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Roozbeh Tabrizian is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Florida, holding the Nelms Rising Star Endowed Professorship. His research focuses on RF micro- and nano-electro-mechanical systems (RF N/MEMS), nonlinear and nonreciprocal systems, and ferroelectric materials for sensing and information processing. He has received prestigious awards including the NSF CAREER Award (2018) and DARPA Young Faculty Award (2019). Education: PhD in Electrical Engineering from Georgia Tech (2013), BS from Sharif University of Technology (2007). Research interests include developing temperature-stable acoustic resonators, ferroelectric transducers, and novel materials for high-frequency applications. His work bridges nanotechnology, materials science, and MEMS to create innovative devices for communication and sensing. Key scientific awards include the HWCOE Innovation Award (2025), DARPA Director’s Fellowship (2021), and multiple best paper awards at international conferences. His grants include the NSF CAREER Award supporting nano-acoustic waveguide research. He advises on advanced MEMS fabrication techniques and collaborates on CMOS-compatible resonators. His lab develops nanoelectromechanical tags for anti-counterfeiting and high-precision frequency control systems.

• RF Micro/Nano-Electro-Mechanical Systems (RF N/MEMS)
• Nonlinear and Nonreciprocal Systems
• Ferroelectric Materials and Devices
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Saerom Lee is an Associate Professor of Marketing at the Gordon S. Lang School of Business and Economics, University of Guelph. She holds a PhD in Marketing from the Smeal College of Business at Pennsylvania State University and previously served as an Assistant Professor at the University of Texas at San Antonio. Her research explores identity, social influence, and social motivations in consumer decisions, with a focus on prosocial behavior, sustainable consumption, and well-being. Key areas include how touchscreens affect support for social causes, marketplace morality, and the psychology behind luxury consumption in professional settings. Dr. Lee has published in top-tier journals like the Journal of Consumer Research and Journal of Marketing Research , receiving awards from the Academy of Marketing Science, American Marketing Association, and others. She serves on editorial review boards for Journal of Marketing Research and Journal of Retailing . Education: PhD in Marketing, Pennsylvania State University Her work bridges consumer psychology and social responsibility, with grants and collaborations in sustainable behavior and ethical decision-making. She advises students in the Department of Marketing and Consumer Studies, fostering interdisciplinary research on modern consumption trends.

• Consumer Behavior
• Marketing
• Social Psychology
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Peter Avitabile is a Research Professor in the Mechanical and Aerospace Engineering Department at Michigan Technological University and a Professor Emeritus at the University of Massachusetts Lowell. With nearly five decades of experience, his expertise spans structural dynamics, vibrations, and modal analysis. He has contributed over 350 technical papers and authored Modal Testing: A Practitioner’s Guide . Dr. Avitabile holds a DEng from UMass Lowell and has led the Structural Dynamics and Acoustic Systems Laboratory. He is a Fellow of the Society for Experimental Mechanics (SEM) and served as its President in 2016. Education: DEng, Mechanical Engineering, University of Massachusetts Lowell (1998) MS, Mechanical Engineering, University of Rhode Island (1982) BS, Mechanical Engineering, Manhattan College (1974) Research Interests: Structural dynamic modeling techniques, experimental modal analysis, system modeling, reduced order modeling, and model correlation. Awards: SEM DeMichele Award (2004) Fellow, Society for Experimental Mechanics (2022) UMASS Lowell Pillars of Excellence Award (2016) Grants & Funding: Over $9.3 million in research funding since 2000, alongside substantial hardware/software donations. His work has been supported by industries and government agencies including NASA, the Department of Energy, and the Navy. Teaching & Mentorship: Taught over 30 semesters of graduate courses in structural dynamics and modal analysis at UMass Lowell. Advised 18 PhD and 19 MS students. Conducted international seminars on structural dynamics for companies like NASA, General Motors, and Siemens. Labs & Affiliations: Co-Director, Structural Dynamics and Acoustic Systems Lab (UMass Lowell) Director, Modal Analysis and Controls Lab (UMass Lowell)

• Structural Dynamics
• Vibrations
• Modal Analysis
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Dr. Brady Nelson is an Associate Professor in the Department of Psychology at Stony Brook University, specializing in clinical affective neuroscience. He holds a Ph.D. from the University of Illinois at Chicago (2013). His primary research examines the neural mechanisms underlying anxiety disorders and depression, focusing on reward sensitivity and unpredictable threat reactivity in developmental populations. Key methodologies include EEG, fMRI, and psychophysiological measures. Current projects include the iPANDA longitudinal study tracking reward sensitivity and depressive symptoms in adolescent girls. Dr. Nelson has secured $9.1 million in federal research funding since 2018, including NIH grants for studies on psychopathology biomarkers and pandemic mental health impacts. He directs the Laboratory for Clinical Affective Neuroscience and has authored over 80 peer-reviewed articles. His work emphasizes translational neuroscience, bridging basic research to clinical applications for mental health prevention and intervention. Active grants include investigations into maternal parenting interventions and the neurobiological foundations of internalizing disorders. Dr. Nelson advises on graduate studies but will not review applications for the 2025-2026 academic year.

