holds joint appointments in Mathematics, Neural Science, and Mechanical Engineering at New York University's Courant Institute of Mathematical Sciences. He also serves as Co-Director of the Applied Mathematics Laboratory and Director of the Center for Computational Biology at the Flatiron Institute. Education: PhD (Applied Mathematics) from the University of Arizona (1985), MS (Applied Mathematics) from the University of Arizona (1984), BA (Mathematics) from the University of Colorado (1981). Research: Focuses on complex phenomena in active matter, biophysics, and complex fluids. Key areas include fluid-structure interactions (e.g., swimming/flying mechanics), cytoskeletal dynamics, and collective behavior in biological systems. Collaborates closely with experimentalists through the Applied Math Lab and Flatiron Institute. Labs & Affiliations: Co-Director, Applied Mathematics Laboratory; Director, Center for Computational Biology (Simons Foundation); affiliated with NYU’s Courant Institute and Department of Mathematics. Notable Work: Models for microtubule-motor assemblies, active suspensions, and fluid-structure interactions. Pioneered computational frameworks for Stokes suspensions and fiber dynamics in viscous fluids.
Wang Jianmin serves as Professor and Doctoral Supervisor at Tongji University's School of Art and Media, concurrently holding the position of Vice Dean since 2014. With a computer science PhD from Sun Yat-sen University, he bridges engineering and media arts through pioneering research in intelligent communication systems and digital media interfaces. His work focuses on human-centered design for emerging technologies, particularly in automotive and virtual environments. His academic foundation includes: PhD in Engineering (Computer Software and Theory), Sun Yat-sen University (2003) Master's in Computational Mathematics, Sun Yat-sen University (1999) Bachelor's in Computational Mathematics, Nankai University (1996) Professor Wang's research centers on intelligent communication systems and digital media art, with significant contributions to automotive human-machine interfaces (HMI), virtual reality applications, and user experience methodologies. His investigations into driver-robot transparency, augmented reality navigation, and mixed-reality educational platforms demonstrate interdisciplinary innovation connecting computer science, cognitive psychology, and design theory. Current projects explore AI-driven media systems for urban environments and safety-critical interaction frameworks. Analysis of his recent publications reveals a cohesive research trajectory focusing on automotive HMI (40% of output), human-robot interaction (30%), and mixed reality applications (30%). His work consistently emphasizes experimental validation through driving simulators and user studies, yielding practical design guidelines for industry implementation. The interdisciplinary nature spans computer science, cognitive ergonomics, and media studies, with increasing emphasis on AI integration in communication systems. His scientific recognition includes national and provincial awards for innovation in human-computer interaction and educational technology: 2019 China Industry-University-Research Innovation Award for automotive HMI systems 2020 China User Experience Alliance Excellence Award 2012 Guangdong Dingying Science and Technology Award Multiple national/provincial science progress awards (2001-2009) 2020 Tongji University Teaching Achievement Award for curriculum development As an educator, Professor Wang mentors graduate students in national design competitions including the 'Core Cup' Future Automotive HMI Challenge and International User Experience Innovation Competition. His research program is supported by substantial funding from diverse sources: National Grants: National Natural Science Foundation projects on driver behavior modeling and cognitive testing Ministry of Education: 15+产学合作 projects for virtual simulation labs and curriculum development Shanghai Municipal: Publicity Department funding for smart city media research Industry Partnerships: Huawei (intelligent vehicle HMI), SAIC Motor (AR-HUD design), and automotive electronics firms He directs Tongji's Media Experiment and Practice Teaching Center and the All-Media Research Institute, leading teams developing virtual simulation platforms for emergency news reporting, intelligent vehicle interaction testing systems, and mixed reality educational tools. Current initiatives focus on AI-enhanced media art for urban applications and next-generation HMI frameworks for autonomous mobility solutions.
