Find Academic Supervisors

Kate Christison-LagayView profile

Assistant Professor

• Neuroscience
• Consciousness Studies
• Auditory Perception
• +3 more

Dr. Kate Christison-Lagay is an Assistant Professor in the Department of Biological Sciences at the University of New Hampshire (UNH), part of the College of Life Sciences and Agriculture. She holds a Ph.D. in Neuroscience from the University of Pennsylvania. Her research focuses on neural mechanisms underlying sensory perception, particularly in auditory and visual systems, and conscious awareness. She teaches courses such as Neuroscience and Behavior (NSB 500), Neurobiology Laboratory (NSB 501), and Neuroethology (ZOOL 777W). Education: Ph.D., Neuroscience, University of Pennsylvania Research Interests: Dr. Christison-Lagay investigates how the brain processes sensory information to generate conscious perception. Her work spans auditory and visual modalities, with emphasis on neural networks involved in stimulus detection, attentional modulation, and cross-modal integration. Techniques include electrophysiological recordings, EEG analysis, and clinical trials involving thalamic stimulation for neurological conditions. Recent studies explore the role of cortical-subcortical interactions in visual awareness and auditory categorization in non-human primates. Publications: Her recent work includes studies on auditory perception mechanisms, visual consciousness networks, and translational neuroscience approaches to epilepsy treatment. Key themes involve understanding neural correlates of conscious experience across sensory domains. Grants & Advising: No specific grants or advisees are listed in the provided materials. She is affiliated with UNH's Biological Sciences department, located in Rudman Hall. Labs/Teams: Affiliated with UNH's Biological Sciences research facilities, though specific lab names are not mentioned in the profile.

Douglas H. WedellView profile

Professor

• Affective Neuroscience
• Context Effects in Judgment
• Spatial Memory
• +2 more

Douglas H. Wedell is a Professor in the Department of Psychology at the University of South Carolina and Director of the Institute for Mind and Brain. He earned his Ph.D. in Cognitive Psychology from UCLA (1984). His research examines how context shapes judgment, memory, and decision-making through behavioral experiments and neuroimaging. Current projects investigate affective representations across sensory modalities, contextual influences on preference formation, spatial memory biases, and music cognition. He employs methods including fMRI, psychophysiology, and computational modeling. Wedell's publications demonstrate integration of behavioral and neuroscientific approaches to contextual cognition. Recent work focuses on cross-modal affective processing, reinforcement learning in changing contexts, and physiological correlates of decision outcomes. He directs the NSF-funded Summer Research Experience in Brain and Cognitive Sciences and teaches courses in cognitive psychology, judgment/decision-making, and quantitative methods.

Sarah PowerView profile

Associate Professor

• Biomedical Engineering
• Physiological Signal Processing
• Brain-Computer Interfacing
• +1 more

Sarah Power is Associate Professor jointly appointed in the Faculty of Engineering and Applied Science (Electrical and Computer Engineering) and Faculty of Medicine at Memorial University. She holds a B.Eng. from Memorial (2006), M.A.Sc. from Toronto, and PhD in Biomedical Engineering from Toronto. Her research applies signal processing and pattern recognition to medical/rehabilitation challenges, focusing on mental state classification using EEG and physiological signals. This includes workload assessment, stress detection, and brain-computer interfaces. Power's publications demonstrate expertise in EEG signal classification, fNIRS-BCI development, and real-world neurotechnology applications. Recent work advances hierarchical classification systems and addresses validation challenges in passive BCI designs.

