Find Academic Supervisors

• Autism Spectrum Disorder
• Neurodevelopment
• Neuroanatomy
• +9 more

David G. Amaral is a Professor in the Department of Psychiatry and Behavioral Sciences at the University of California, Davis, School of Medicine. His research is centered on the neurobiological underpinnings of autism spectrum disorder (ASD), with a focus on brain development, neuroanatomy, and translational neuroscience. He leads major initiatives such as the Autism Phenome Project and Autism BrainNet, fostering collaboration across institutions and disciplines. His research interests span autism neurobiology, neurodevelopment, brain imaging, genomics, and primate models of neurodevelopmental disorders . He investigates early brain overgrowth, amygdala development, cortical structure, sex differences, and metabolic and immune contributions to ASD. His work integrates human studies with nonhuman primate models to bridge basic science and clinical understanding. The most recent publications highlight trends in longitudinal neuroimaging of ASD, sex differences in brain development, maternal immune activation, genetic and metabolic biomarkers, and comparative neuroanatomy . His team frequently employs advanced MRI, transcriptomics, and stereological methods to uncover mechanisms of atypical brain development. Dr. Amaral is actively involved in scientific leadership and editorial roles, contributing to journals such as Autism Research . He is a key member of large-scale consortia including SPARK and the Pediatric Imaging, Neurocognition, and Genetics (PING) Study, which have advanced population-level understanding of brain development. He mentors a broad network of researchers and collaborates extensively with scientists across neuroscience, psychiatry, immunology, and genetics. His laboratory and research teams are embedded within the UC Davis MIND Institute, a leading center for neurodevelopmental disorders research.

Syed Fawad HussainView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Multi-View Learning
• +7 more

Dr. Syed Fawad Hussain is an Associate Professor in the School of Computer Science at the University of Birmingham, Dubai campus. He is actively engaged in research and academic leadership, contributing significantly to the fields of artificial intelligence and machine learning. Education: PhD in Computer Science, Grenoble Alpes University, France (2010) MSc in Computer Science, Sorbonne University (Pierre and Marie Curie), Paris, France (2006) BS in Computer Science (2003) Dr. Hussain's research focuses on developing advanced machine learning algorithms for high-dimensional data, with specializations in multi-view learning, co-clustering, and semantic kernels. His work spans interdisciplinary domains including mobile healthcare, social media analysis, and cultural heritage preservation. He applies AI to classify ECG/EEG signals, detect diseases like schizophrenia and NAFLD, restore ancient manuscripts, and improve wireless communication systems. His recent publications reveal a strong trend in applying deep learning and ensemble methods to real-world problems across healthcare, defense, transportation, and digital humanities. He frequently collaborates on projects involving signal processing, image classification, and data fusion. Dr. Hussain has supervised numerous graduate students and co-authored with researchers across multiple disciplines. He has contributed to national-level academic development in Pakistan as co-chair of the Higher Education Commission's curriculum revision committee. Scientific Contributions: Published in high-impact journals such as Scientometrics , Information Fusion , Expert Systems with Applications , and Knowledge-Based Systems . Active in both theoretical and applied AI research. Contributor to national curriculum development in computer science. He is affiliated with the University of Birmingham’s Dubai campus and previously served as a faculty member and dean at GIK Institute, Pakistan. His work continues to bridge theory and application in artificial intelligence.