Prof. Stephen Mayhew is a Professor at Aston University's School of Life & Health Sciences, affiliated with the College of Health and Life Sciences. He leads the Cognition & Neuroscience Research Group (CNRG) and contributes to the Aston Research Centre for Health in Ageing. His research focuses on multimodal neuroimaging (EEG/fMRI/MRI/MEG) to study brain activity in health and cognition, particularly negative BOLD responses and their role in neural inhibition and behavior. Recent work includes investigating task-demand effects on BOLD responses, brain state dynamics during rest, and neurovascular coupling methods. Education & Affiliations: Affiliated with Aston University's School of Life & Health Sciences Member of CNRG and Health in Ageing Centre Research Interests: His work explores collaborative/antagonistic brain networks, lifespan changes in brain function, and the functional significance of negative BOLD responses. Techniques include fMRI, EEG, and advanced neuroimaging analysis methods like fractal dimension and laminar 7T MRI. Key Contributions: Published over 30 peer-reviewed articles on neuroimaging and brain networks Systematic reviews on neurovascular coupling and transcranial Doppler methods Labs & Teams: Active in CNRG and collaborates across disciplines in health sciences and bioengineering.
Leif Ristroph is an Assistant Professor of Mathematics at the Courant Institute of Mathematical Sciences , New York University . His research bridges experimental physics and applied mathematics , focusing on fluid-structure interactions in both biological and geophysical contexts. Key research areas include: Biophysical Flows : Aerodynamics of insect flight ( Applied Mathematics Laboratory ), hydrodynamics of fish schooling, and flow-sensing mechanisms via the fish lateral line system Geophysical Flows : Shape evolution during erosion, dissolution patterns in fluid flows, and bubble formation dynamics Recent publications (2019-2015) explore: Flow interactions in flapping swimmers and hovering systems Evolutionary optimization of wing shapes and self-sculpting processes Stability mechanisms in tandem flapping and insect flight His work has been featured in major media outlets like Nature , New York Times , and ScienceDaily . Ristroph's lab at NYU's Applied Mathematics Laboratory combines physical experiments, computational models, and theoretical analysis to study complex fluid-structure interactions.
Aravind Rajeswaran is a Research Scientist at Meta AI (FAIR) and Visiting PostDoc/Collaborator at Berkeley AI Research Lab (BAIR) at UC Berkeley's College of Engineering, Department of Electrical Engineering and Computer Sciences. He completed his PhD in Computer Science at the University of Washington under Profs. Sham Kakade and Emo Todorov, with additional collaborations with Sergey Levine and Chelsea Finn, and previously earned his bachelor's degree with the best undergraduate thesis award from IIT Madras working with Balaraman Ravindran. His research focuses on building generalist AI agents that operate in open worlds, combining reinforcement learning, representation learning, and world models. Key projects include Locate 3D for real-world object localization, OpenEQA for embodied question answering with foundation models, VC-1 as an artificial visual cortex for embodied intelligence, and R3M as a universal visual representation for robot manipulation. His work demonstrates how pre-trained visual representations can significantly enhance robotic capabilities with minimal supervision. Rajeswaran's publication record shows consistent high-impact contributions across premier AI conferences including NeurIPS, ICML, CVPR, and RSS from 2018 through 2025, with research spanning reinforcement learning, representation learning, robotics, and computer vision. His work on Decision Transformer demonstrated how sequence modeling frameworks can effectively train reinforcement learning policies. Best Paper Award, Scaling Robot Learning Workshop at ICRA 2022 best undergraduate thesis award from IIT Madras As an educator and mentor, Rajeswaran has guided numerous PhD students who have gone on to positions at Stanford, MIT, CMU, Berkeley, and top AI companies including Meta, DeepMind, and Anthropic. He designed and co-taught the Deep Reinforcement Learning course (CSE599G) at UW in 2018, with materials adopted by courses at MIT and CMU, and served as lead TA for Machine Learning for Big Data (CSE547). His research has been supported through his role as Principal Investigator for the Cortex Team at FAIR.