Yan GaiView profile

Associate Professor

• Neuroengineering
• Biomedical Engineering
• Hearing Impairment
• +4 more

Yan Gai, Ph.D., is an Associate Professor of Biomedical Engineering at Saint Louis University (SLU), affiliated with the School of Science and Engineering. She leads the Neuroengineering Lab, focusing on advancing assistive technologies for paralyzed and hearing-impaired patients. Her work includes brain-controlled wheelchairs, smart hearing aids, and cochlear implants. Dr. Gai holds a Ph.D. in Bioengineering from Syracuse University, with postdoctoral training at NYU and UW-Madison. Education: Ph.D. in Bioengineering, Syracuse University M.S. in Bioengineering, Syracuse University M.E. in Electrical Engineering, South China University of Technology B.S. in Electrical Engineering, South China University of Technology Research Interests: Dr. Gai’s lab integrates behavioral, electrophysiological, and computational methods to study auditory pathways in speech perception and sound localization. Current projects emphasize neuroengineering solutions for sensory deficits, including cochlear implant simulations and brain-computer interfaces. Her work bridges basic neuroscience with clinical applications. Key Achievements: Recipient of SLU’s President Research Fund (2017) for brain-controlled wheelchair technology Published over 20 peer-reviewed articles in journals like Journal of Neurophysiology and PLoS Computational Biology Developed noise-vocoding techniques for cochlear implant research Labs/Teams: Neuroengineering Laboratory (http://gailab.net/)

• Cognitive Neuroscience
• Neural Oscillations
• Brain Connectivity
• +7 more

Daniel Baldauf serves as Associate Professor at the Center for Mind/Brain Sciences (CIMeC), University of Trento, Italy, where he directs the MEG facility and leads the Attention Network Group. His academic appointments include Assistant Professor positions at CIMeC (2016-2019) and research scientist roles at MIT's McGovern Institute (2014-2018). PhD in Psychology, Ludwig-Maximilians-University Munich (2008) Diploma in Psychology, Ludwig-Maximilians-University Munich (2005) Graduate studies in Psychology and Neurobiology, Ludwig-Maximilians-University Munich (2000-2005) Fulbright Fellowship at Caltech (2006-2007) Postdoctoral training at MIT under Robert Desimone (2009-2014) His research centers on neural communication mechanisms using multimodal neuroimaging. Key interests include directed information flow between brain areas through neural oscillations, with applications to visual/auditory attention, working memory, and executive control. His lab employs MEG/EEG, fMRI, DTI, and behavioral paradigms to investigate how oscillatory synchrony orchestrates perception and sensorimotor control across five integrated projects: top-down attention mechanisms, frequency tagging methodologies, functional-anatomical connectivity mapping, attention during sequential behavior, and sleep-state connectivity dynamics. The exceptional temporal resolution of MEG enables millisecond-precision analysis of large-scale network interactions. Publication trends reveal consistent focus on attentional networks and neural synchrony, with increasing methodological sophistication in multimodal integration (MEG/fMRI/DTI) and computational approaches like 2D-Fourier frequency tagging. Recent work expands into sleep neurophysiology while maintaining core attention research. DFG Doctoral Grant (2005-2008) DAAD Study Abroad Grant (2006-2007) Fulbright Travel Grant (2007) Vision Science Society Student Investigator Award (2007) Baldauf actively mentors through CIMeC's MA and PhD programs, teaching specialized courses in MEG analysis, computational methods, brain connectivity, and research ethics. His lab collaborates with Fondazione Bruno Kessler's Neuroinformatics group on DTI-fMRI integration. Current research leverages CIMeC's state-of-the-art MEG facility to explore neural dynamics across wakefulness and sleep cycles, with emphasis on how oscillatory patterns support cognitive functions. Future directions include refining causal inference in connectivity studies through transcranial stimulation and developing machine learning approaches for neural decoding. The Attention Network Group maintains strong industry and academic partnerships, with Baldauf serving on editorial boards for Nature Scientific Reports and reviewing for 20+ top neuroscience journals including Neuron, Journal of Neuroscience, and NeuroImage.

Malcolm SlaneyView profile

Adjunct Professor

• Auditory Perception
• Psychoacoustics
• Signal Processing
• +3 more

Malcolm Slaney serves as an Adjunct Professor at Stanford University's Center for Computer Research in Music and Acoustics (CCRMA) and holds an Affiliate Professor position in the Electrical Engineering Department at the University of Washington. He concurrently works as a Principal Investigator at the International Computer Science Institute in Berkeley. His academic foundation includes: Ph.D. in Electrical Engineering from Purdue University M.S.E.E. from Purdue University B.S.E.E. from Purdue University Dr. Slaney's research centers on auditory perception mechanisms and computational modeling of hearing, with recent breakthroughs in decoding auditory attention from neural signals. His work integrates psychoacoustics with signal processing to advance medical imaging and multimedia systems, exemplified by his foundational contributions to tomographic reconstruction algorithms and auditory function modeling. His scientific recognition includes: Life Fellow of the IEEE With extensive industry experience spanning Bell Laboratories, Apple, Microsoft Research, and Google Research, Dr. Slaney has co-authored the seminal IEEE text "Principles of Computerized Tomographic Imaging" and co-edited "Computational Models of Auditory Function." He has led CCRMA's Hearing Seminar for over 30 years while serving editorial roles for IEEE Transactions and ACM Multimedia, delivering influential tutorials at ICASSP and SIGIR conferences on psychoacoustics and multimedia retrieval.