• Psychiatric Genetics
• Statistical Genetics
• Neuroimaging
• +5 more

Honorary Professor Sarah Medland is a distinguished Psychiatric and Statistical Geneticist at the University of Queensland's School of Psychology. She also serves as the Coordinator of the Mental Health Research Program and Group Leader (Psychiatric Genetics) at QIMR Berghofer Medical Research Institute. Professor Medland chairs the genetics working group of the ENIGMA neuroimaging consortium and is an active member of the Psychiatric Genomics Consortium. Professor Medland earned her PhD in Psychology from the University of Queensland in 2006, receiving the Dean's Award for Outstanding Research Higher Degree Thesis. She completed her BA Hons in Psychology (with Psychology Double Major and English Minor) at the University of Queensland in 2000. Professor Medland's research bridges Genetics, Psychology, Neuro-Imaging, Health Economics and applied Statistics, with a focus on understanding the genetic and environmental contributions to human behaviour and disease. Her work spans psychiatric genetics, statistical genetics, neuroimaging, and mental health genetics. She has published extensively with 5 book chapters, 419 journal articles, 64 conference papers, and 1 thesis to her name. Her recent publications demonstrate a strong focus on genetic contributions to brain structure and function, psychiatric disorders, and neurodevelopmental conditions, frequently employing genome-wide association studies, neuroimaging techniques, and advanced statistical methods. Order of Australia Medal (OAM) Fellow of the Australian Academy of Social Sciences (FASSA) Fellow of the Australian Academy of Health and Medical Sciences (FAHMS) Dean's Award for Outstanding Research Higher Degree Thesis Professor Medland leads the Psychiatric Genetics group at QIMR Berghofer Medical Research Institute, where she coordinates the Mental Health Research Program. Her research program involves large-scale genetic studies, neuroimaging analyses, and collaborations with international consortia including ENIGMA and the Psychiatric Genomics Consortium. She has supervised numerous students and early-career researchers in the fields of psychiatric genetics and neuroimaging.

• Machine Learning
• Computational Science
• Artificial Intelligence
• +3 more

Xi Yu is a Researcher at the Computational Science Initiative of Brookhaven National Laboratory, with expertise in Machine Learning, Artificial Intelligence, and Computational Science. Previously, they served as a Postdoctoral Research Associate (2022–2025) and Research Intern at Mitsubishi Electric Research Laboratories (2021). Ph.D. in Electrical Engineering, University of Florida (2022) M.S. in Electrical Engineering, University of Florida (2019) Their research spans domain generalization, adversarial robustness, information theory, and coral image segmentation, with a focus on applying neural networks and entropy functional methods to diverse challenges in AI and environmental science. Recent publications highlight work on AI training energy efficiency, CLIP-based image-text alignment, and information bottleneck theory. Notable awards include the NYU Tandon Faculty First Look Fellowship (2024) and recognition at ICDM (2021).

Christine BrownView profile

Professor

• Immunotherapy
• Cancer Research
• Cellular Immunology
• +3 more

Christine Brown, Ph.D., is a Professor in the Departments of Hematology & Hematopoietic Cell Transplantation and Immuno-Oncology at City of Hope. As Deputy Director of the T Cell Therapeutics Research Laboratory and holder of the Heritage Provider Network Professor in Immunotherapy chair, she leads preclinical and clinical programs in CAR T-cell therapy for hematological and solid tumors. Ph.D., Cell and Molecular Biology (UC Berkeley, 1998) B.Sc., Combined Science with Biochemistry emphasis (Santa Clara University, 1990) Postdoctoral Fellowship, Leukemia & Lymphoma Scholar (Pennsylvania State University) Her research focuses on chimeric antigen receptor (CAR) T-cell therapy for cancer, particularly brain tumors like glioblastoma. Key areas include CAR design optimization, T cell manufacturing, immunological assays, and animal models. She investigates L1-CAM and IL13Rα2 as tumor antigens while addressing challenges in T cell persistence, antigen specificity, and tumor microenvironment interactions. Recent publications highlight CAR T-cell applications in ovarian cancer, gliomas, and breast cancer brain metastasis, with emphasis on co-stimulatory signaling, mechanoporation delivery, and mathematical modeling of T cell dynamics. Her work is supported by grants including R01 FD005129 and California Institute for Regenerative Medicine funding. Howard Hughes Medical Institute Postdoctoral Fellowship (1998) Leukemia and Lymphoma Society Scholar (2000) City of Hope Values in Action Award (2012) Lymphoma SPORE Developmental Research Award (2013) She leads multifunctional teams translating immunotherapies to clinical trials, participates in regulatory processes, and contributes to consortia like the Caltech/UCLA/CHLA/COH Engineered Immunity group. Her lab's work spans basic discovery, preclinical validation, and first-in-human trials.