Prof. Helen Blank is a Professor leading the Multisensory Perception Group and the Prediction in Communication Lab at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf. Her work focuses on understanding how sensory information is integrated and predicted in contexts like speech perception and face recognition. She holds a Marie Curie Fellowship for her research on prior information's role in human communication. Fluent in German, English, and French, she contributes to experimental medicine and systems neuroscience. Her research spans predictive coding, neuroimaging, and clinical applications in Parkinson’s and developmental disorders. Education: Not explicitly stated in text, inferred as advanced degrees in neuroscience or related fields. Her research interests emphasize multisensory integration, predictive processing in speech and vision, and the neural bases of perception. Recent articles explore topics such as pupil responses to auditory surprise, face expectation hierarchies, and audio-visual speech processing. Awards include the Marie Curie Fellowship supporting her predictive communication work. She leads interdisciplinary teams within the Center for Experimental Medicine, advancing knowledge on perceptual mechanisms and their clinical implications.
Deanne L. Westerman is a Professor and Cognitive Area Coordinator in the Department of Psychology at Binghamton University. Her research focuses on human memory processes, particularly recognition memory, familiarity, and attributional factors influencing memory decisions. She holds a PhD and MA from Case Western Reserve University and a BS from John Carroll University. Her work explores how perceptual and conceptual fluency impact memory judgments, with recent studies examining effects of photos/screenshots on memory impairment and emotional image processing. She has received the Chancellor's Award for Excellence in Teaching (2002-2023). Currently accepting graduate students for Fall 2024. Key research areas: Recognition memory, metamemory, cognitive bias, and memory illusions. Methodological expertise includes experimental design, memory paradigms, and cognitive neuroscience techniques.
Frank Russo is a Professor in the Department of Psychology at Toronto Metropolitan University, where he holds the NSERC-Sonova Senior Research Chair in Auditory Cognitive Neuroscience. He leads the Science of Music Auditory Research and Technology (SMART) Lab and holds affiliate and adjunct positions at the University Health Network and the University of Toronto, respectively. Research Interests: Dr. Russo's work lies at the intersection of auditory cognitive neuroscience, music psychology, and rehabilitation. His research explores how humans perceive music and speech, particularly under challenging conditions such as hearing loss or non-native accents. He investigates the cognitive and neural mechanisms of listening effort, emotional speech processing, and the social and therapeutic benefits of music, especially through community choirs and digital interventions. Publication Trends: His recent publications emphasize objective measurement of listening effort using functional near-infrared spectroscopy (fNIRS), music-based interventions for Parkinson’s disease and dementia, vocal and emotional responses to singing, and multisensory integration in beat perception. The work is highly translational, bridging basic cognitive neuroscience with clinical and community applications. Scientific Awards and Honors: NSERC-Sonova Senior Research Chair in Auditory Cognitive Neuroscience Fellow of the Canadian Psychological Association Fellow of Massey College Fellow of the Canadian Society for Brain, Behavior and Cognitive Science Past President of the Canadian Acoustical Association Advising and Grants: Dr. Russo actively mentors students and researchers, as evidenced by his co-authorship with numerous junior colleagues. He has secured major funding through NSERC and industry partnerships, enabling the development of impactful technologies such as hearing aid algorithms, sensory substitution systems, and digital therapeutics. His SingWell project fosters collaboration across academic, clinical, and community sectors. Labs and Teams: He directs the SMART Lab at Toronto Metropolitan University, a hub for interdisciplinary research on music, hearing, and cognition. The lab collaborates extensively with KITE Research Institute, Rehabilitation Sciences at the University of Toronto, and various community organizations focused on aging, hearing loss, and neurodegenerative conditions.
