Find Academic Supervisors

Chao LiView profile

Research Fellow

• Artificial Intelligence in Healthcare
• Medical Imaging
• Precision Medicine
• +3 more

Chao Li is a Principal Research Fellow at the University of Cambridge's Faculty of Mathematics, specializing in AI-driven healthcare solutions. His research focuses on precision medicine through image-based AI and multi-omics integration, with applications in neurological disease modeling, surgical oncology, and clinical AI safety. He leads the Centre for Mathematical Imaging in Healthcare , advancing translational AI for personalized medicine. Research Themes: Image-based AI for precision mental health AI in surgical and interventional oncology Multi-omics approaches for disease characterization Evaluation of AI innovations for clinical translation Publications highlight advancements in multimodal fusion for diagnostics, histology-molecular marker integration, and neuroimaging analytics for mental health. His work bridges computational mathematics with clinical challenges, emphasizing real-world healthcare impact. Labs/Teams: Active member of the Centre for Mathematical Imaging in Healthcare , collaborating across departments to develop AI tools for clinical deployment.

Michael PetridesView profile

Professor

• Cognitive Neuroscience
• Neuropsychology
• Behavioral Neuroscience
• +3 more

Michael Petrides is a Professor in the Department of Psychology at McGill University. His research focuses on neuropsychology and cognitive neuroscience, investigating the functions of the frontal, temporal, and parietal cortices through studies involving patients with brain lesions, animal models, and neuroimaging techniques like PET and fMRI. His work bridges human and non-human primate studies to understand cognitive mechanisms. Research Interests: Cognitive Neuroscience: Examines neural underpinnings of higher cognitive functions. Behavioral Neuroscience: Analyzes brain-behavior relationships via lesion studies and animal models. Neuroimaging: Utilizes PET and fMRI to map brain regions involved in memory, language, and decision-making. Publications Trends: His work emphasizes cross-species comparisons (human-macaque), functional connectivity analysis, and clinical applications of neuroimaging in neurosurgical planning. Advising & Grants: No student advisees listed. Grants and funding details not explicitly mentioned in provided materials. Labs/Teams: Affiliated with McGill's Psychology Department research groups studying cognitive neuroscience and brain architecture.

• AI & Neuroscience
• Biomedical Engineering
• Neurotechnology
• +7 more

Aldo Faisal is a Professor of AI & Neuroscience at Imperial College London's Department of Bioengineering and Faculty of Engineering. He is also the Founding Director of the UKRI Centre for Doctoral Training in AI for Healthcare (£20M), leading the Faisal Lab. His roles include associate investigator at the MRC London Institute of Medical Sciences and affiliation with the Gatsby Computational Neuroscience Unit (UCL). His research bridges AI, neuroscience, and healthcare, focusing on neurotechnology, human behavior analysis, and clinical applications. Education: Studied Computer Science and Physics in Germany, followed by Biology at the University of Cambridge (Emmanuel College). Earned a PhD in Neuroscience under Simon Laughlin, and postdoctoral work with Daniel Wolpert on sensorimotor control. Prior professional experience includes roles at McKinsey & Co. and Credit Suisse. Research Interests: Combines cross-disciplinary approaches to study brain-behavior relationships, developing technologies for neurological disorders and amputees. Key labs include the Brain & Behaviour Lab (neurotechnology) and Behaviour Analytics Lab (behavioral data science). Techniques include machine learning, robotics, and neuroimaging (EEG/fNIRS). Publications: Over 100+ peer-reviewed articles, spanning AI in healthcare, motor learning, and neurotechnology. Recent work emphasizes safety of AI in critical care, wearable biomarkers for neuromuscular diseases, and human-AI collaboration. Awards: UKRI Turing AI Fellowship, Toyota Mobility Prize ($50k), Rosetree Interdisciplinary Award (£300k), and fellowships from German National Merit Foundation and Böhringer-Ingelheim Foundation. Elected to Global Futures Council (WEF, 2016). Grants & Labs: Leads £20M CDT in AI for Healthcare, £2M Turing Fellowship project, and manages labs at Imperial and University of Bayreuth (Germany). Collaborates with institutions like CRUK Convergence Science Centre and Data Science Institute.

