Dr. Cassandra Sampaio Baptista is a Lecturer at the University of Glasgow's School of Psychology & Neuroscience. Her research focuses on brain plasticity in adulthood, particularly exploring how experiences like skill learning or rehabilitation influence structural and functional changes in the brain. She employs neuroimaging techniques such as fMRI neurofeedback and MRI to investigate mechanisms of myelin and white matter plasticity. Her work emphasizes translational applications, including stroke rehabilitation and promoting healthy aging. Key contributions include demonstrating myelin's role in motor learning and developing MRI protocols for white matter analysis. She collaborates on projects funded by the BIAL Foundation (2025–2026) and has supervised multiple postgraduate students. Recent publications highlight studies on oligodendrocyte dynamics, neurofeedback interventions for stroke survivors, and cross-species neuroscience approaches. While no specific awards are listed, her extensive publication record reflects her leadership in neuroplasticity research.
Rebecca Schulman is an Associate Professor in the Department of Chemical and Biomolecular Engineering at the Whiting School of Engineering, Johns Hopkins University. She holds secondary appointments in Chemistry and Computer Science and is affiliated with multiple interdisciplinary institutes, including the Institute for NanoBioTechnology, the Hopkins Extreme Materials Institute, the Chemistry-Biology Interface Program, the Center for Cell Dynamics, and the Laboratory for Computational Sensing and Robotics. She currently co-directs the Passport to Future Technology Leadership program for PhD students. Research Interests: Schulman's research lies at the intersection of DNA nanotechnology, synthetic biology, and smart materials. Her group develops intelligent, adaptive biomolecular materials and nanostructures by integrating concepts from materials science, biochemistry, circuit design, and soft matter physics. The team focuses on engineering dynamic self-assembly processes using DNA to create reconfigurable materials, molecular circuits, and autonomous soft micro-robots. Key themes include self-healing nanostructures, feedback-regulated crystallization, programmable hydrogels, and synthetic genetic networks for materials control. Publication Trends: Her recent publications demonstrate a consistent focus on using DNA-based chemical reaction networks to program spatial and temporal behavior in materials. The work spans from fundamental mechanisms like catalytic polymerization and crystal growth regulation to applications in soft robotics, self-wiring circuits, and synthetic pattern formation. The research is highly interdisciplinary, combining synthetic biology with materials engineering to achieve life-like functionalities in non-living systems. Scientific Awards: AIMBE Fellowship Award Vannevar Bush Faculty Fellowship Award Hartwell Individual Biomolecular Research Award President’s Early Career Award in Science and Engineering (PECASE) DARPA Young Faculty Award DARPA Directors Fellowship NSF CAREER Award Turing Scholar Award DOE Early Career Award Advising and Grants: Schulman mentors graduate students and leads a vibrant research group focused on next-generation biomolecular engineering. Her work is supported by major federal grants, including the NSF CAREER, DOE Early Career, DARPA, and the Vannevar Bush Fellowship—a prestigious Department of Defense award for basic research. She is actively involved in training future leaders through programs like the Passport to Future Technology Leadership. Labs and Teams: The Schulman Lab at Johns Hopkins is a multidisciplinary team working on DNA-powered materials and molecular programming. The lab is embedded within several collaborative centers, enabling strong cross-departmental and cross-institutional research. Their work combines experimental biochemistry with theoretical modeling to design and implement complex molecular systems.