Dr. Emma Axelsson is a Lecturer at the School of Psychological Sciences, University of Newcastle, Australia. Her research focuses on cognitive and social development in typically and atypically developing children, with specific interests in early word learning, sleep-related memory consolidation, screen time effects on development, and infants' social category representations using eye-tracking technology. Doctor of Philosophy, University of East London Bachelor of Arts (Honours in Psychology), University of Queensland Dr. Axelsson's research spans multiple disciplines including cognitive neuroscience, memory and attention, and child development. She explores how sleep patterns interact with learning outcomes, investigates screen time's impact on preschoolers' cognition, and examines visual processing of bodies and faces in developmental contexts. Her recent publications highlight trends in screen time research, with 2025 studies analyzing executive function and sleep interactions, and 2024 work examining cross-species social evaluation mechanisms. Earlier articles (2022-2013) cover temperament effects on word learning, body perception mechanisms, and longitudinal developmental studies. Dr. Axelsson supervises multiple PhD and Masters projects related to screen time, sleep, and neurodevelopmental outcomes. Her research team collaborates internationally through networks like ManyBabies and Healthy Minds (Hunter Medical Research Institute).
Dr. Todd D. Murphey is a Professor of Mechanical Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He serves as Director of Transformative Research and Director of the Master of Science in Robotics Program at Northwestern, leading initiatives in computational dynamics, control systems, and robotics. His work bridges engineering, neuroscience, and biomedical applications, with a focus on developing systems that interact effectively with humans and their environments. Dr. Murphey received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 2002, with a thesis titled "Control of Multiple Model Systems." Prior to that, he earned a B.S. in Mathematics, summa cum laude, from the University of Arizona in 1997. Dr. Murphey's research centers on computational methods in dynamics and control, with applications spanning neuroscience, health science, robotics, and automation. His work in the Interactive & Emergent Autonomy Lab focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. The group develops mathematical approaches that lead to orders of magnitude improvement in computational efficiency for real-time implementation. Key application areas include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. Analysis of Dr. Murphey's recent publications reveals a strong emphasis on human-swarm interaction, algorithmic matter, and control of cyber-physical systems in uncertain environments. His work increasingly integrates information theory with physical systems, exploring how both autonomous and biological systems interact with environments to learn and improve behaviors. Recent trends show growing applications in rehabilitation technology, with particular focus on human-machine interaction in biomedical devices and embodied intelligence. Dr. Murphey has received numerous honors and awards for his contributions to robotics and engineering: Named Director of Transformative Research at Northwestern University (2025) Appointed IEEE Robotics and Automation Society Vice President of Publication Activities (2022) Co-recipient of Best Paper Award for IEEE Transactions on Robotics (2020) Appointed to Air Force Scientific Advisory Board (2019) Recipient of ABB Best Student Paper Award for CPL-SLAM research (2019) Cole-Higgins Award from Northwestern Engineering (2015) Dr. Murphey has supervised numerous graduate students including Taosha Fan, Giorgos Mamakoukas, and Ian Abraham, with research spanning robotic exploration using electrosense and mechanical contact, human-in-the-loop control, and shared control for rehabilitation devices. His lab has secured significant funding from the National Science Foundation, DARPA, and industry partners including Siemens and Ekso Bionics, supporting research in algorithmic matter, emergent behavior, and human-swarm collaboration. The Interactive & Emergent Autonomy Lab, led by Dr. Murphey, investigates how both autonomous systems and biological systems interact with their environments to learn and improve behaviors. Current projects include active learning and data-driven control, active perception in human-swarm collaboration, algorithmic matter and emergent computation, control for nonlinear and hybrid systems, cyber physical systems in uncertain environments, harmonious navigation in human crowds, information maximizing clinical diagnostics, reactive learning in underwater exploration, robot-assisted rehabilitation, and software-enabled biomedical devices. The lab collaborates with researchers across Northwestern and institutions including Georgia Tech, MIT, and industry partners.
