Find Academic Supervisors

Nikunj Arunkumar BhagatView profile

Assistant Professor

• Neural & Bio-signal processing
• Medical Instrumentation
• Brain-machine interfaces
• +2 more

Nikunj Arunkumar Bhagat serves as an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, with a joint appointment in the Department of Biological Sciences and Biosciences. His research focuses on neural engineering, rehabilitation technologies, and biomedical instrumentation. Dr. Bhagat's research interests include Neural & Bio-signal processing, Medical Instrumentation, Brain-machine interfaces, Functional Electrical Stimulation, and Rehabilitation Engineering. His work bridges electrical engineering with neuroscience and rehabilitation medicine, developing technologies to assist individuals with neurological impairments. His publication portfolio shows a strong focus on brain-machine interfaces, rehabilitation robotics, and neural decoding techniques. The research spans from fundamental neural signal processing to practical applications in stroke rehabilitation, tetraplegia assistance, and hand movement restoration. His most recent work (2023) continues to advance state-space control approaches for neuromuscular stimulation and object detection applications for hand rehabilitation. Dr. Bhagat has established collaborative research with prominent institutions and researchers in the field of neurorehabilitation and brain-computer interfaces, as evidenced by his publications in high-impact journals such as IEEE Transactions on Human-Machine Systems, NeuroImage: Clinical, and Frontiers in Neuroscience. His academic journey includes a Ph.D. in Electrical Engineering from the University of Houston (2017), an M.Tech in Electrical Engineering from IIT Bombay (2011), and a B.E. in Electronics Engineering from Sardar Patel College of Engineering, University of Mumbai (2007).

• Computational Vision
• Visual Attention
• Perceptual Learning
• +5 more

Miguel Eckstein is a Distinguished Professor at UC Santa Barbara with joint appointments in the Department of Psychological & Brain Sciences (College of Letters & Science) and the Department of Electrical and Computer Engineering (College of Engineering). He earned a Bachelor's in Physics and Psychology from UC Berkeley and a PhD in Cognitive Psychology from UCLA. His career includes prior positions at Cedars Sinai Medical Center and NASA Ames Research Center. Eckstein leads pioneering research in computational human vision, integrating behavioral psychophysics, eye tracking, EEG, fMRI, and computational modeling to study: Neural mechanisms of visual perception, attention, and learning Medical image perception for clinical diagnostics Bio-inspired computer vision systems Human-robot interaction optimization His work bridges fundamental cognitive neuroscience with applied engineering solutions. Publication analysis reveals interdisciplinary contributions spanning neuroscience, computer vision, medical imaging, and psychology. Recent work (2017-2021) emphasizes neural decoding of visual processes, 3D medical imaging limitations, human-AI perceptual comparisons, and crowd-sourced visual intelligence. Awards and honors include: Guggenheim Fellowship (2019) National Academy of Sciences Troland Award NSF CAREER Award SPIE Image Perception Cum Laude Award Optical Society of America Young Investigator Award He directs the Vision and Image Understanding Lab and co-founded the Mellichamp Initiative in Mind & Machine Intelligence, fostering cross-disciplinary AI research. Grant activities support medical imaging perception, neural computation, and human-machine collaboration projects.

Sarah Degallier RochatView profile

Professor

• Human-robot interaction
• Collaborative robotics
• Digital skills training
• +5 more