Jelena RisticView profile

Professor

• Cognitive Neuroscience
• Developmental Psychology
• Social Cognition
• +3 more

Professor Jelena Ristic is a faculty member in the Department of Psychology at McGill University, holding the former William Dawson Chair (2009–2022). She specializes in cognitive neuroscience and developmental science, with a focus on social attention, interactive cognition, and eye tracking technologies. Her research integrates behavioral, neural, and developmental approaches to understand how humans process social information in dynamic contexts. Dr. Ristic earned her B.A., M.A., and Ph.D. from the University of British Columbia, followed by postdoctoral training at the University of California, Santa Barbara. She serves as an Associate Editor for Journal of Experimental Psychology: Human Perception and Performance and Visual Cognition . Her work explores mechanisms underlying social attention, including gaze dynamics, group interactions, and the impact of face masks on emotion recognition. Key research tools include EEG, eye tracking, and experimental paradigms analyzing social perception and decision-making. Notable awards include the CSBBCS Mid-Career Award and Best Article recognitions from APA and CPA. Her laboratory, the Laboratory for Attention & Social Cognition , investigates topics like social event segmentation, attentional modulation, and collective behavior. Current studies address how perceptual and contextual factors shape social interactions in real-world settings.

Alan WongView profile

Senior Lecturer

• Perceptual Training & Expertise
• Object Perception
• Gamified and Digital Cognitive Training
• +4 more

Dr Alan Wong is a Senior Lecturer and Programme Lead for the MSc Psychology in Game Design & Digital Innovation at the University of Surrey's School of Psychology (part of the Faculty of Health and Medical Sciences). He previously held an Associate Professor position at the Chinese University of Hong Kong (CUHK) before joining Surrey in 2022. His research focuses on perceptual expertise, object recognition, and cognitive training, with notable contributions to absolute pitch acquisition in adults and multitasking limitations. He leads the Perception & Experience Lab, collaborating with the Learning and Perception Lab on expertise-related studies. Key achievements include demonstrating adult absolute pitch improvement via training and identifying distinct processing constraints in multitasking. He has supervised numerous students across PhD, MPhil, and undergraduate programs, with notable advisees including Pu Fan, Vince Ngan, and Kelvin Lui. Awards include the 2nd Prize in CUHK's 3-minute Thesis Competition and recognition as a Fellow of the Surrey Institute for People-Centred Artificial Intelligence. His work bridges basic research with applied domains like education and therapy. Education PhD in Cognition and Cognitive Neuroscience, Vanderbilt University Former Associate Professor at CUHK's Department of Psychology Research Interests Dr Wong investigates how perceptual training shapes expertise in domains like music notation, face recognition, and reading. His lab explores neural mechanisms underlying holistic processing (e.g., word/character perception) and develops gamified training tools. Recent projects include EEG studies on object processing and meta-analyses of attention deficits in schizophrenia. Collaborative efforts with Yetta Wong's lab further integrate findings on absolute pitch and visual expertise. Lab & Teams The Perception & Experience Lab emphasizes interdisciplinary approaches, combining behavioral experiments with neuroimaging (EEG). Partnerships include the Surrey Institute for People-Centred AI and the Institute for Sustainability. Ongoing projects address expertise transferability, digital training efficacy, and perceptual-cognitive links in reading disorders. Past collaborations produced a best-selling child education book (co-authored with CityU researchers) and smartphone apps for multitasking training.