Prof. Wouter Roos is a Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Molecular Biophysics department at the Zernike Institute for Advanced Materials. His research focuses on viral dynamics, membrane assemblies, and protein mechanics, utilizing advanced techniques like High Speed Atomic Force Microscopy (HS-AFM) and optical tweezers. Education: Studied Physics at the Universiteit van Amsterdam, earned a PhD from the Universität Heidelberg under Joachim Spatz. Conducted postdoctoral research at Max-Planck-Institut, Institut Curie, and Vrije Universiteit before joining Groningen in 2015. Research Interests: Physical Virology (viral material properties and dynamics), membrane biophysics (synthetic cells and lipid interactions), and molecular motor systems. His work bridges physics, chemistry, and biology to understand nanoscale biological processes. Recent Article Trends: Studies on hybrid membranes for synthetic cells, leukemic cell mechanics, and antibiotic-membrane interactions highlight his interdisciplinary approach. Key techniques include HS-AFM and single-particle tracking. Awards: Received a VIDI grant and multiple national/international grants. His lab leads the oLife Co-Fund consortium and participates in the MOSBRI research infrastructure. Grants & Leadership: Coordinates the oLife Fellowship Programme and chairs the Molecular Biophysics Lab. Active in steering committees for EU-funded initiatives. Labs/Teams: Heads the Molecular Biophysics Lab, focusing on viral dynamics and membrane systems. Collaborates globally on projects like ESCRT-III polymerization and antibiotic mechanisms.
Ian Greenhouse serves as an Assistant Professor in the Department of Human Physiology within the College of Arts and Sciences at the University of Oregon. He directs the Action Control Laboratory, where he investigates the neurophysiological mechanisms underlying human movement initiation and cancellation using multimodal approaches including electrophysiology, neuroimaging, and brain stimulation. Education: Undergraduate degree in Psychology from Tufts University Ph.D. from the University of California, San Diego Postdoctoral training at the University of California, Berkeley Research Focus: Dr. Greenhouse's work centers on action control neurophysiology , specifically examining motor inhibition processes during response stopping and preparation. His lab employs electromyography (EMG) , transcranial magnetic stimulation (TMS) , and magnetic resonance spectroscopy (MRS) to probe corticospinal excitability in healthy and clinical populations. Key investigations include neural computations for action preparation, biomarkers of stopping failure, and relationships between motor performance and brain chemistry (e.g., GABA). Publication Trends: Analysis of Dr. Greenhouse's 2022-2025 publications reveals intensified focus on subcomponents of response inhibition (pause vs. cancel processes) and neurochemical modulation of motor control. His work increasingly integrates menstrual cycle effects on GABA with action stopping metrics, while maintaining core investigations of corticospinal dynamics during unimanual/bimanual preparation. Recent studies show growing clinical applications in stroke rehabilitation. Scientific Awards: No awards were documented in the source materials. Advising and Research: As laboratory director, Dr. Greenhouse mentors students in the Action Control Laboratory's research program. Although specific grants aren't detailed, his high-output publication record spanning neuroimaging, electrophysiology, and clinical applications suggests sustained external funding for equipment-intensive neuroscience research. Laboratory Operations: The Action Control Laboratory (https://actioncontrollab.uoregon.edu) operates from Gerlinger Hall (Room 348), utilizing TMS-EMG integration, MRS, and behavioral paradigms to study action control. Current projects examine preparatory inhibition in stroke recovery, interhemispheric dynamics during movement preparation, and individual differences in stopping processes using the stop-signal task framework.