Carina Mallard is Professor of Experimental Perinatal Brain Injury Research and Pro-Vice-Chancellor at the University of Gothenburg since July 2023, where she oversees research infrastructure and chairs the Research Board. She previously served as Deputy Vice-Chancellor (2021–2023) and Head of Core Facilities (2018–2021). Her academic career began with a Physiology degree from Lund University and a PhD in Pediatrics at the University of Auckland (1995), followed by a professorship appointment in 2006. Her research focuses on perinatal brain injury , particularly in premature infants , investigating neuroinflammatory mechanisms maternal dietary interventions neurovascular unit dynamics microglia activation long-term consequences of maternal obesity . Recent publications highlight her work on neonatal rodent models , transcriptomic profiling , and anti-inflammatory therapies . Key themes include RNA degradation , mitochondrial protection , and immune-neurovascular interactions . She has supervised 20 doctoral students since 2004 and collaborates internationally with institutions like King's College London. Contact details include two institutional emails and physical addresses across Gothenburg's biomedical campuses. Her leadership roles span research strategy, doctoral education, and EU-level scientific initiatives.
Andrew D. White is an Associate Professor of Chemical Engineering at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from the University of Washington (2013). His research focuses on automating scientific discovery through AI, particularly leveraging large language models (LLMs) and deep learning techniques in chemistry. His lab develops agents that integrate literature analysis, hypothesis generation, and experimental design to advance fields like molecular dynamics and drug discovery. Education: PhD in Chemical Engineering, University of Washington, 2013 BS/MS (not explicitly stated in text, inferred from career timeline) Research Interests: Large language models for scientific automation Deep learning applications in chemistry and materials science Molecular dynamics simulations Scientific agents and autonomous systems Publications: His work includes groundbreaking studies on closed-loop AI systems for chemistry, federated learning in molecular property prediction, and multi-agent systems for drug discovery. Recent highlights include the Robin system and ChemCrow tools. Awards: Recipient of the NSF Career Award (2018), NIH Outstanding Investigator Award (2020), and the Curtis Teaching Award (2019). He also advises biotech companies and serves on the National Academy of Sciences' Chemical Sciences Roundtable. Grants & Funding: Supported by DOE, NSF (multiple grants including CBET-1751471), NIH (R35GM137966), and LLNL projects. Collaborates with institutions like Argonne National Lab and Qubit Pharmaceuticals. Labs & Teams: Leads the White Lab at Rochester and co-founded FutureHouse, a nonprofit advancing AI-driven scientific discovery. Supervises a multidisciplinary team of PhD students and postdocs in computational chemistry, AI, and biophysics.
Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.
Susanna Thon is an Associate Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University (JHU), affiliated with the Whiting School of Engineering. She serves as Associate Director of the Ralph O’Connor Sustainable Energy Institute (ROSEI) and a member of the Data Science and AI Institute. Her research focuses on nanomaterials engineering for optoelectronic devices, emphasizing solar energy conversion and sensing. Notable areas include plasmonic-photocatalytic systems using aluminum nanoparticles and nanostructured materials like colloidal quantum dots for next-generation devices. Thon holds a BSc from MIT (2005) and MSc/PhD in Physics from UC Santa Barbara (2008/2010). She joined JHU in 2013 after postdoctoral work at the University of Toronto. Her work is funded by agencies such as the NSF, U.S. Army, and Maryland Energy Innovation Institute. She has published over 50 peer-reviewed papers and received JHU’s Catalyst and Discovery awards. Key research projects include developing plasmonic systems to enhance light absorption in titanium dioxide and creating scalable fabrication techniques for optoelectronic materials. Thon’s team also advances quantum dot solar cells and novel characterization methods for energy materials. She actively participates in professional societies, including the Optical Society of America and IEEE. Her grants and collaborations aim to train the next generation in sustainable energy research, with recent initiatives funded through NSF and Space@Hopkins seed grants. Thon’s lab integrates nanophotonics, materials science, and machine learning to address global energy challenges.