Andrew LinView profile

Senior Lecturer

• Neuroscience
• Olfactory System
• Neural Circuit Function
• +3 more

Dr. Andrew Lin is a Senior Lecturer and School Director of One University at the University of Sheffield's School of Biosciences. He holds a PhD from the University of Cambridge and a BA in Biology from Harvard University. His career includes roles as a Lecturer (2019-2022), Vice-Chancellor’s Fellow (2015-2019), and Postdoctoral Fellow at the University of Oxford (2009-2015). Research focuses on how the brain encodes sensory information for memory formation, using Drosophila's olfactory system as a model. Key areas include sparse coding in Kenyon cells, synaptic inhibition/excitation balance, and neural circuit dysfunction links to epilepsy. Teaching includes modules like BMS11004 Introduction to Neuroscience and BMS248 Neural Circuits, Behaviour and Memory. He has secured grants from the European Research Council, BBSRC, and Wellcome Trust. Professional memberships include the FENS-Kavli Network and BBSRC Pool of Experts. Lab research employs techniques like in vivo two-photon imaging, electrophysiology, and genetic manipulation. PhD opportunities are available in neural circuitry and sensory processing.

• Computational Neuroscience
• Neural Networks
• Synaptic Plasticity
• +3 more

Prof. Tatjana Tchumatchenko is Professor and TRA Steering Committee member at the University of Bonn, leading a computational neuroscience group at the Institute of Experimental Epileptology and Cognition Research. Her research focuses on computational analysis of recurrent neural networks and molecular dynamics of synapses. Research examines how molecular dynamics in dendrites organize synaptic plasticity outcomes, and how synaptic learning rules help neural networks solve computational tasks. The group develops quantitative methods to understand neural data and predictive models of neural network function across molecular, synaptic, and network levels. Honors include the Boehringer Ingelheim FENS Research Award (2022), ERC Starting Grant (2020), Heinz Maier-Leibnitz-Prize (2016), and election to the Young Academy of Europe. Current projects investigate dendritic protein distribution, energy constraints in neurons, and astrocyte contributions to learning.

Timothy A. BrownView profile

Professor

• Classification of Anxiety and Mood Disorders
• Psychometric Methods
• Structural Equation Modeling
• +3 more

Dr. Timothy A. Brown is Professor Emeritus in Psychological & Brain Sciences at Boston University, where he directs research at the Center for Anxiety & Related Disorders. His expertise spans anxiety/mood disorders classification, temperament-psychopathology relationships, and advanced statistical methodologies. His research focuses on dimensional models of emotional disorders, psychometric evaluation of diagnostic instruments, and structural equation modeling applications. He developed influential frameworks for understanding comorbidity patterns through latent variable modeling. Publications demonstrate consistent themes in psychometric validation, transdiagnostic approaches, and longitudinal modeling of psychopathology. Recent work emphasizes COVID-19 mental health impacts and clinical assessment optimization. Dr. Brown teaches graduate courses in multivariate statistics, including confirmatory factor analysis and structural equation modeling. He authored the authoritative textbook Confirmatory Factor Analysis for Applied Research . He serves as Associate Editor of the Journal of Abnormal Psychology and collaborates internationally on classification systems for emotional disorders.

Deanna GreeneView profile

Associate Professor

• Developmental cognitive neuroscience
• Brain network development
• Cortico-subcortical systems
• +2 more

Deanna Greene is an Associate Professor in the Department of Cognitive Science at UC San Diego. She holds a PhD in Cognitive Neuroscience from UCLA and completed postdoctoral training at Washington University in St. Louis. Her research integrates neuroimaging and cognitive neuroscience approaches to study brain development in neurodevelopmental disorders. Her lab investigates network organization in cortico-subcortical systems, focusing on Tourette syndrome and comorbid conditions. Research employs multimodal neuroimaging to map developmental trajectories and mechanistic disruptions. Recent publications emphasize clinical neuroscience, with themes spanning diagnostic reappraisal of tic disorders, neuroanatomical correlates of symptoms, and individual variability in brain organization. Articles frequently utilize advanced MRI techniques and computational modeling.