Jeffrey L. Krichmar is a Professor in the Department of Cognitive Sciences and Department of Computer Science at the University of California, Irvine. His academic journey includes a B.S. in Computer Science from the University of Massachusetts Amherst (1983), an M.S. in Computer Science from The George Washington University (1991), and a Ph.D. in Computational Sciences and Informatics from George Mason University (1997). Prior to UCI, he served as Assistant Professor at George Mason University (1997-1999) and Senior Fellow at The Neurosciences Institute (1999-2007). University of California, Irvine (2007-present) George Mason University (1997-1999) The Neurosciences Institute (1999-2007) His research focuses on neurorobotics , exploring how embodied cognition and biologically plausible neural models can enhance robotic systems. Key areas include spiking neural networks , neuromodulation , path planning , and interactive tactile robots for therapeutic applications. His work bridges neuroscience , robotics , and cognitive science , with applications in autonomous vehicles , neuroprosthetics , and AI explainability . Recent publications emphasize spiking neural networks for navigation , neuromodulated attention , and neuromorphic hardware integration. The development of CARLsim, a GPU-accelerated spiking neural network simulator now in version 6.0, represents a major technical contribution. His team's work on socially assistive robots like CARL-SJR targets therapeutic applications for autism and ADHD. Scientific Awards IJCNN 2020 Best Paper Award Finalist for Best Student Paper at IJCNN 2018 Best Paper Award at IEEE IJCNN 2009 Grants include National Science Foundation funding for neural models of decision-making (2009). His lab (Cognitive Anteater Robotics Laboratory) develops systems that use large-scale brain simulations for autonomous behavior , with applications in adaptive robotics , sensorimotor learning , and neuroethology . Current projects explore neuromodulatory influences on attention systems and cognitive flexibility .
Dr. Aaron Schurger is an Assistant Professor in the Psychology Department at Chapman University’s Crean College of Health and Behavioral Sciences. He is also a member of the Institute for Interdisciplinary Brain and Behavioral Sciences. Schurger holds a BA from Indiana University, and MA and PhD from Princeton University. His research focuses on the neuroscience of volition, consciousness, and decision-making, particularly exploring the readiness potential (RP) and its implications for free will debates. His work challenges classical interpretations of the RP using computational models, suggesting it reflects stochastic neural processes rather than preconscious decisions. Recent contributions include studies on the origins of the RP in spiking neural networks, critiques of causal structure theories of consciousness, and interdisciplinary analyses of free will. His findings emphasize that the RP may not indicate preconscious decision-making but instead arise from natural neural fluctuations during decision thresholds. Schurger collaborates across neuroscience, philosophy, and cognitive science, contributing to debates on consciousness, action initiation, and neural correlates of subjective experience. His research also addresses methodological rigor in studying unconscious processing and integrates computational models with empirical data, as seen in studies on movement timing and neural stability during perception. While no specific grants or labs are explicitly listed, his affiliations suggest involvement in interdisciplinary projects at Chapman.
Kris Baetens is a Professor in the Department of Psychology Brain, Body and Cognition at Vrije Universiteit Brussel (VUB). His research focuses on the neural mechanisms underlying social cognition, mentalization, and inhibitory control, particularly exploring the role of the cerebellum and prefrontal cortex in these processes. He employs techniques such as transcranial direct current stimulation (tDCS), EEG, and fMRI to investigate cognitive and clinical phenomena. Leading projects like ANI423 (neural correlates of inhibitory control in adolescents) and FWOAL1160 (cerebellum's role in social cognition). Recipient of the EUTOPIA Young Leaders Academy fellowship (2024-2026). Active collaborations in the PRISM network for mental health research. Key research interests include: - Cerebellar contributions to cognitive and social functions - Neurostimulation techniques for mental health interventions - Mentalizing processes in social action prediction - Personality and learning mechanisms His articles consistently analyze the interplay between neural structures like the cerebellum and behavioral outcomes in clinical and cognitive contexts. Recent work emphasizes applications of tDCS in treating alcohol use disorders and disordered eating, highlighting translational research in non-invasive brain stimulation. Advising/Grants: Supervises student research projects and manages grants from FWO and OZR agencies. Labs/Teams: Core member of the PRISM network and involved in the EUTOPIA fellowship initiative.