Ian van der LindeView profile

Associate Professor

• Vision Science
• Image Processing
• Cognitive Psychology
• +4 more

Dr. Ian van der Linde is a Reader (equivalent to Associate Professor) at Anglia Ruskin University, affiliated with the Faculty of Science and Engineering and the School of Computing and Information Science. He conducts cross-faculty research at the intersection of computer science, vision science, image processing, algorithms, and cognitive psychology, with a particular focus on the human visual system. His research expertise includes: Vision Science and Eye Research Image Processing and Computer Vision Cognitive and Behavioural Psychology Computational Methods in Neuropsychological Testing Dr. van der Linde's research primarily investigates gaze control, visual short-term memory, face perception, visual task planning, image quality assessment, multimodal binding, the impact of ageing on visual performance, and the computations performed in the early visual system. His work combines computer modeling with experimental psychology to understand human vision, with applications in healthcare, computer vision systems, and cognitive assessment tools. His recent publications demonstrate a consistent focus on visual short-term memory, particularly examining how humans bind visual features together, how this process changes with age, and how it relates to cognitive decline. His work also extends to facial recognition, image quality assessment, and the application of computational methods to neuropsychological testing. Scientific recognition includes: Fellow of the British Computer Society (FBCS) Fellow of the Higher Education Academy (FHEA) Chartered Engineer of the Engineering Council UK (CEng) The Wellcome Trust, 'I'm a Scientist, Get Me Out of Here', Winner, Nickel Zone, £500 Dr. van der Linde has supervised numerous PhD students across Computing, Psychology, and Vision Sciences, with research spanning audio signal processing, online security behaviors, cardiovascular bioinformatics, cloud computing adoption, and visual working memory. He has secured research funding from various sources including the Wellcome Trust, Home Office Scientific Development Branch, and Knowledge Transfer Partnerships. He is a member of the Computing, Informatics and Applications Research Group and teaches courses in Image Processing, Data Structures & Algorithms, and Core Mathematics for Computing.

• Neurodevelopmental Diseases
• Brain Trajectories
• Anorexia Nervosa
• +7 more

Clara Moreau is an Assistant Professor in the Department of Psychiatry and Addiction at the University of Montreal , where she leads the BRIGHT Lab (Brain Research using Imaging Genetics methods in Human Transdiagnostically) . Her work bridges neuroscience, genetics, and psychiatry to address neurodevelopmental and psychiatric conditions. Ph.D. in Neuroscience (2020), University of Montreal M.Sc. in Cognitive Sciences (2014), Cogmaster (ENS/Paris Descartes) B.Sc. in Psychology (2012), Paris Descartes University Her research focuses on neurodevelopmental diseases, particularly anorexia nervosa, where she investigates brain trajectories and relapse prediction through longitudinal studies at CHU Sainte-Justine Hospital. She co-leads the ENIGMA-Eating Disorders Initiative , a global neuroimaging project spanning 20 institutions, and directs the ENIGMA-rsfMRI working group to standardize functional MRI analysis. Key contributions include identifying thalamo-sensorimotor hyperconnectivity across psychiatric diagnoses, developing multiverse analytical approaches for fMRI reproducibility, and exploring brain plasticity in prolonged malnutrition contexts. Her work combines neuroimaging genomics, polygenic risk scores, and transdiagnostic frameworks to redefine psychiatric classification beyond symptomatology. Major funding : NIH R01 grant (1U01MH136221-01, 2025-2029) for studying eating disorders and clinical outcomes. 2025: Invited lecture at Douglas Mental Health Institute 2024: Keynote at ENIGMA Developmental Summit 2023: Seminar at TU Dresden 2022: Talk on genetic pleiotropy at Timone Institute

Irina StepanovView profile

Professor

• Public Health
• Environmental Health Sciences
• Tobacco Research
• +4 more

Irina Stepanov is a Professor at the University of Minnesota within the School of Public Health , specifically the Division of Environmental Health Sciences . She serves as Director of the Institute for Global Cancer Prevention Research and is a Masonic Cancer Center Member . Her academic credentials include a PhD in Chemistry from Moldova State University (2002) and postdoctoral training at the University of Minnesota Masonic Cancer Center. Research Focus: Environmental health sciences with emphasis on tobacco carcinogens, biomarker discovery, DNA adducts, mass spectrometry applications Awards: Delta Omega Public Health Honorary Society (2013), Masonic Scholar (2011) Leadership: Director of global cancer prevention institute, faculty member in MPaT graduate programs Her extensive publications in toxicology , epidemiology , and biochemical analysis demonstrate expertise in tobacco exposure biomarkers , cancer risk assessment , and public health policy development . Key collaborations include the Society for Research on Nicotine and Tobacco, American Association for Cancer Research, and American Chemical Society.