Evelyn Lake is an Associate Professor in the Department of Radiology and Biomedical Imaging at Yale University, with affiliations to the Wu Tsai Institute and Yale Biomedical Imaging Institute. Her research focuses on functional neuroimaging, particularly using rodent models to study brain connectivity, neurovascular coupling, and disorders like Alzheimer’s disease and autism spectrum disorder. PhD in Medical Biophysics, University of Toronto (2016) Postdoctoral Associate, Yale University (2019) BSc (Honors) in Biophysics, University of Guelph (2010) Her work spans multimodal imaging techniques (e.g., simultaneous Ca2+ and fMRI), examining how genetic mutations (e.g., PTEN, KATNAL2) affect cerebrospinal fluid dynamics and neuronal connectivity. She investigates longitudinal changes in Alzheimer’s models and methodological aspects of animal neuroimaging, such as sample size optimization and awake imaging protocols. Recent publications highlight her contributions to understanding autism-related white matter abnormalities, transdiagnostic connectome predictive modeling, and the impact of neurovascular uncoupling in awake mice. Collaborations include Todd Constable, Francesca Mandino, Xilin Shen, and Xenophon Papademetris.
Dr. Merry Mani is an Associate Professor in Radiology and Imaging Sciences and Biomedical Engineering, specializing in biomedical imaging and signal processing. Her work focuses on advancing MRI-based imaging technologies to study neurological disorders such as Alzheimer's, Autism, and Epilepsy. She holds a Ph.D. in Electrical and Computer Engineering from the University of Rochester (2014) and completed a postdoctoral fellowship at the University of Iowa School of Medicine (2018). Her research combines biophysical modeling with machine learning to explore brain microstructures. Key achievements include the NNARSAD Young Investigator Grant and NIH-funded projects like 'Fast Multi-dimensional Diffusion MRI with Sparse Sampling'. Her lab develops cutting-edge reconstruction methods like qModeL and MUSSELS, prioritizing high spatio-temporal resolution imaging. Major contributions span diffusion MRI acquisition, model-based deep learning, and clinical applications in neurodegenerative diseases. Notable grants include NIH R01EB031169 for Alzheimer’s neurodegeneration studies and projects on rTMS for depression. Her work bridges imaging innovation with clinical impact, aiming to improve diagnosis and treatment through advanced imaging biomarkers.
Istvan Mody is a Professor at the University of California, Los Angeles (UCLA) with appointments in the Department of Neurology and Department of Physiology . His research focuses on synaptic signaling in health and disease, including mechanisms of GABAergic transmission, calcium homeostasis, and their roles in neurological disorders such as epilepsy, Alzheimer's disease, Huntington's disease, stress, alcoholism, and postpartum depression. He utilizes advanced techniques like patch-clamp electrophysiology, neuroanatomical and immunohistochemical methods, and molecular biology in animal models and human brain tissue . Research Interests: Dr. Mody investigates the physiology, pharmacology, and pathology of synaptic transmission and extrasynaptic receptor activation , with a particular emphasis on GABA(A) receptors and their subunit-specific modulation. His work explores how disruptions in excitation-inhibition balance contribute to neurological diseases, including mechanisms of tonic inhibition , calcium signaling , and neurosteroid interactions . He also studies the effects of chronic stress and hormonal fluctuations on neural excitability and behavior. Publications Trends: Recent studies highlight his work on gamma oscillations in Alzheimer's models, microglial dynamics , and rehabilitation strategies for stroke. His lab develops optical tools like dqGEVI for neuronal activity monitoring and investigates human brain organoids to model network dysfunction in epilepsy and intellectual disability. Laboratory Location: 635 Charles Young Dr S, Los Angeles, CA 90095, United States.
Sharon Abrahams is a Professor of Neuropsychology and holds a Personal Chair at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. She leads research in clinical and experimental neuropsychology, focusing on neurodegenerative diseases like motor neurone disease/ALS and frontotemporal dementia. Her work integrates neuroimaging, cognitive assessment, and clinical intervention. She is affiliated with the Euan MacDonald Centre for Motor Neurone Disease, the Centre for Clinical Brain Sciences, and Edinburgh Neuroscience. Current PhD students include Monica de Icaza Valenzuela, Debbie Gray, and Caroline McHutchison. Abrahams has secured over 17 research grants since 2008, including projects on cognitive screening in MND, apathy impact, and the ECAS tool. Her research emphasizes cognitive and behavioral changes in ALS, with a focus on early detection, staging, and patient quality of life. Notable contributions include the Edinburgh Cognitive and Behavioural ALS Screen (ECAS), validated across multiple languages and populations.