• Affective Neuroscience
• Psychophysiology
• Anxiety Disorders
• +3 more

Prof Noel O'Connor is a Full Professor at Dublin City University's School of Electronic Engineering, specializing in cutting-edge research at the intersection of artificial intelligence (AI), medical imaging, robotics, and smart city technologies. His work spans applications such as cardiac MRI reconstruction, robotic manipulation using reinforcement learning, and the development of the Smart DCU Digital Twin for autism-friendly university environments. Research interests include AI-driven medical diagnostics, multimodal data fusion, and adaptive systems. His contributions to cardiac MRI reconstruction and transformer-based medical imaging analysis reflect a strong focus on healthcare innovation. He also explores ethical AI practices to reduce social bias in foundation models. Recent work emphasizes smart infrastructure projects, such as optimizing parking recommendations for electric vehicles and enhancing accessibility through digital twin frameworks. His research often integrates real-time sensor data and multi-agent systems to address complex urban challenges. No scientific awards are listed. Collaborations include the ASU-DCU International Research Program on Sensors and Machine Learning. Advising details and grant information are not explicitly provided.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +4 more

Geir Olav Dyrkolbotn is an Associate Professor at NTNU's Center for Cyber and Information Security (CCIS) and a Major in the Norwegian Armed Forces, serving at the Norwegian Defence Cyber Academy (NDCA). He leads the NTNU Malware Lab and the cyber defence research group at CCIS. He holds a PhD in Information Security from Gjøvik University College and a MSc in Computer Science from NTNU. With over 25 years in the military, his work focuses on tactical communication systems, defensive cyber operations, and operational security. His research emphasizes cyber defence, reverse engineering, malware analysis, side-channel attacks, and machine learning applications. Education: PhD in Information Security, Gjøvik University College (HiG) MSc in Computer Science, NTNU Research Interests: Geir Olav's work bridges theoretical cybersecurity research and practical military applications. He explores innovative methods for hardware reverse engineering, malware detection/classification using low-level features, and forensic acquisition techniques. His contributions include analyzing USB power delivery vulnerabilities, NTFS cluster allocation behavior, and secure chip exploitation for digital forensics. Teaching: Courses include IIKG6500/IMT4213 Cyber-taktikk, IMT4214 Cyber-etterretning, IIKG6501 Cyber Intelligence, and IMT4116 Malware Analysis & Reversing. Labs & Teams: Heads the NTNU Malware Lab and leads the cyber defence research group at CCIS, collaborating on projects like the Digital Forensic Acquisition Kill Chain and hardware security vulnerability assessments.

• Cyber Defence
• Reverse Engineering
• Malware Analysis
• +5 more

Dr. Stefon van Noordt is an Assistant Professor in the Department of Psychology at Mount Saint Vincent University. His research focuses on understanding brain-based markers of attention control and performance monitoring, particularly in developmental and individual differences contexts. He integrates behavioral, imaging, and computational tools to study neural dynamics in normative and pathological states like anxiety. His work is supported by NSERC, CIHR, and other institutions. He holds postdoctoral training from McGill University and Yale University. Education includes a Ph.D. in Psychology (2016) from Brock University, with postdoctoral fellowships at the Montreal Neurological Institute and Yale Child Study Centre. His research emphasizes EEG analysis, autism risk prediction, and medial frontal theta oscillations. Research interests span cognitive neuroscience, developmental psychology, and neuroimaging, with a focus on EEG methodologies and their application to autism spectrum disorder. Recent work includes studies on infant EEG connectivity, social exclusion effects, and neural responses to peer feedback. Dr. van Noordt collaborates on projects like the EEG-IP platform for international infant data integration and has published extensively on EEG biomarkers and neurodevelopmental trajectories. He mentors students in Honours thesis projects and postdoctoral training.

• Cognitive Neuroscience
• Developmental Psychology
• Neuroimaging
• +3 more

Patrick Bennett is a Professor in the Department of Psychology, Neuroscience & Behaviour at McMaster University , focusing on visual perception, aging, and cognitive neuroscience. His research explores how aging affects visual processing mechanisms, face identification, and perceptual learning. Key Research Areas : Aging effects on vision, Face processing, EEG dynamics, Biological motion perception, Perceptual learning Recent Publications : Analyzed visual crowding in older adults (2025), Investigated 3D target detection mechanisms (2024), Studied face mask impacts on emotion recognition (2023) Teaching : Instructs advanced statistics and research design courses for psychology students. His work combines computational methods with behavioral experiments to understand neural processing changes across the lifespan.

