Find Academic Supervisors

• Epilepsy
• Neurology
• Neural Networks
• +5 more

Aline Herlopian, MD, is an Associate Professor of Neurology at Yale School of Medicine, specializing in epilepsy and treatment-resistant seizures. She serves as Medical Director of the Clinical Neurophysiology/EEG Lab and Director of Clinical Trials in Epilepsy. Her clinical focus includes catastrophic epilepsies and innovative treatments like brain stimulation, laser therapy, and surgical resection. Clinical Epilepsy Fellowship, Massachusetts General Hospital (2017) Clinical Neurophysiology Fellowship, Massachusetts General Hospital (2016) Neurology Residency, University of Arkansas for Medical Sciences (2015) MD, American University of Beirut (2008) Her research explores neural network dynamics in epilepsy, EEG pattern classification via machine learning, and global health applications in neurological care. She has authored 15+ publications in 2024-2025, including peer-reviewed articles and book chapters on epilepsy subtypes and surgical approaches. Inaugural Global Health Education Innovation Award (2025) Dr. Herlopian leads clinical trials in epilepsy and collaborates extensively with Yale Institute for Global Health. She is a renowned advisor for patient education, emphasizing seizure demystification through analogies, and contributes to Yale Co-Authors networks in neurology research.

Miler T. LeeView profile

Associate Professor

• Gene Regulation
• Developmental Biology
• Computational Genomics
• +9 more

Miler T. Lee is an Associate Professor at the University of Pittsburgh , focusing on gene regulation during early embryonic development through high-throughput experimental and computational genomics. He earned his Ph.D. in Genomics and Computational Biology in 2009 from the University of Pennsylvania under Dr. Junhyong Kim, followed by postdoctoral work with Dr. Antonio Giraldez at Yale University. Joining the university in 2016, his research spans maternal-to-zygotic transition (MZT), RNA stability, pluripotency networks, and evolutionary developmental biology, utilizing model organisms like zebrafish, Xenopus, and Hydractinia symbiolongicarpus. Key Research Themes: Maternally inherited RNA dynamics during embryogenesis Mechanisms of RNA degradation and transcriptome remodeling Evolution of pluripotency networks in hybrid species Role of zinc signaling in fertilization barriers Computational tools for RNA regulation and sensing Scientific Awards: Pan-American Society for Evolutionary Developmental Biology Junior Faculty Award (2024) Outstanding New Investigator – International Xenopus Board (2023) Basil O'Connor Scholar – March of Dimes (2017-2019) Recent publications highlight his work on enhancer classification, RNA degradation mechanisms, and cross-species MZT comparisons. His lab develops innovative methods like RESA for regulatory sequence analysis and studies evolutionary divergence in RNA localization patterns. While the articles span computational and experimental approaches, they consistently address RNA's role in cellular identity, developmental timing, and evolutionary adaptation. Applications include understanding pluripotency, designing RNA biosensors, and elucidating fertilization barriers. Prospective Ph.D. students are encouraged to contact him for opportunities in gene regulation, development, evo-devo, and computational genomics.

• high resolution MRI
• visual perception
• functional imaging
• +6 more

Reza Farivar-Mohseni is an Associate Professor at McGill University , affiliated with the Faculty of Medicine and Health Sciences and the Department of Ophthalmology and Visual Sciences . He serves as a Scientist at the RI-MUHC (Montreal General Hospital site), contributing to the Brain Repair and Integrative Neuroscience (BRaIN) Program and the Centre for Translational Biology . Research Interests: Dr. Farivar-Mohseni’s work focuses on cortico-cortical communication, information processing in the brain, and disruptions in neurological disorders like traumatic brain injury. He specializes in advancing non-invasive brain imaging (MRI) for both fundamental and clinical applications, particularly improving concussion detection and diagnosis. Publications: His research spans high-resolution MRI, visual perception, and functional imaging. Key themes include depth-cue invariance in object recognition, gamma-band neural representations, and cortical deficits in amblyopia. Recent studies (2025–2022) address computational neuroscience, vision screening tools, and neural imaging techniques. Labs & Collaborations: He collaborates with the MGH-MRI Research Platform and works within the Centre for Translational Biology , focusing on translating imaging advancements into clinical tools.