Nikolaus WeiskopfView profile

Professor

• Magnetic Resonance Imaging
• Neuroimaging
• Brain Microstructure
• +5 more

Professor Nikolaus Weiskopf serves as Managing Director of the Department of Neurophysics at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI-CBS) in Leipzig, Germany. With over 230 journal articles and numerous conference presentations, he is a leading authority in quantitative MRI techniques for studying brain microstructure in vivo. Dr. Weiskopf specializes in developing advanced MRI methods that provide non-invasive histological information about brain tissue. His research focuses on: Quantitative multi-parameter mapping (MPM) for in vivo histology High-resolution imaging of cortical layers and columns Spinal cord microstructure imaging Applications of ultra-high field (7T) MRI Neurodegenerative disease biomarkers His recent publications reveal a strong emphasis on pushing MRI technology to achieve microscopic-level insights about brain organization. His work bridges basic neuroscience with clinical applications, particularly in spinal cord injury and neurodegenerative conditions like Alzheimer's disease. Through correlative MRI-histology studies, his team establishes the biological basis of MRI signals, transforming quantitative MRI into a powerful tool for in vivo histology. Dr. Weiskopf leads the ERC-funded hMRI project focused on non-invasive in vivo histology of the brain and contributes significantly to the NISCI clinical trial investigating Nogo-A antibodies for spinal cord injury recovery. His laboratory develops and shares important neuroimaging tools including the hMRI toolbox for quantitative MRI analysis, which has been widely adopted by the research community.

• Applied Machine Learning
• Computer Vision
• Signal Processing
• +3 more

Atzori Manfredo is a Researcher at the School of Management, HES-SO Valais-Wallis, focusing on machine learning applications in biomedical engineering and digital health. His work bridges computer vision, signal processing, and clinical diagnostics, with emphasis on EMG-based prosthetic control, computational pathology, and neuroimaging reproducibility. Research interests span: Applied ML : Transfer learning, explainable AI, and self-supervised methods for medical data. Biomedical Engineering : EMG signal analysis for hand prosthetics, wearable sensors, and rehabilitation robotics. Digital Pathology : Whole slide image analysis, artifact mitigation, and multimodal data fusion for cancer diagnostics. His publications (2022-2024) reveal strong trends in addressing real-world challenges: improving robustness of EMG classification under dynamic conditions, enhancing reproducibility in neuroimaging studies, and developing open-source tools (e.g., SelfEEG, BIDSAlign) for EEG/EMG data processing. Cross-disciplinary collaboration is evident in veterinary radiology, ophthalmology, and ontology development for pathology data.

• Intelligent Assistive Robotics
• Robotics
• Computer Vision
• +4 more

Dan Withey is a Lecturer in Intelligent Assistive Robotics at the University of the West of England within the Faculty of Engineering and Technology , Department of Engineering, Design and Mathematics. With a background in Electrical and Computer Engineering and Biomedical Engineering, he has decades of industry experience in robotics R&D, computer vision, and telecommunications. His expertise includes autonomous robotics, signal processing, and machine learning. Academic Rank: Lecturer Department: Engineering, Design and Mathematics Withey’s research spans assistive technologies , robotics , and computer vision , focusing on applications like smart walker navigation, LiDAR-based mapping, and robotic posture control. His recent publications highlight interdisciplinary work in healthcare robotics , dynamic SLAM , and sensor fusion . He actively supervises PhD and Master’s students, blending academic rigor with real-world robotics challenges. Collaborations include sociology departments in Bulgaria, emphasizing human-centric robotic solutions. His work bridges theoretical innovation and applied engineering, particularly in autonomous navigation and machine learning for rehabilitation .

• Neuroscience
• Cognitive Neuroscience
• Affective Science
• +7 more

Florin Dolcos is a Professor in the Psychology Department and the Neuroscience Program at the University of Illinois in Urbana-Champaign, affiliated with the Beckman Institute. He directs the Social, Cognitive, Personality, and Emotional (SCoPE) Neuroscience Laboratory, focusing on the interplay between emotion and cognition. University: University of Illinois, Urbana-Champaign Departments: Psychology, Neuroscience Program Institute: Beckman Institute Lab: SCoPE Neuroscience Laboratory Research Interests: Florin Dolcos's work bridges Neuroscience , Cognitive Science , and Affective Science , with a focus on: Emotion-cognition interactions Memory and stress effects Neuroimaging techniques Moral psychology and decision-making Relational and source memory Emotion regulation and mental health Recent Publications Trends: His recent studies investigate how emotion divergently impacts cognition, stress effects on memory retrieval, moral judgment modeling, and trimodal brain imaging methods. These works often employ behavioral experiments, eye-tracking, and multimodal neuroimaging approaches. Labs & Teams: Dolcos leads the SCoPE Neuroscience Laboratory , fostering interdisciplinary research in cognitive and affective neuroscience across the University of Illinois system.