• Visual Perception
• Aging and Cognitive Neuroscience
• Face Identification
• +3 more

Paul Nuyujukian serves as an Assistant Professor of Bioengineering and Neurosurgery, with courtesy appointment in Electrical Engineering at Stanford University. He is a Faculty Scholar of the Wu Tsai Neurosciences Institute, directing the Brain Interfacing Laboratory where his team develops neural interface technologies for clinical applications in stroke and epilepsy. Education: MD, Stanford University (2014) PhD in Bioengineering, Stanford University (2012) BS, UCLA (2006) Dr. Nuyujukian's research integrates motor systems neuroscience with neuroengineering to decode brain activity during movement and recovery from injury. His laboratory pioneers brain-machine interface (BMI) platforms that translate neural signals into communication and control systems, with particular emphasis on intracranial EEG recording and real-time neural decoding. Current work focuses on developing clinically viable BMI solutions for neurological conditions through both preclinical models and human trials, advancing our understanding of neural population dynamics in health and disease. Recent publications reveal strong trends in intracranial EEG acquisition systems, seizure detection algorithms using information theory, and closed-loop BMI applications for ambulatory neuroscience. His work bridges fundamental neuroscience with clinical translation, particularly in epilepsy monitoring, chronic pain management, and neural prosthetics for paralysis. A notable emphasis exists on creating scalable, minimally invasive recording platforms that reduce clinical burden while maintaining high-fidelity neural data. Scientific Awards: No specific awards listed in provided materials As director of the Brain Interfacing Laboratory, Dr. Nuyujukian mentors students and collaborators in neural engineering research while securing grant funding for BMI development. His group maintains active collaborations with Stanford's Department of Neurosurgery and Neurology for clinical translation, with current projects including real-time decision-state decoding and personalized network mapping for pain management. The laboratory operates advanced facilities for both animal and human neural recording, emphasizing seamless integration of engineering innovation with clinical neuroscience. The Brain Interfacing Laboratory comprises multidisciplinary scientists and engineers developing next-generation neural interfaces. Current initiatives include the LiCoRICE platform for ambulatory neuroscience, seizure detection systems using compression-enabled entropy estimation, and ketamine's effects on hippocampal connectivity. The team actively participates in clinical trials for BMI applications in stroke rehabilitation and epilepsy, with strong partnerships across Stanford's medical and engineering schools to accelerate technology translation.

• Motor Systems Neuroscience
• Neuroengineering
• Brain-Machine Interfaces
• +4 more

Rosario B. Jaime-Lara is an Assistant Professor at the University of California, Los Angeles (UCLA) School of Nursing. She holds advanced degrees including a PhD in Nursing from the University of Pennsylvania, MSN from Columbia University, and dual BS degrees in Nursing and Biological Sciences from University of Pennsylvania and UC Davis. Her research focuses on neurophysiological mechanisms of eating behavior, nutritional disparities in Mexican-American communities, and chemosensory science. Key themes include obesity research, sensory neuroscience, and translational clinical studies. She employs rodent models and clinical research methodologies to explore taste/smell physiology and metabolic health. Jaime-Lara has received over 17 honors including the 2022 Hommer Memorial Award and multiple diversity fellowships. Her work spans interdisciplinary collaborations in genomics, microbiome research, and health IT interventions for chronic disease management. Recent publications emphasize olfactory dysfunction in coronaviruses, fat taste mediators, and metabolic profiling. Her research bridges basic science and clinical practice, with particular attention to underserved populations.

• Nutrition
• Neurophysiology
• Obesity Research
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Neil Lin is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of California, Los Angeles (UCLA), with a joint appointment in Bioengineering. His research focuses on developing 3D-printed tissues that replicate the structure, mechanics, and functionality of human organs, with applications in drug screening and regenerative medicine. Lin leads the Lin Lab - Living Soft Material Engineering , advancing soft and living material engineering through interdisciplinary approaches. Lin holds a Ph.D. and M.S. in Engineering from Cornell University (2016 and 2013) and a B.S. in Engineering from National Tsing Hua University, Taiwan (2008). His work spans biomaterials mechanics, quantitative imaging, and AI-driven biological analysis. Research interests include the structure and dynamics of soft biomaterials, image-based force measurements, and quantitative imaging techniques for material characterization. Recent work explores cell morphology regulation, AI applications in microscopy, and mechanical heterogeneity in live tissues. Lin’s publications highlight advancements in cell trapping, AI-based image translation, and prostate cancer metabolism modeling. He has received prestigious awards, including the Young Investigator Award (2022), Hellman Fellowship, and NIH Maximizing Investigators' Research Award (2022). His lab integrates engineering and biology to address challenges in tissue engineering, with ongoing projects on 3D kidney models, drug response assays, and AI-driven phenotyping of senescent cells.