Ali ShojaieView profile

Professor

• Biostatistics
• Statistics
• Machine Learning
• +4 more

Ali Shojaie is a Professor of Biostatistics and Statistics at the University of Washington, serving as Associate Chair for Strategic Research Affairs in the Department of Biostatistics. He leads the Summer Institute for Statistics in Big Data (SISBID) and the Data Management and Statistics (DMS) Core for the UW Alzheimer's Disease Research Center. His research focuses on developing statistical and machine learning methods for high-dimensional data, with applications in genomics, neuroscience, and public health. Shojaie's work includes advancements in graphical models, Granger causality, and spatial statistics. He has contributed to methodologies for analyzing networks from time series and spatial data, with applications in understanding gene regulatory networks and brain connectivity. His recent projects involve NIH-funded grants exploring gene-phenotype associations using omic data and explainable machine learning for brain stimulation research. Scientific awards include the 2022 Leo Breiman Award from ASA's Statistical Learning and Data Science section, and election as a Fellow of the Institute of Mathematical Statistics (IMS) and American Statistical Association (ASA). He serves on editorial boards for journals like the Journal of the American Statistical Association and Biometrika. Shojaie advises numerous PhD students and postdocs, many of whom have secured academic and industry positions. His lab develops open-source software tools, including the netgsa and ngc packages for network analysis and Granger causality estimation.

• Survival Analysis
• Longitudinal Data Analysis
• High-Dimensional Data Analysis
• +8 more

Bin Nan serves as Chancellor's Professor in the Department of Statistics at the University of California, Irvine, where he develops statistical and machine learning methodologies to advance biomedical research and improve human health outcomes through rigorous data analysis. His educational credentials demonstrate a strong quantitative foundation: Ph.D. in Biostatistics, University of Washington (2001) M.S. in Biostatistics, University of Washington (1999) M.S. in Statistics, Virginia Commonwealth University (1997) M.S. in Aerospace Engineering, Beijing University of Aeronautics & Astronautics (1987) B.S. in Aerospace Engineering, Beijing University of Aeronautics & Astronautics (1984) Nan's research program focuses on developing cutting-edge statistical methods for survival analysis, longitudinal data, high-dimensional inference, and machine learning, with direct applications to epidemiology, bioinformatics, and brain imaging. His work addresses critical challenges in biomedical data such as temporal dependence in neuroimaging sequences, estimation of large correlation matrices, and analysis of disease onset with terminal events, all aimed at identifying biomarkers for earlier disease diagnosis. Analysis of his recent publications (2015-2023) reveals a consistent trajectory toward methodological innovation in handling complex biomedical data structures, particularly through de-biased lasso techniques for survival models, neural network applications to censored data, and specialized approaches for longitudinal data with terminal events. These advances predominantly support Alzheimer's disease research and transplant outcome studies. No specific scientific awards were documented in the source material. His research program maintains continuous funding through National Science Foundation and National Institutes of Health grants, including a recent $1.8 million award for Alzheimer's disease methodology development. Nan actively collaborates with the UCI Alzheimer's Disease Research Center and UCI Center for the Neurobiology of Learning and Memory, though student advising details were not provided. His teaching portfolio includes advanced graduate courses in probability theory, survival analysis, and high-dimensional inference. Nan operates within interdisciplinary biomedical research teams focused on translating statistical innovation into clinical applications, particularly through brain imaging analysis and biomarker identification for neurodegenerative diseases.