Duncan Astle is the Gnodde Goldman Sachs Professor of Neuroinformatics at the Department of Psychiatry, University of Cambridge. He serves as a Programme Leader at the Medical Research Council's Cognition and Brain Sciences Unit (MRC CBU) and is a Fellow of Robinson College. Astle heads the 4D Lab (Development, Dynamics, Disorders, Data Science), which provides a research home for approximately 15 Early Career Researchers working at the intersection of developmental cognitive neuroscience and advanced data science methodologies. Astle's research focuses on understanding childhood development through innovative analytical approaches. His work employs transdiagnostic methods to study children with attention, learning, and memory difficulties, moving beyond traditional diagnostic categories. He investigates how neural systems develop in childhood, how they relate to developmental disorders, and how they respond to intervention. His research integrates network science, machine learning, and generative modeling to capture the complexity of neurodevelopmental diversity, examining how cognitive skills, literacy, numeracy, and mental health interrelate over developmental time. His publication record reveals a strong focus on brain connectivity and organization across development. Recent work explores structural and functional neurodevelopmental trajectories, brain wiring economics, and the impact of environmental factors on neural development. Astle's research frequently employs advanced data science techniques to identify sub-populations of children with different cognitive or brain profiles, regardless of diagnosis, and to map non-linear relationships between brain organization and cognitive difficulties. His work has increasingly focused on transdiagnostic approaches to understanding developmental disorders and the application of computational models to developmental neuroscience. Astle actively supervises PhD students and has built a substantial research group that contributes to major projects including the Centre for Attention Learning and Memory (CALM) and Resilience in Education and Development (RED). His work has been supported by prestigious funding bodies including the Royal Society, the British Academy, the Medical Research Council, and the Economic and Social Research Council, as well as multiple charitable foundations. The 4D Lab, under Astle's leadership, utilizes state-of-the-art facilities at the University of Cambridge, including on-site magnetic resonance imaging and magnetoencephalography scanners. The lab contributes to building specialist cohorts such as CALM (800 children with cognitive difficulties plus 200 comparison children) and RED, which study children's development, resilience, and educational outcomes. Astle's team explores how growing up in adverse environments affects children's brains, behavior, and mental health, with the aim of identifying early markers of risk and resilience.
Yize Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health and an Associate Professor in the Department of Biomedical Informatics & Data Science at Yale University. She holds affiliations with multiple Yale research centers including the Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute, Yale Center for Brain and Mind Health, and Yale Computational Biology and Bioinformatics. Dr. Zhao's research focuses on developing statistical and AI methods to analyze large-scale complex biomedical data including medical imaging, genomics, and electronic health records. Her methodological expertise spans Bayesian statistics, feature selection, predictive modeling, data integration, missing data analysis, and network analysis. Her research interests span multiple biomedical domains with a strong focus on mental health, psychiatry, neurodegenerative diseases, and aging. Her recent work includes brain-to-behavior modeling, multi-layer biomedical networks, imaging genetics and genomics, and the integration of multi-modal biomedical data with real-world data. Dr. Zhao's work has resulted in numerous high-impact publications, with recent research focusing on Alzheimer's disease, brain network analysis, and advanced statistical methods for neuroimaging. Her publications show a strong trend toward integrating multi-modal data sources and developing sophisticated statistical approaches to address complex biomedical questions. Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS) COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS) YSPH Investigator Research Award Yale Alzheimer's Disease Research Center Research Scholar Award Elected member of the International Statistical Institute Dr. Zhao serves as an Associate Editor for Biometrics and is a standing member of the NIH Biodata Management and Analysis (BDMA) study section. Her research is supported by multiple NIH grants, highlighting the significance and impact of her work in biostatistics and biomedical data science.