Prof. Dr. Sarah Degallier Rochat serves as Head of Humane Digital Transformation at Bern University of Applied Sciences (BFH), where she is a Professor in the Department of Technology and Computer Science. She is affiliated with the Institute for Human Centered Engineering (HuCE) and specifically works within the Laboratory for Computer Perception and Virtual Reality. Her research spans multiple institutional collaborations including the Institute for Data Applications and Security (IDAS) at BFH and partnerships with the University of Fribourg on experimental studies. Professor Degallier Rochat's research focuses on human-robot interaction , collaborative robotics , and humane digital transformation . She challenges the notion of complete human replacement by technology, advocating instead for human augmentation where technology empowers rather than mechanizes workers. Her work examines how humans and robots can work together effectively in industrial settings, with particular emphasis on developing intuitive interfaces for robot programming that promote digital skills acquisition among workers through experiential learning rather than symbolic cognition. Her research has evolved from foundational work in motor primitives for humanoid robots to current applications in industrial settings. She investigates the human factors involved in digital transformation, with special attention to workers with intermediate and lower levels of education who are often overlooked in digital skills training. Her approach emphasizes embodied cognition and work experience as foundations for developing effective human-machine interfaces that leverage existing worker knowledge. Human augmentation through collaborative robotics Intuitive robot programming interfaces (visual programming) Digital skills development for industrial workers Human-centered approaches to digital transformation Ethical considerations in human-robot collaboration Workplace adaptation to new technologies Professor Degallier Rochat has secured funding from diverse sources including Innosuisse, the Gerbert Rüf Foundation, and SNF. With support from the Gerbert Rüf Foundation's First Venture program, she co-founded a spin-off company aimed at making automation profitable for SMEs through employee training. Her research demonstrates significant practical impact, with interface designs tested across 116 participants showing positive effects on programming anxiety and usability. Her laboratory develops practical solutions for human-robot collaboration in manufacturing environments, creating interfaces that workers can use without extensive technical training. Through numerous publications, conference presentations, and media engagements, she actively contributes to the discourse on ethical and human-centered technological development in industry.

• Neurobiology
• Neuropsychology
• Brain Imaging
• +4 more

Dr. Ilona Kotlewska is an assistant professor at the Institute of Experimental Psychology, Jagiellonian University, Kraków. A neurobiologist and neuropsychologist with a PhD in biological sciences, she specializes in brain imaging techniques and the neurobiological basis of attention and self-awareness. Education: Graduate of the College of Interfaculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw. Research: Focuses on visual, auditory, and tactile attention mechanisms, ownership neural correlates, and brain oscillations. Her recent work includes studies on theta oscillations, attentional selectivity, and self-face processing, published in journals like Scientific Reports and Journal of Cognitive Neuroscience . She has received prestigious awards including the Fulbright Junior Research Award, START Scholarship, and multiple Rector's Awards for scientific and organizational achievements. Scientific Awards: Rector's Award for Outstanding Scientific Achievements (2023), Fulbright Junior Research Award (2017–2018), START Scholarship (2018), ETIUDA Scholarship (2018). Community Work: Organized the Neuronus Neuroscience Forum and supported Ukrainian refugees, earning the Rector's Award for Organizational Achievements (2023).

• Cognitive Science
• Brain-Computer Interfaces
• Robotics and Human-Robot Interaction
• +5 more

Dr. Artur Gunia is a researcher at the Department of Cognitive Science within the Faculty of Philosophy at Jagiellonian University in Kraków, Poland. His work spans the interdisciplinary field of cognitive science with particular focus on human-technology interaction, neurotechnology, and philosophical aspects of cognition. His research interests encompass brain-computer interfaces, cognitive enhancement technologies, virtual and augmented reality systems, robotics, and the ethical implications of emerging technologies. Gunia's work demonstrates a strong interdisciplinary approach, bridging cognitive science, computer science, philosophy, and psychology to explore how technologies can augment human cognitive capabilities while addressing associated ethical concerns. Analysis of his recent publications reveals a consistent focus on the intersection of cognitive science and technology, particularly examining how emerging technologies like brain-computer interfaces, virtual reality systems, and social robots affect human cognition, perception, and behavior. His work spans both theoretical investigations of cognitive frameworks and practical applications of cognitive enhancement technologies across various domains including education, safety systems, and assistive technologies. Gunia has made significant contributions to understanding the phenomenological aspects of body schema in virtual environments, trust dynamics in human-machine interaction, and ethical considerations in robotics. His publications demonstrate a consistent trajectory of research exploring how humans adapt to and integrate with technological systems, with particular attention to cognitive, affective, and ethical dimensions.