Michael EconomoView profile

Assistant Professor

• Systems Neuroscience
• Motor Control
• Neural Circuits
• +3 more

Michael N. Economo, PhD, is an Assistant Professor in the Department of Biomedical Engineering at Boston University. His research focuses on neural circuits controlling movement, leveraging cutting-edge optical, electrophysiological, and genetic tools. He holds affiliations with Neuroscience & Neuroengineering and Photonics & Optical Systems programs. Education: PhD in Biomedical Engineering from Boston University, B.S. Biomedical Engineering and B.A. Mathematics from Duke University. Research Interests: Systems neuroscience, motor control, long-range neural circuits, computational neuroscience, neurotechnology. His lab investigates how neural circuits across brain regions coordinate movement using advanced techniques like optogenetics, in vivo imaging, and transcriptomics. Key Projects: Orofacial motor control, voltage imaging with TICO microscopy, neural circuit dissection. Technologies: Neuropixels probes, fluorescent voltage indicators, single-cell RNA sequencing. Notable Awards: NSF CAREER (2023), Scialog Fellow (2023), Whitehall Foundation Young Investigator Award (2021). Advising & Grants: Supervises graduate students (e.g., Munib Hasnain, Jackie Birnbaum) and postdocs (e.g., Vicky Moya, Yujin Han). Lab members focus on motor planning, neuromodulation, and neural dynamics. Labs/Teams: The Economo Lab collaborates on neurotechnology development and integrates interdisciplinary approaches from engineering and biology. Affiliated with BU’s Graduate Program in Neuroscience.

Andrea FaliniView profile

Professor

• Advanced MR Techniques
• Neuro-oncology
• Degenerative Diseases
• +3 more

Andrea Falini is a Full Professor of Neuroradiology at the Vita-Salute San Raffaele University (School of Medicine). He holds leadership roles including Head of the Neuroradiology Department at the Scientific Institute S. Raffaele Hospital and Head of the Advanced Diagnostic in Neuro-oncology Unit. His career spans clinical, academic, and administrative roles since 1991, with extensive experience in neuroradiology, neuro-oncology, and neuroimaging research. Education: MD (1986, University of Milan), PhD in Neurological Sciences (1989), and specialized training in Neurology and Radiology at leading institutions, including a visiting scholar position at UCSF (1996). Research interests focus on advanced MRI techniques, neuro-oncology, neurodegenerative diseases, and cognitive neuroscience. His work emphasizes functional MRI, diffusion tensor imaging, and clinical applications in glioma management and neurodegenerative disorders. Awarded the 1989 'De Visart' Prize and grants supporting his international collaborations. He has authored 218+ peer-reviewed articles, with an H-index of 40+, and actively contributes to academic committees and international conferences. Leadership roles include Vice-Director of the Neuroscience Division (2014–present) and coordination of the BraiMap Research Program. His academic teaching spans neuroradiology, biomedical engineering, and cognitive neuroscience courses.

• Neurology
• Neurocritical Care
• Electroencephalography (EEG)
• +2 more

Christine Eckhardt is an Assistant Professor in the Department of Neurology at the T.H. Chan School of Medicine (UMass Chan Medical School), specializing in Neurocritical Care. She earned her MD from Harvard Medical School and holds an MS degree. Education: MD, Harvard Medical School, Boston, MA MS (unspecified field) Dr. Eckhardt's research focuses on neurocritical care, neurotoxicity syndromes, and EEG-based diagnostics. She develops quantitative EEG methods for assessing immune effector cell-associated neurotoxicity (ICANS) and delirium severity, with applications in CAR T-cell therapy and critical care neurology. Her recent publications (2022–2023) emphasize automated neurotoxicity detection , EEG signal processing , and health equity disparities in heart failure care. Key subfields include neurocritical care, computational neuroscience, and clinical outcome modeling.