• Biomedical Engineering
• Tissue Engineering
• 3D Printing
• +5 more

Professor David Bannerman is a leading academic in Behavioral Neuroscience at the University of Oxford's Department of Psychiatry. He heads the Behavioural Neuroscience Unit, focusing on neural mechanisms underlying anxiety, learning, and memory. His research integrates neurophysiological, genetic, and pharmacological approaches to study neuropsychiatric disorders such as Alzheimer’s, schizophrenia, and sleep disturbances. Education: BSc (Hons) and PhD qualifications are listed. His research interests span synaptic plasticity, neurodegenerative processes, and the neurobiology of fear/anxiety. Notable areas include the role of orexin pathways in anxiety, tau protein effects on spatial cognition, and the impact of psychedelics like 5-MeO-DMT on neural states. He also investigates sleep spindles’ role in brain state regulation and the consequences of SSRI discontinuation on serotonergic systems. Recent work emphasizes Alzheimer’s disease mechanisms (e.g., amyloid β’s synaptic effects), schizophrenia models (NMDA receptor dysfunction), and the neuroplasticity linked to working memory training. His lab employs cutting-edge techniques, including optogenetics and in vivo neural recordings, to dissect complex behaviors and circuit-level dysfunction. His publications highlight interdisciplinary approaches, bridging basic neuroscience with translational research. Key themes include: synaptic dysfunction in neurodegeneration, environmental influences on neurobehavioral outcomes (e.g., magnetic fields), and the neurobiological basis of psychiatric symptomatology.

• Behavioral Neuroscience
• Neurobiology of Anxiety
• Synaptic Plasticity
• +4 more

Nilanjan Sarkar is the Vice Dean and Senior Associate Dean for Faculty Affairs at Vanderbilt University's School of Engineering, holding the David K. Wilson Professorship in Engineering. He is a Professor in Mechanical Engineering, Computer Engineering, and Computer Science. His research focuses on intelligent systems for human interaction, including robotics, virtual/augmented reality, and assistive technologies for neurodevelopmental disorders and aging populations. Education: PhD (Mechanical Engineering, University of Pennsylvania), ME (Indian Institute of Science), BE (Indian Institute of Engineering Science and Technology, Shibpur). Research interests span human-robot interaction, sensor fusion, and rehabilitation engineering. His lab develops systems for autism intervention, stroke rehabilitation, and elderly engagement through socially assistive robotics and VR/AR. Notable projects include robot-mediated therapy for children and AR telepresence systems for long-term care facilities. Labs/Teams: Robotics and Autonomous Systems Laboratory. Key contributions include CoMove, RASSLE, and the Career Interview Readiness in VR platform. His work emphasizes participatory design with end-users for ethical and inclusive technology.

• Human-Robot Interaction
• Human-Computer Interaction
• Robotics
• +6 more

Diogo Almeida is an Associate Professor of Psychology and Global Network Associate Professor of Psychology at New York University Abu Dhabi. His research focuses on neurolinguistics and language processing, employing methodologies such as MEG/EEG, fMRI, and cross-linguistic studies. He holds an MSc in Cognitive Science from the Ecole des Hautes Etudes en Sciences Sociales and an PhD in Linguistics from the University of Maryland, College Park. Prior to NYU Abu Dhabi, he held positions at the University of California, Irvine, and Michigan State University. Almeida’s research explores perceptual processes underlying language understanding, including syntactic structure processing, agreement phenomena, and the neural bases of lexical access. His work integrates behavioral experiments with neuroimaging techniques to investigate how linguistic structures are represented in the brain. Key areas include sentence processing selectivity in Broca’s area, cross-linguistic differences in agreement encoding, and the role of phonological and morphological features in real-time language comprehension. His publications span topics like masked priming effects, sociolinguistic influences on speech perception, and the reliability of experimental syntax methods. He leads the Language, Mind and Brain research group at NYU Abu Dhabi, focusing on interdisciplinary approaches to language cognition. Almeida has contributed to debates on empirical rigor in syntax, advocating for robust experimental designs and large-scale data collection to validate theoretical claims.

• Neurolinguistics
• Language Processing
• Cognitive Science
• +3 more

Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.

• Biometric Technologies
• Machine Learning
• Signal Processing
• +3 more