Can ChenView profile

Assistant Professor

• control theory
• network science
• tensor algebra
• +7 more

Can Chen is an Assistant Professor in the School of Data Science and Society at the University of North Carolina at Chapel Hill, with adjunct appointments in the Department of Mathematics (College of Arts & Sciences) and the Department of Biostatistics (Gillings School of Global Public Health). He holds core faculty status in the Carolina Health Informatics Program and is affiliated with the Computational Medicine Program and Carolina Center for Interdisciplinary Applied Mathematics. Education: B.S. in Mathematics (UC Irvine, 2016), M.S. in Electrical & Computer Engineering (UMichigan, 2020), Ph.D. in Applied & Interdisciplinary Mathematics (UMichigan, 2021), followed by a postdoc at Brigham and Women’s Hospital/Harvard Medical School (2021–2023). Research interests span control theory, network science, tensor algebra, numerical analysis, machine learning, computational biology, and hypergraph learning. Notable contributions include theoretical frameworks for ecological systems stability, tensor-based dynamical systems, and hypergraph learning applied to genome-scale metabolic networks. Recent work includes a Physics Reports review on ecological stability, a Springer book on tensor algebra, and a Nature Communications paper introducing CHESHIRE for metabolic network analysis. His lab focuses on developing computational tools for systems biology and translational medicine. Key collaborations involve proteogenomic approaches to cancer biomarker discovery, E3 ligase-based targeted therapy, and signal transduction pathways in oncology. He currently oversees research on protein degradation mechanisms, immune-oncology, and systems-driven drug development.

Cynthia F. MossView profile

Professor

• Sensory coding
• Auditory neuroscience
• Spatial perception
• +6 more

Cynthia F. Moss is a Professor in the Department of Psychological and Brain Sciences at Johns Hopkins University (JHU), with joint appointments in Neuroscience and Mechanical Engineering. She directs the Comparative Neural Systems and Behavior Laboratory (Bat Lab), investigating neural mechanisms of sensory perception and spatial navigation in echolocating bats. Her work combines neurophysiology, behavioral ecology, and engineering to study how bats process auditory information for navigation, communication, and obstacle avoidance. Dr. Moss earned a B.S. (summa cum laude) from the University of Massachusetts, Amherst, and a Ph.D. from Brown University. She held prior faculty positions at Harvard University and the University of Maryland, where she directed the Neuroscience and Cognitive Science graduate program. Her research has received prestigious awards including the Hartmann Award (2017), James McKeen Cattell Award (2018), and Alexander von Humboldt Research Prize (2019). Her research focuses on sensory coding of natural stimuli, spatial perception, attention, and adaptive motor control. Key findings include discoveries about 3D auditory space representation in the midbrain, age-resistant hearing in bats, and the role of wing hairs in flight control. Her lab employs innovative techniques like wireless neural recording, two-photon imaging, and DREADDs-mediated inactivation to study neural circuits. Dr. Moss collaborates across disciplines, bridging neurobiology, robotics, and sensory systems engineering. Her work informs biomimetic technologies for sonar navigation and adaptive control systems. She actively mentors students and postdocs in the Krieger School of Arts and Sciences, Whiting School of Engineering, and School of Medicine at JHU.