Rémi GiraudView profile

Associate Professor

• Image processing
• Deep learning
• Computer vision
• +3 more

Rémi Giraud is an Associate Professor at ENSEIRB-MATMECA (Bordeaux INP) in the Electronic department, conducting research at the IMS laboratory within the Signal and Image Processing group (MOTIVE team). He is also a member of the In2Brain research group. Dr. Giraud received his M.Sc. in telecommunications from ENSEIRB-MATMECA and a Master's in signal and image processing from the University of Bordeaux in 2014, graduating with honors as top of his class. He completed his Ph.D. in computer science at the University of Bordeaux in 2017, followed by a year as Assistant Professor before becoming Associate Professor in 2018. Current position: Associate Professor at ENSEIRB-MATMECA (Bordeaux INP), Electronic department Research affiliation: IMS laboratory, Signal and Image Processing group, MOTIVE team Additional affiliation: In2Brain research group Education: PhD in Computer Science (2017, University of Bordeaux), M.Sc. in Telecommunications and Signal/Image Processing (2014, ENSEIRB-MATMECA and University of Bordeaux) His research focuses on image processing and analysis, deep learning, and computer vision, with particular expertise in (un)supervised image segmentation, colorization, matching techniques, irregular under-representations (superpixels), spatial relations, and medical imaging (3D MRI applications). His work bridges theoretical computer vision with practical medical applications, developing algorithms that enhance image understanding in both general and specialized contexts. Dr. Giraud has developed several significant methodologies including SCALP (Superpixels with Contour Adherence using Linear Path), TASP (Texture-Aware SuperPixel), DSP (Dual Superpixel Descriptors), and NNSC (Nearest Neighbor-based Superpixel Clustering). His publications demonstrate consistent advancement in superpixel segmentation techniques with increasing focus on medical imaging applications, particularly brain MRI analysis. He currently supervises multiple PhD students including Julien Walther (working on Deep Learning Models from Structural Image Representations), Eloi Navet (An AI Assembly for Neurological Disease Prediction), Edern Le Bot (Holistic Brain MRI Segmentation), and Matthieu Vilain (Semi-supervised Deep Learning for image sequences). His research has resulted in numerous publications in top-tier conferences and journals, with a clear trajectory from theoretical algorithm development to practical implementation in medical contexts.

• Neuroimaging
• Alzheimer's Disease
• Neurodegenerative Disorders
• +5 more

Dr. Elisenda Bueichekú serves as a Research Scientist at the Yale School of Medicine within the Radiology & Biomedical Imaging Department . Her work focuses on neuroimaging applications in neurodegenerative disorders, particularly Alzheimer’s disease progression and memory systems analysis. She collaborates with leading researchers in the Mental Health PET Radioligand Development (MHPRD) Program and the PET Core facility. Primary Affiliation: Yale School of Medicine Department: Radiology & Biomedical Imaging Research Programs: MHPRD Program, PET Core Her research integrates multimodal neuroimaging techniques to investigate: Tau pathology propagation patterns Connectome-based disease modeling Cortical hub analysis in memory systems Cognitive resilience mechanisms Neuroimaging of anosognosia Functional network contributions to creativity Dr. Bueichekú contributes to translational research through: Advanced PET/MRI methodologies Spatiotemporal disease progression mapping Development of imaging-based biomarkers Recent publications demonstrate expertise in: Alzheimer’s disease neuroimaging Tau and amyloid co-accumulation Functional connectivity analysis Memory system characterization Scientific contributions include: 2025 Center for Brain & Mind Health Pilot Grant Key publications in top-tier journals (Nature Aging, Alzheimer's & Dementia, etc.)

• Magnetic resonance spectroscopic imaging
• Tumor micro-environment imaging
• Multinuclear MRI (¹H/²³Na)
• +4 more