• Cognitive Control
• Selective Attention
• Neuroscience
• +2 more

Christopher Blais is an Assistant Professor in the Department of Psychology at Arizona State University, specializing in cognitive control and neuroscience. He directs the EEG lab, focusing on implicit mechanisms of self-regulation and attention. PhD in Cognitive Psychology, University of Waterloo (2006) MA in Cognitive Psychology, University of Waterloo (2002) BA in Psychology with minor in Mathematics, University of Waterloo (2001) His research explores cognitive control, selective attention, and neural correlates of behavior regulation. Key areas include understanding how implicit processes influence attentional control and memory, utilizing EEG and computational models. Recent publications highlight trends in cognitive neuroscience, including applications of machine learning to EEG data, social learning mechanisms, and educational technology innovations. Blais has contributed to studies on bilingualism, prospective memory, and emotion regulation. Blais teaches undergraduate courses like BIO 495 (Undergraduate Research) and PSY 499 (Individualized Instruction), emphasizing hands-on learning in psychology and neuroscience.

Almudena González BritoView profile

Associate Professor

• Neuroaesthetics
• Neuromusicology
• Music Cognition
• +2 more

Almudena González Brito is a Reader (equivalent to Associate Professor) at the University of La Laguna, Spain, in the Department of Art History and Philosophy. She is a cellist, researcher, and cultural manager with international training from Madrid, Barcelona, Amsterdam, and Brussels, holding a PhD in Art and Humanities from her current institution. She earned her PhD in 2016 from the University of La Laguna with the thesis "El violonchelo en la música contemporánea un estudio de la musicología carnal" (The cello in contemporary music: a carnal musicology study), supervised by Dr. Pompeyo Juan Pérez Díaz and Dr. Julián Jesús González González. Since 2014, Dr. González Brito has pioneered research at the intersection of music and neuroscience through neuroaesthetics and neuromusicology. Her work investigates why different musical and choreographic styles produce distinct brain responses, examining how daily musical choices impact behavior, physiology, and overall well-being. She integrates humanistic and scientific methodologies to decode the neural mechanisms underlying aesthetic experiences and musical cognition. Her publication portfolio (2015-2024) reveals consistent focus on EEG-based analysis of brain connectivity during music perception and performance. Key patterns include comparative studies of tonal versus atonal music processing, expertise effects in musicians, neural responses to dance choreography, and stylistic differences in Baroque versus contemporary performance. These investigations consistently employ advanced network analysis of functional brain connectivity. Dr. González Brito leads the CORPOART research group (Corporeality: Flows of Communication in Neuroaesthetic Interpretation) and participates in the NNLab (Neurochemistry and Neuroimaging Laboratory), directing projects that explore the behavioral and physiological implications of musical style selection. She actively supervises doctoral candidates within the University of La Laguna's Official Doctoral Program in Art and Humanities. Her laboratory work centers on the CORPOART group's investigation of daily musical choices and their consequences for human physiology and well-being, utilizing EEG and neuroimaging techniques to bridge artistic practice with cognitive neuroscience.