Lomax BoydView profile

Academic

• Neuroethics
• Human Brain Models
• Moral Philosophy in Science
• +3 more

Lomax Boyd is an Assistant Research Professor at the Johns Hopkins Berman Institute of Bioethics and a Civic Science Fellow. His work focuses on the ethical and scientific implications of emerging brain models such as organoids, chimeras, and genetically engineered organisms. He holds a PhD in Genetics and Genomics from Duke University and completed postdoctoral training in neurogenetics at The Rockefeller University. Education: BS in Biochemistry & Molecular Biology, University of Richmond MS in Biology, College of William and Mary PhD in Genetics & Genomics, Duke University Postdoctoral Research, The Rockefeller University Research Interests: Boyd explores how neurobiological discoveries intersect with ethical questions, particularly regarding moral status, public epistemology, and science communication. His work bridges neuroethics education, the governance of organoid research, and the societal implications of biotechnologies. Grants & Funding: Kavli Foundation: Studying epistemic beliefs and public attitudes toward science Dana Foundation: Neuroscience trainee ethics engagement programs Key Projects: Leads the Neuroscience & Society initiative connecting neuroscientists with stakeholders. Co-authored the Baltimore Declaration on organoid intelligence governance.

• Bile Acid Metabolism
• Microbial Pathogenesis
• Bacterial Vaccines and DNA Delivery
• +3 more

Prof. Cormac Gahan is a Professor at the School of Microbiology, University College Cork (UCC), and a Principal Investigator at the APC Microbiome Institute. He holds editorial roles in journals like Journal of Pathogens and Microbiome . His research focuses on host-microbe interactions, microbial pathogenesis, and bacterial vaccine development. Prof. Gahan has published 167 peer-reviewed articles, with an h-index of 75 and over 19,000 citations. Education: PhD in Immunology and Microbiology from UCC (1996). Affiliations: APC Microbiome Institute, School of Pharmacy (UCC). Research Interests: Bile acid metabolism, bacterial pathogenesis (e.g., Listeria monocytogenes), live bacterial vaccine vectors, gut microbiota dynamics. His work bridges microbiology, immunology, and clinical therapeutics. Grants & Funding: Over €13.5M from SFI, EU, Health Research Board, and industry partnerships. Current grants include EU Horizon 2020 projects and APC Microbiome initiatives. Labs & Collaborations: Leads the Bile Research Group and collaborates with institutions like Cork Cancer Research Centre and Teagasc. Directs the UREKA summer school program for microbiology training.

Caroline RobertsonView profile

Associate Professor

• Neuroscience
• Perception
• Memory
• +4 more

Dr. Caroline Robertson is an Associate Professor in the Department of Psychological and Brain Sciences at Dartmouth College. She holds a B.A. from Columbia University, a Ph.D. from the University of Cambridge, and completed postdoctoral training at the Harvard Society of Fellows and MIT. Her lab investigates the interplay of perception, memory, and neurodiversity, particularly in autism. Using advanced techniques like virtual reality (VR), eye-tracking, fMRI, and MR spectroscopy, her research explores how sensory input interacts with cognitive processes in diverse populations. Key research areas include: Constructive nature of visual perception Neural mechanisms of scene perception and spatial memory Neurobiological underpinnings of autism spectrum conditions Role of GABAergic systems in perceptual awareness Her lab emphasizes inclusivity, actively involving neurodiverse individuals in research design. They operate a state-of-the-art VR suite for studying naturalistic environments and collaborate on projects like the Dartmouth Autism Research Initiative. Recent work focuses on retinotopic coding in memory-perception interactions and the impact of perceptual load on social attention in autism. Her team's research has been published in Nature Neuroscience , PNAS , and Current Biology , with a focus on translational insights into neurodivergent experiences.