Søren BechView profile

Professor

• Acoustics
• Audio Engineering
• Sound Zones
• +4 more

Søren Bech is a Professor at the Department of Electronic Systems within The Technical Faculty of IT and Design at Aalborg University. His academic qualifications include a PhD from the Technical University of Denmark (1988) and an MSc in Electrical Engineering (1982). His primary research focuses on audio quality, acoustics, and sound zone technologies, with emphasis on perceptual audio evaluation, spatial audio systems, and cortical auditory attention decoding. He leads projects such as ISOBEL (Interactive Sound Zones) and SOUNDS (Service-Oriented, Ubiquitous, Network-Driven Sound), addressing challenges in dynamic audio environments and networked audio systems. Key research areas include automotive audio systems, headphone technology, and the integration of EEG-based attention decoding for personalized sound experiences. He has received recognition, including the Best Student Paper award in 2024. Collaborations span academia and industry, with involvement in organizations like the Danish Sound Cluster and Danmarks Forsknings- og Innovationspolitiske Råd. His work bridges theoretical acoustics with practical applications in consumer electronics and immersive media.

Jesper JensenView profile

Professor

• Acoustic Signal Processing
• Machine Learning
• Speech Enhancement
• +5 more

Jesper Jensen is a Professor at the Department of Electronic Systems, part of The Technical Faculty of IT and Design at Aalborg University. His research focuses on acoustic signal processing, machine learning, and speech enhancement, with particular expertise in applications like hearing aids, noise reduction algorithms, and deep learning architectures for audio systems. He serves as a project supervisor at institutions including Oticon A/S since 2007, and co-leads the CASPR (Centre for Acoustic Signal Processing Research) center. Key research interests include multichannel signal processing, robust speech enhancement in reverberant environments, and adaptive filtering techniques. His work integrates Bayesian methods, deep neural networks (DNNs), and sparse modeling to address challenges in audio localization, speech presence probability estimation, and sound zone control systems. Notable Achievements: Recipient of the prestigious 'Stor international pris' award in 2017 Over 135 publications in journals like IEEE Signal Processing Letters and conference proceedings Active collaborations with industry partners such as Oticon A/S His research outputs emphasize practical applications, including voice control systems for hearing aids, binaural speech enhancement in noisy environments, and acoustic reflector localization for robotics. Recent work explores transformer networks and learning-based frameworks for real-time audio processing.

Konrad KordingView profile

Professor

• Causality
• Machine Learning
• Deep Learning for Neuroscience
• +3 more

Konrad Kording is a Penn Integrates Knowledge (PIK) Professor in Neuroscience at the University of Pennsylvania. His research focuses on causality, machine learning, and deep learning applications in neuroscience. He leads a highly interdisciplinary lab exploring neural data analysis, Bayesian decision theory, and meta-science. Key projects include developing algorithms for causal inference from observational data and analyzing movement and neural activity using computational models. Education: PhD in Physics from ETH Zurich, Diploma in Experimental Physics and Computational Neuroscience. Collaborates widely across disciplines, including with bioengineers, statisticians, and clinicians at UPenn and external institutions like MIT and UCSB. Advises graduate students and postdocs in topics ranging from neural decoding to AI ethics. Founded the Kording Lab, emphasizing independent project-driven research with unique lab practices like weekly 'lab teachings' and collaborative coding sessions.

Mahnaz ArvanehView profile

Senior Lecturer

• Brain-computer interface (BCI)
• Neural signal processing
• Biomedical signal processing
• +5 more

Dr. Mahnaz Arvaneh is a Senior Lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield. She holds a PhD in Advanced Brain-Computer Interface from Nanyang Technological University (2013) and has held academic roles at University College Dublin and Trinity College Dublin. Her research focuses on brain-computer interfaces (BCI), neural signal processing, and their applications in healthcare, including stroke rehabilitation and neuroprosthetics. She directs the Physiological Signals and Systems Laboratory and has published over 50 peer-reviewed papers in top journals/conferences. Research interests include biomedical signal processing, machine learning, neuroprosthetics, and clinical BCI applications. Notable achievements include high-impact media coverage (BBC, Sky News), IEEE editorial roles, and co-editing the IET book Signal Processing and Machine Learning for Brain-Machine Interfaces . She has secured grants totaling over £500k, including EPSRC funding for exoskeleton robotics and neurotechnology development. Dr. Arvaneh's work emphasizes translational research, with projects like TeleRegain (BCI-based stroke telerehabilitation) and Neurophysiological Biomarkers for Neurodegenerative Diseases. Her teaching includes modules on biomedical devices, signal processing, and rehabilitation engineering. Current grants focus on neurotechnology inclusivity, mental healthcare applications, and thermal stimulus quantification in dentistry.