Sandeep Kumar Mishra, PhD, is an Associate Research Scientist in the Department of Radiology & Biomedical Imaging at Yale School of Medicine, where he holds a primary appointment in the Magnetic Resonance Research Center within the Division of Bioimaging Sciences. He completed his doctoral training at Pondicherry University (2017) and finished post-doctoral research at Yale in 2024 before transitioning to his current research-intensive faculty role. Education: PhD, Pondicherry University – 2017 Post-doctoral Associate, Yale University – 2024 Research Focus: Mishra’s work integrates multinuclear magnetic resonance spectroscopy, responsive paramagnetic probes, and nano-constructs to quantify the tumor microenvironment. Major themes include in-vivo mapping of interstitial pH and sodium gradients in gliomas, development of Fe(II)/Co(II)/Ni(II)-DOTA tetraglycinate complexes for simultaneous pH–temperature sensing, and engineering dual-modal nano-agents that couple MR angiography with therapeutic delivery (chemo-photothermal, cryo-ablation, MMP inhibition). Publication Trends: Across 28 peer-reviewed articles (2016-2025) he demonstrates a sustained trajectory in cancer imaging, moving from theranostic nanoparticles toward sophisticated spectroscopic imaging of tumor acid–base and ionic homeostasis, with increasing translational orientation involving rodent glioma and hepatocellular carcinoma models. Collaborations & Affiliations: He is embedded in Yale’s inter-disciplinary MR research ecosystem, collaborating recurrently with faculty in Radiology, Biomedical Engineering, and the Magnetic Resonance Research Center (D. Coman, F. Hyder, P. Herman, J. Verhagen, J. Santana, A. Shewarega). Contact: sandeepkmishra11@gmail.com | Magnetic Resonance Research Center, 300 Cedar Street, New Haven, CT 06519, USA

Nikolaus RajewskyView profile

Professor

• RNA Biology
• Gene Regulation
• Single-Cell Transcriptomics
• +6 more

Nikolaus Rajewsky is a leading Professor at the Max Delbrück Center for Molecular Medicine (MDC) and Charité – Universitätsmedizin Berlin , where he founded and directs the Berlin Institute for Medical Systems Biology (BIMSB) . His lab integrates experimental (biochemistry, molecular biology) and computational (bioinformatics, physics) approaches to study RNA regulation in gene expression , with applications to developmental biology, regeneration, neurodegenerative diseases, and cancer . Using model systems like C. elegans , planaria, and human brain organoids, his team pioneers cutting-edge methods such as MirDeep , DistMap , and FLAM-seq for RNA analysis. His research focuses on single-cell transcriptomics , spatial RNA sequencing , and circular RNA (circRNA) regulation , revealing novel roles for circRNAs like CDR1as in neuropsychiatric disorders. Recent work includes 3D tumor microenvironment mapping and computational modeling of RNA metabolism in diseases. Scientific Awards : Gottfried Wilhelm Leibniz Prize (2012) EMBO Membership (2010) Honorary PhD, Sapienza University of Rome (2014) Berlin Science Award (2009) His team's recent articles highlight breakthroughs in 3D spatial transcriptomics , circRNA degradation mechanisms , and mitochondrial disease modeling using human brain organoids. The lab actively collaborates with clinical partners across Charité and European institutions, driving the LifeTime initiative for cell-based interceptive medicine.

Marlene BehrmannView profile

Professor

• Cognitive Neuroscience
• Cognitive Science
• Visual Perception
• +4 more

Marlene Behrmann is the Thomas S. Baker University Professor of Psychology and Cognitive Neuroscience at Carnegie Mellon University (CMU), affiliated with the Dietrich College of Humanities and Social Sciences. She leads the Behrmann Lab, which moved to the University of Pittsburgh in 2023. Her research focuses on visual cognition, object recognition, and neural mechanisms of perception, with a particular emphasis on face and word recognition. Behrmann holds a B.A. and M.A. in Speech and Hearing Therapy and a Ph.D. in Psychology from the University of Toronto. She is a leader in her field, recognized by her induction into the National Academy of Sciences (2015) and the American Academy of Arts and Sciences (2019). Her work combines neuropsychological studies of patients with brain damage, neuroimaging, and computational modeling to explore visual processing. Recent research highlights include studies on dorsal-ventral pathway interactions, functional reorganization post-hemispherectomy, and autism-related sensory processing differences. Behrmann has advised numerous graduate students and postdocs, contributing to their academic and professional development. Key awards include her National Academy of Sciences membership and American Academy of Arts and Sciences fellowship. Her lab collaborates widely, publishing in top journals like Cerebral Cortex , PNAS , and Trends in Cognitive Sciences . She also engages in translational research to improve interventions for perceptual and cognitive disorders.