NG Huck HuiView profile

Research Professor

• Stem Cell Biology
• Regenerative Medicine
• Neurodegenerative Diseases
• +7 more

NG Huck Hui is a Research Professor and Senior Group Leader at the Laboratory of Precision Disease Therapeutics, Genome Institute of Singapore (GIS), under A*STAR. His research focuses on stem cell biology, particularly on understanding and harnessing the potential of pluripotent and adult stem cells for regenerative medicine and disease modeling. Key interests include stem cell state maintenance, controlled differentiation for 3D cellular models, and applications in neurodegenerative and metabolic diseases. He leads a team developing advanced genetic and cell culture approaches to create biologically accurate disease models, aiming to advance personalized medicine. His work emphasizes creating functional organoids (e.g., midbrain organoids with dopaminergic neurons) and mini-brains for studying complex disorders. Recent publications highlight innovations in stem cell reprogramming, transcriptional networks (e.g., Oct4/Nanog), and regulatory mechanisms governing pluripotency. He actively recruits postdoctoral fellows and students to expand this research. His laboratory collaborates across disciplines to bridge basic science with translational applications, focusing on leveraging stem cells for therapeutic discovery and disease understanding.

Marc SchmidtView profile

Professor

• Neurobiology
• Animal Behavior
• Physiology
• +3 more

Marc Schmidt is a Professor of Biology at the University of Pennsylvania's School of Arts & Sciences, co-directing the Biological Basis of Behavior Program. He holds a B.A. in Biology from Swarthmore College (1986) and a Ph.D. in Neuroscience from Colorado State University (1993), followed by postdoctoral work at the California Institute of Technology in Neuroethology (1993–1999). His research focuses on neural mechanisms underlying courtship behaviors in songbirds, particularly the brown-headed cowbird, integrating neurobiology, computational methods, and engineering to study vocal and social displays. Key projects include analyzing neural circuits for vocal production, respiratory control, and female mate choice using a 'smart aviary' equipped with computer vision and wireless neural recording systems. Collaborations span engineering, physics, and other disciplines to track social behavior dynamics and neural activity in naturalistic settings. Research highlights include unraveling the role of the 'song system' in coordinating non-vocal courtship behaviors and linking brain activity to social context. Schmidt's work bridges neural circuitry with behavioral outcomes, emphasizing interdisciplinary approaches to understand complex social interactions. His lab employs advanced tracking systems and computational models to quantify group behavior across breeding seasons, aiming to predict and explain social network dynamics. He teaches courses in cellular/molecular neurobiology and animal behavior, contributing to both undergraduate and graduate education. Publications span vocal motor control, norepinephrine modulation, and social network analysis. His NSF-funded 'smart aviary' project exemplifies translational research, merging engineering and biology to study avian social behavior. Schmidt's contributions advance our understanding of neural mechanisms behind social communication and the evolution of courtship displays in vertebrates.

• Biomedical Engineering
• Nanotechnology
• Microelectronics
• +5 more

Professor Omid Kavehei is a Professor of Intelligent Microsystems in the Faculty of Engineering at the University of Sydney, serving as Deputy Head of the School of Biomedical Engineering. Previously, he held roles as a Research Fellow at the University of Melbourne and Lecturer at RMIT University. His research focuses on biomedical microsystems, nanotechnology, and brain-inspired hardware for healthcare applications, particularly epilepsy monitoring and seizure prediction. Education: PhD (specific institution not explicitly stated) His work bridges nanoelectronics and healthcare, aiming to develop low-power, brain-inspired devices for sensory perception and medical diagnostics. Key interests include neuromorphic engineering, wearable sensors, and AI-driven medical systems. Awards include the Ramaciotti Biomedical Research Award (2021), Microsoft AI for Accessibility Grant (2019), and multiple teaching/research excellence awards from the University of Sydney. His recent work explores neuromorphic cytometry for cell analysis, edge AI for ECG/EEG diagnostics, and closed-loop neurostimulation systems. Collaborations include the Sydney Nano Institute, Brain and Mind Centre, and industry partners like Microsoft. Current research students are advancing topics like bio-inspired algorithms for seizure detection, hardware-friendly machine learning models, and flexible sensor systems for aquatic environments. Grants include funding for neurophysiology platforms, quantum sensors, and semiconductor design. Labs/teams: Involved in the Centre for Drug Discovery Innovation and collaborations across engineering, neuroscience, and clinical domains.