Chuck AndersonView profile

Professor

• Machine Learning
• Deep Learning
• Reinforcement Learning
• +9 more

Chuck Anderson is a Professor in the Department of Computer Science at Colorado State University (CSU), with joint appointments in the Molecular, Cellular, and Integrative Neuroscience Program, the School of Biomedical Engineering, the Graduate Degree Program in Ecology, and the Online Systems Engineering Program. His research focuses on machine learning, deep learning, and reinforcement learning, with applications to brain-computer interfaces, high-dimensional data, health, environment, and energy. Research Interests: His work spans algorithm development for classification, modeling, and control, with a strong emphasis on understanding learned representations. He applies these methods to neuroscience, climate science, programming, and accessibility technologies, demonstrating a highly interdisciplinary approach. His research integrates insights from computer science, neuroscience, and engineering to solve complex real-world problems. Publication Trends: His recent and advised publications reveal a sustained focus on reinforcement learning, deep neural networks, and brain-computer interfaces. There is a growing trend toward diffusion models, ensemble methods, and applications in climate and healthcare, indicating forward-looking and impactful research directions. Scientific Awards: CSU Online Outstanding Distance Educator Award (2024) Best Overall Paper Award, IJCNN 2015 Advising and Grants: He has advised over 15 Ph.D. students, with recent graduates working on reinforcement learning, neuroimaging, climate AI, and program synthesis. While specific grants are not listed, his sustained output and advising suggest consistent research funding. He also leads an AI consulting company, Pattern Exploration, focusing on custom AI solutions for health, environment, and energy. Labs and Teams: Though not explicitly named, his work implies leadership in a machine learning research group at CSU, likely involving students and collaborators across neuroscience, biomedical engineering, and climate science. His involvement in online AI programs and consulting indicates active outreach and applied research teams.

• Cognitive Neuroscience
• Psycholinguistics
• Bilingualism
• +3 more

Dr. Mirjana Bozic is an Associate Professor at the Department of Psychology, University of Cambridge , affiliated with Cambridge Neuroscience . Her research focuses on the neural mechanisms of spoken language comprehension and the cognitive consequences of bilingualism . Specializes in neuroimaging (fMRI, MEG/EEG) and behavioral studies Key themes: language processing, morphological complexity, selective attention in bilinguals Scientific Awards: No specific awards listed in the provided text. Recent Publications (2025–2005) reveal consistent exploration of: Morphological processing in multilingual contexts Neural substrates of speech comprehension under interference Language evolution and proto-language theories Effects of SARS-CoV-2 on memory function Cognitive benefits of bilingualism Iconicity in spoken/written language Methodologically combines neuroimaging (fMRI, MEG, EEG) with cross-linguistic analysis (German, Italian, Polish, Arabic, Russian, English).

Sophie HerbstView profile

Research Fellow

• Implicit timing
• Auditory temporal predictions
• Neural oscillations
• +4 more

Sophie Herbst is a Research Fellow at CEA, focusing on implicit timing mechanisms and their role in auditory processing. Her work employs Bayesian models to analyze how temporal predictions derived from sensory input statistics enhance hearing. Methods: Psychophysics, Computational Modelling, EEG, MEG Funding: ANR JCJC WHEN project investigating temporal predictions in audition Contact: sophie.herbst@cea.fr Research Interests: Her work bridges auditory neuroscience and cognitive psychology, emphasizing neural oscillations like delta and alpha waves in temporal prediction. She explores how these mechanisms interact with sensory analysis to optimize auditory perception. Article Trends: Recent publications highlight cross-modal temporal processing, neural oscillation dynamics (delta, alpha), and applications of MEG/EEG in decoding subjective time perception . Her studies often integrate behavioral paradigms (e.g., gap detection) with neuroimaging. Advising and Grants: She actively recruits Master’s students for the ANR-funded WHEN project, which examines endogenous temporal prediction representations and their auditory functional consequences.