Alessandro LiviView profile

Lecturer

• Neuroscience
• Decision Making
• Brain Imaging
• +4 more

Alessandro Livi, PhD is an Instructor in Neuroscience at Washington University in St. Louis School of Medicine, affiliated with the Padoa-Schioppa Lab. His research focuses on neural mechanisms underlying economic decision making, particularly studying the lateral orbital area in the mouse brain using 2-photon calcium imaging and GRIN lens technology. Dr. Livi's educational background includes: PhD in Neuroscience from the University of Parma (Italy), 2019 MS in Neuroscience from the University of Bologna (Italy), 2014 BS in Psychology from the University of Urbino (Italy), 2012 His research spans multiple domains of neuroscience with particular emphasis on decision making processes, neural representation of economic values, and action cost processing. Dr. Livi employs advanced techniques including 2-photon calcium imaging, electrophysiology, and behavioral neuroscience approaches to investigate how neural circuits represent value and guide economic choices. His work bridges cognitive neuroscience with economic theory, examining neural computations of subjective values during choice processes. Analysis of Dr. Livi's publication record reveals a strong focus on neural mechanisms of decision making, particularly in the orbitofrontal cortex, with significant contributions to understanding mirror neuron systems and action observation networks. His research spans both primate and rodent models, investigating how the brain represents decision variables, action costs, and economic values through advanced neural recording techniques. Dr. Livi has established a robust research profile with 29 publications and over 700 citations according to ResearchGate. His technical expertise includes: 2-photon calcium imaging Electrophysiology Neural data analysis Behavioral neuroscience paradigms Computational modeling of neural data

HASAN POLATView profile

Associate Professor

• Biomedical Signal Processing
• Machine Learning Applications
• Electroencephalography (EEG) Analysis
• +4 more

Assoc. Prof. Dr. Hasan Polat serves as Associate Professor at Bingöl University's Technical Sciences Vocational School since 2020, following progression from Instructor (2019-2020) and prior Research Assistant position at Mus Alparslan University (2014-2019). His academic foundation includes PhD and Master's degrees in Electrical and Electronics Engineering from Dicle University, and a Licence from Süleyman Demirel University in Electronics and Communication Engineering. His research expertise spans biomedical signal processing and AI-driven environmental monitoring , with 4 journal publications (2016-2019) and 12 international conference presentations. Key contributions include deep learning frameworks for epilepsy detection from EEG signals and machine learning models for Salmonella prediction in agricultural waters, demonstrating significant interdisciplinary impact. Teaching responsibilities encompass Algorithm and Programming, Digital Electronics, Power Electronics, and circuit analysis courses. His publications reveal a methodological evolution from wavelet transforms and empirical mode decomposition toward advanced convolutional neural networks, with consistent focus on real-world biomedical and environmental applications. No scientific awards are documented in the provided materials. Current research activities appear sustained through academic appointments rather than specified grants, with teaching duties forming a core component of his institutional role. Collaborative work with international researchers like Michelle D. Danyluk indicates global engagement despite the absence of a formally named research laboratory.

• Cognitive Neuroscience
• Computational Modeling
• Predictive Coding
• +4 more

Ryszard Auksztulewicz serves as Visiting Professor and Group Leader of the Prediction and Memory unit within the Department of Education and Psychology at Freie Universität Berlin. Based at Habelschwerdter Allee 45, Room JK 25/220 in Berlin, he leads research at the intersection of cognitive and systems neuroscience. His research focuses on neural mechanisms of prediction, attention, and memory , employing multimodal approaches including EEG, fMRI, MEG, ECoG, TMS, electrophysiology, and calcium imaging. He integrates these with computational modeling (Bayesian models of neural/behavioral data) and multivariate decoding techniques. Key research themes include: Predictive coding frameworks for understanding sensory processing Neural gain modulation in temporal expectation Auditory cortex representations of memory and prediction Task-dependent modulation of sensory predictions Recurrent processing in perceptual awareness Analysis of his 34 publications (h-index: 18) reveals consistent focus on computational neuroscience approaches to memory systems , with recent work emphasizing cross-species auditory processing and neural representation dynamics. His 2022-2018 publications particularly highlight mechanistic distinctions between "what" and "when" predictions in sensory cortex. Teaching responsibilities include: Probabilistic and Statistical Modeling (Lecture) Introduction to Programming (Seminar) Research Colloquium for Qualification Theses