Denise Head is Professor of Psychological & Brain Sciences and Associate Chair at Washington University in St. Louis, with an additional appointment as Associate Professor in Radiology. Her research integrates cognitive neuroscience and neuroimaging to study cognitive aging and Alzheimer's disease. PhD, University of Memphis MS, University of Memphis BS, University of New Orleans Her research focuses on age-related cognitive changes and their neural underpinnings. Key areas include spatial navigation deficits in aging, the role of lifestyle factors (exercise, sleep, stress) in brain aging, and interventions to support cognitive function in older adults. She uses virtual reality, mobile eye-tracking, and neuroimaging techniques such as fMRI and DTI. The recent publications highlight a consistent trajectory in cognitive neuroscience and aging research, with emphasis on neuroimaging biomarkers, structural brain changes, and cognitive performance in normal and pathological aging. Her work bridges psychology, neurology, and radiology, contributing to early detection and understanding of Alzheimer's disease. Scientific Awards: No awards listed in the provided text. Dr. Head advises graduate students and leads a research lab focused on cognitive aging, though specific student names are not listed. Her lab investigates mediators of brain aging and develops methods to support spatial navigation in older adults. While specific grants are not mentioned, her ongoing research and recent publications suggest active external funding. She leads a research team in the Department of Psychological & Brain Sciences, utilizing advanced neuroimaging and behavioral methods to study aging and dementia. The lab integrates real-world and virtual experimental designs to understand spatial cognition and brain health in older populations.
Professor Fernando Calamante is a Professor of Biomedical Engineering at The University of Sydney and Director of Sydney Imaging Core Research Facility. He leads the National Imaging Facility node and focuses on advanced MRI methodologies, particularly Diffusion and Perfusion MRI, to study brain connectivity and neurological disorders. His work includes developing the MRtrix software, widely used in diffusion MRI analysis. He holds extensive funding (~$50M) and has been recognized with awards like ISMRM Fellowship and NHMRC grants. His research spans super-resolution imaging, brain connectomics, and clinical applications in stroke and tumors. Education: BSc (Physics, Argentina), PhD (Magnetic Resonance Imaging, University College London). Career highlights include leadership roles at The Florey Institute and ISMRM presidency (2021-2022). Research interests include: Novel MRI methods for brain connectivity and super-resolution imaging Applications of Diffusion and Perfusion MRI in neurology Integration of structural and functional connectomics Key achievements: Over 200 publications, software innovations, and leadership in global MRI societies.
Essa Yacoub is a Professor in the Department of Radiology at the University of Minnesota, affiliated with the PhD Program in Medical Physics and the Center for Magnetic Resonance Research. His work focuses on advancing MRI and fMRI technologies, particularly at ultrahigh magnetic fields (e.g., 10.5 T), to achieve unprecedented spatial and temporal resolution in brain imaging. He leads projects in RF coil design, noise reduction algorithms, and developmental neuroimaging. Roles: Professor, Medical Physics Program Faculty Affiliations: Center for Magnetic Resonance Research, Department of Radiology Research emphasizes high-resolution fMRI applications, including layer-specific brain mapping, pediatric neurodevelopment studies (e.g., Baby Connectome Project), and translational tools like BIBSNet for infant brain segmentation. His innovations bridge hardware engineering (RF coils) and software (denoising pipelines) to tackle challenges in mesoscopic-scale imaging. Key contributions include optimizing imaging protocols at 7T/10.5T, developing NORDIC denoising for submillimeter data, and advancing understanding of brain networks in aging and neurological disorders. His work is foundational for large-scale initiatives like the Human Connectome Project and non-human primate neuroimaging collaborations. Grants and collaborations focus on translational imaging technologies, while educational contributions include training through the Medical Physics PhD Program. Ongoing efforts aim to refine ultra-high field MRI applications for clinical and basic neuroscience research.