John H. Rossmeisl, Jr.View profile

Professor

• Neuro-oncology
• Comparative neurology
• Biomedical device development
• +3 more

John H. Rossmeisl, Jr. is a Professor of Neurology and Neurosurgery at Virginia Tech's Department of Small Animal Clinical Sciences within the Virginia-Maryland College of Veterinary Medicine. He serves as the Dr. and Mrs. Dorsey Taylor Mahin Professor of Neurology and Neurosurgery and currently holds the position of Associate Department Head. MS (2003), DVM (1997) - Virginia-Maryland College of Veterinary Medicine BA in Zoology and German (1993) - University of New Hampshire Rossmeisl's research focuses on: Development of novel brain tumor therapeutics Blood-brain barrier disruption techniques Convection-enhanced drug delivery systems Comparative neuro-oncology models Medical device engineering for neurological applications Recent publications demonstrate expertise in: High-frequency irreversible electroporation (H-FIRE) Histotripsy ablation methods Neuroimaging biomarkers Molecular targeting of gliomas 3D-printed surgical guides Scientific awards include: Zoetis Award for Research Excellence (2014) Thompson Award (2011) Student AVMA Teaching Excellence Award (2008) As director of the Veterinary and Comparative Neuro-oncology Laboratory, he leads translational research programs that bridge veterinary and human medicine while maintaining active clinical and research collaborations across multiple institutions including Wake Forest University Comprehensive Cancer Center.

Mintai KimView profile

Professor

• Environmental Resilience
• Sustainability
• Ecological Design
• +6 more

Mintai Kim is a Professor at the School of Design at Virginia Tech, specializing in Landscape Architecture. His work bridges environmental disturbances with community resilience through two primary domains: nightscape research and Geodesign. Utilizing advanced technologies like smart sensors and brain imaging, he investigates light pollution impacts and coastal adaptation strategies. Education: Ph.D. in Environmental Planning (UC Berkeley, 2001), MLA in Landscape Architecture (UC Berkeley, 1994), BS in Landscape Architecture (University of Seoul, 1988) Dr. Kim's research emphasizes: High-resolution light pollution measurement Neurophysiological responses to day/night environments Geodesign applications for sea level rise resilience Feng Shui principles in landscape planning GIS integration for ecological design His publications span topics from urban land cover dynamics to pedestrian lighting safety , showcasing a multidisciplinary approach combining neuroscience, technology, and ecological design. Notable trends include: Longitudinal environmental monitoring Cognitive science applications in landscape Digital tools for climate adaptation Human-centered nightscape design Scientific recognitions include: CELA Excellence in Research Award (2018) Best Paper awards (2013, 2016, 2018) CAUS Scholarship Certificate ILAM Research Excellence Award

Diego Borro YagüezView profile

Professor

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +6 more

Diego Borro is a Full Professor (Catedrático) in Computer Science and Artificial Intelligence at TECNUN, Technological Campus of the University of Navarra , where he has been part of the faculty since 2004. He is a leading researcher at CEIT since 2003, focusing on Robotics, Virtual/Augmented Reality, Computer Vision, and Artificial Intelligence. His academic credentials include a PhD in Computer Science (2003) and an MS in Computer Science (2000) from the University of Navarra and University of Basque Country respectively. His research spans from 3D tracking and haptics to industry 4.0 applications and medical robotics, with over 34 journal papers and 65 conference articles. He has supervised 14 doctoral theses and participated in 55+ research projects. His leadership roles include heading CEIT's Simulation Unit (2012-2016) and Vision and Robotics (V&R) research line (2016-2022), currently serving as main researcher at Intelligent Systems for Industry 4.0 group (SS4I4). Accredited as Full Professor (Catedrático) by ANECA (3 sexenios) Member of IEEE, ACM, and Eurographics societies Key projects: STEPbySTEP exoskeleton benchmark, WARM AR maintenance systems, and inner ear drug delivery research