Mohammad A. AhadView profile

Associate Professor

• Bioinstrumentation
• Biosensors
• Biosignal Modeling
• +4 more

Dr. Mohammad A. Ahad is an Associate Professor and Interim Department Chair in Electrical & Computer Engineering at Georgia Southern University, where he has been faculty since 2011. His research focuses on bioinstrumentation, biosensors, and biomedical signal processing, particularly in Electrical Impedance Myography (EIM) for non-invasive medical diagnostics. Education: Ph.D. Electrical and Computer Engineering, University of Tennessee, Knoxville (2007) M.S. Electrical and Computer Engineering, University of Tennessee, Knoxville (2002) B.S. Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (1998) Research Focus: Dr. Ahad's work spans biomedical instrumentation development, FPGA-based system design, and computational modeling of biological systems. His EIM research enables novel diagnostic approaches for muscle pathologies and cancer detection through finite element analysis and electrode optimization. Grant Leadership: Secured competitive funding as PI for multiple NIH and NSF projects focusing on human-robot interfaces, non-invasive instrumentation, and early cancer detection techniques using impedance methods. Teaching: Specializes in hands-on engineering education including digital design with DE2 boards, embedded systems programming, and signal processing laboratories.

Julie A. Van DykeView profile

Adjunct Professor

• Language Comprehension
• Reading Disorders
• Cognitive Neuroscience
• +3 more

Dr. Julie A. Van Dyke serves as Senior Research Scientist and Vice President of Research and Strategic Initiatives at Haskins Laboratories, an independent research institute affiliated with Yale University and the University of Connecticut. She holds adjunct professorships at McMaster University and the City University of New York Graduate Center while maintaining affiliate status at UConn's CT Institute for Brain and Cognitive Sciences. Her NIH-funded research investigates neurocognitive mechanisms underlying language comprehension and reading disorders. Her educational background includes: Ph.D. in Cognitive Psychology from University of Pittsburgh M.Sc. in Computational Linguistics from Carnegie Mellon University Honors B.A. in Computer Science and Linguistics from University of Delaware Dr. Van Dyke's research centers on cue-based retrieval theory, examining how retrieval interference causes comprehension failures in both normative processing and clinical populations (dyslexia, ADHD, age-related decline). She pioneered the application of speed-accuracy tradeoff methodology to diagnose direct-access retrieval mechanisms and investigates individual differences in eye-movement control during reading. Her work bridges cognitive theory with clinical applications through machine learning classifiers for reading disability and fixation-related brain imaging of word-by-word processing. Analysis of her recent publications reveals consistent focus on retrieval interference mechanisms across multiple methodologies: eye-tracking studies establish individual skill factors in oculomotor control, neuroimaging work identifies neural correlates of interference resolution, and machine learning approaches develop diagnostic classifiers. Key trends include the role of predictive timing in fluency disorders and dissociation between grammatical vs. semantic interference effects. Her scientific recognition includes: NIH/NICHD Institutional Post-doctoral National Research Service Award NIH/NICHD Individual Post-doctoral National Research Service Award Dr. Van Dyke actively shapes her field through editorial roles as Associate Editor for Journal of Experimental Psychology: General and Section Editor for Language and Linguistics Compass. Her NIH-funded grants support collaborative projects with researchers including Victor Kuperman, Luca Campanelli, and Clint Johns, focusing on retrieval interference, reading disability mechanisms, and neural underpinnings of comprehension. Current initiatives integrate computational linguistics with cognitive neuroscience to model real-time processing during reading. As Vice President at Haskins Laboratories, she leads a multidisciplinary team utilizing eye-tracking, EEG, fMRI, and machine learning to investigate language processing. Her lab collaborates with the CT Institute for Brain and Cognitive Sciences and maintains strong ties with UConn's neuroscience community, with ongoing data collection for fixation-related brain imaging studies.