Silvia ArberView profile

Professor

• Molecular and cellular mechanisms of neuronal differentiation
• Neuronal circuit development and connectivity
• Motor system development and function
• +7 more

Silvia Arber holds a joint appointment as Full Professor for Neurobiology/Cell Biology at the Biozentrum, University of Basel, and serves as Senior Group Leader at the Friedrich Miescher Institute (FMI) in Basel, Switzerland. Her laboratory investigates the organization, function, and development of neuronal circuits controlling motor behavior, with a particular focus on how these circuits enable precise movement control. Arber obtained her PhD in 1996 from the Friedrich Miescher Institute under Pico Caroni, followed by postdoctoral training with Thomas Jessell at Columbia University (1996-2000), where she studied transcription factors in spinal cord neuronal differentiation. Her educational background includes Biology II studies at the Biozentrum of the University of Basel with graduation in Cell Biology (1987), a diploma thesis at the FMI (1990), and graduate work at the FMI (1992). Her research program centers on elucidating how neuronal circuits orchestrate accurate motor behavior in response to sensory cues and voluntary movement initiation. Using mouse as a model system, her laboratory employs multi-faceted approaches including advanced mouse genetics, viral technologies for transsynaptic circuit tracing, optogenetics and pharmacogenetics for functional manipulation, quantitative behavioral analysis, electrophysiology, and gene expression profiling. Her work has revealed precise synaptic interactions within dedicated motor circuit modules throughout the nervous system and how these impact function, with implications for understanding diseases causing motor deficits and spinal cord injury. Analysis of Arber's publication record shows a consistent focus on motor circuit organization, with particular emphasis on transcriptional control mechanisms, circuit connectivity mapping, and the relationship between developmental processes and functional circuit organization. Her work bridges molecular, cellular, and systems neuroscience, providing fundamental insights into how the nervous system controls movement. The Brain Prize (2022) Elected to the National Academy of Sciences of the United States (2020) Physiological Society Annual Review Prize Lecture (2019) Pradel Research Award (2018) W. Alden Spencer Award (2018) Louis-Jeantet Prize for Medicine (2017) ERC Advanced Grant (2010-2015) EMBO Member (2005) EMBO Young Investigator Award (2001) While specific students are not listed in the provided materials, Arber's laboratory has received significant research funding including an ERC Advanced Grant (2010-2015) and multiple prestigious awards supporting her research program. Her laboratory at the Biozentrum (Room 11.038) collaborates closely with the Friedrich Miescher Institute, where she serves as Senior Group Leader. The research group employs cutting-edge technologies for neural circuit analysis and has contributed fundamental insights into motor circuit organization, with implications for understanding and potentially treating movement disorders and spinal cord injuries.

Danilo BzdokView profile

Associate Professor

• Computational Biology
• Deep Learning
• Large Language Models (LLM)
• +5 more

Danilo Bzdok is an Associate Professor in the Department of Biomedical Engineering at McGill University’s Faculty of Medicine and a Canada CIFAR AI Chair at Mila – Quebec Artificial Intelligence Institute. He holds dual expertise in systems neuroscience and machine learning, with two doctoral degrees: one in neuroscience from Forschungszentrum Jülich (Germany) and another in computer science (machine learning statistics) from INRIA–Saclay and Neurospin (France). His research bridges computational neuroscience and AI, focusing on understanding human intelligence through neuroimaging and biomedical data. Education: PhDs in Neuroscience (Jülich) and Computer Science (INRIA/Neurospin). Postdoctoral training at Harvard Medical School. Current affiliations include McGill University and Mila. Research interests span computational biology, deep learning, LLMs, and their applications in neuroimaging, precision medicine, and neurodegenerative diseases. Over 150+ peer-reviewed publications, with recent work on LLMs in autism diagnostics, brain network modeling, and social neuroscience. Key Awards: Canada CIFAR AI Chair. Lab focuses on interdisciplinary projects like AI4Science, neuroimaging analysis, and AI ethics. Supervises a dynamic team of PhD/Master’s students and postdocs. Collaborations include clinical institutions and industry partners through Mila’s Applied Research programs.