• Artificial Intelligence
• Machine Learning
• Biomedical Signal Processing
• +3 more

Dr. S M Shafiul Hasan serves as Assistant Professor of Computer Science in the Department of Informatics and Mathematics at Mercer University's College of Professional Advancement. His academic journey includes a PhD and MSc in Electrical and Computer Engineering from Florida International University, complemented by MSc and BSc degrees from Bangladesh University of Engineering and Technology. Prior to Mercer, he conducted postdoctoral research at Emory University developing ML models for stroke recovery diagnostics. His research bridges artificial intelligence and healthcare through: Biomedical signal processing for stroke and Parkinson's diagnostics Neurovascular coupling analysis using transfer entropy EEG-based movement intention prediction systems EHR data mining for atrial fibrillation and dementia risk With 15 peer-reviewed publications since 2016 spanning IEEE Transactions, Stroke, and Frontiers in Neurology, his work demonstrates consistent translational impact. Recent publications (2023-2025) focus on contralateral neurovascular coupling in stroke patients and real-time gait intention prediction, reflecting an evolving research trajectory toward clinical implementation. As an active IEEE member, he contributes to professional discourse while mentoring students through research-intensive projects. His Emory postdoctoral experience indicates strong NIH-relevant grant activity, though specific awards aren't publicly listed. Current work integrates computer vision with prosthetic control systems, showing expansion into assistive robotics.

• Neurodegenerative Diseases
• Cerebrovascular Disease
• Amyotrophic Lateral Sclerosis (ALS)
• +5 more

Héctor Ramón Martínez-Rodríguez is an active researcher affiliated with the School of Medicine and Health Sciences at Tecnológico de Monterrey, Campus Monterrey. His primary appointment is in the Department of Neurology where he serves as a Researcher, focusing on advanced biomarkers and therapies within the research group Biomarcadores y terapias avanzadas . His research interests center on neurodegenerative and cerebrovascular disorders, with particular emphasis on amyotrophic lateral sclerosis (ALS), Parkinson's disease, Alzheimer's disease, and vascular dementia. He investigates diagnostic innovations and therapeutic approaches, leveraging clinical neuroanatomy and patient-centered evaluation methods. His work spans molecular biomarkers in ALS, surgical management of neurovascular conditions, and computational approaches to neurological assessment. Analysis of his 15 most recent publications reveals dominant research themes in ALS pathophysiology (7 articles), cerebrovascular disease (5 articles), and neurotechnology applications (3 articles). His work demonstrates strong methodological diversity including systematic reviews, cohort studies, technical innovations, and biomarker validation across multiple neurological conditions. Martínez-Rodríguez maintains active clinical engagement while pursuing research that addresses Mexico's growing neurological health challenges. His work on cost analysis of neurointerventions and epidemiological studies of stroke in elderly populations reflects commitment to regionally relevant healthcare solutions.

Rumen PozharlievView profile

Assistant Professor

• Consumer Neuroscience
• Neuromarketing
• Advertising Effectiveness
• +2 more

Rumen Pozharliev serves as Assistant Professor in the Strategy and Entrepreneurship Department at Luiss Business School, Luiss University. He concurrently holds a Senior Research Fellow position at the university's X.ITE Research Center, an interdisciplinary hub focused on Behavior and Technology. His academic credentials include: Graduated with honors in Marketing (Economics and Business – Marketing) PhD in Consumer Neuroscience from Erasmus University Rotterdam Professor Pozharliev's research program pioneers the application of neuromarketing techniques to decode how social context modulates neurophysiological responses to advertising. By measuring cognitive processes through EEG and biometric tools, his work provides empirical foundations for predicting advertising effectiveness in real-world social environments. This bridges critical gaps between neuroscience, consumer behavior, and marketing strategy. His scholarly contributions appear in elite journals including Journal of Marketing Research , Journal of Advertising , and Frontiers in Human Neuroscience , establishing him as a leading voice in experimental consumer neuroscience. At Luiss Business School, he teaches specialized courses in consumer neuroscience, service marketing, and marketing planning using Markstrat simulation. His pedagogy emphasizes translating neuroscientific insights into actionable marketing strategies through hands-on experiential learning. The X.ITE Research Center serves as his primary research base, where he directs projects examining technology-mediated human behavior with applications across digital marketing, service design, and consumer decision architecture.