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John J. FoxeView profile

Adjunct Professor

• Neuroscience
• Cognitive Neuroscience
• Developmental Disorders
• +6 more

John J. Foxe is an Adjunct Professor in the Department of Pediatrics (Developmental Medicine) and the Dominick P. Purpura Department of Neuroscience at Albert Einstein College of Medicine. He serves as Director of Research of the Children's Evaluation and Rehabilitation Center (CERC). His research focuses on translational neuroscience, particularly in schizophrenia and autism spectrum disorders, with a strong emphasis on identifying endophenotypic markers and linking them to genetic factors. His lab employs advanced methodologies including neuroimaging, electrophysiology, and virtual reality to study sensory and cognitive functions. Education : Ph.D. from Albert Einstein College of Medicine (alma mater). Research Interests : Dr. Foxe’s work spans developmental neuropsychiatric disorders, auditory processing, and multisensory integration. His lab integrates structural and functional neuroimaging, EEG, and imaging genomics to explore neural mechanisms underlying perception and cognition. Key projects include studying perceptual and cognitive deficits in schizophrenia and autism, as well as the neural basis of speech processing and attention. Publications : Over 160+ publications, with recent work focusing on EEG biomarkers for schizophrenia, multisensory speech perception in children, and the neurophysiology of biological motion processing. His studies highlight deficits in sensory processing and cortical connectivity in neuropsychiatric disorders. Grants & Funding : Extensive NIH and NSF funding for translational research, including projects on auditory dysfunction in schizophrenia and developmental aspects of sensory integration. Labs & Teams : Leads a multidisciplinary lab at Einstein, collaborating with institutions such as Montefiore Medical Center. The lab emphasizes both basic science and clinical studies to develop novel diagnostic tools and interventions for neurodevelopmental disorders.

Marco Antonio Maximo PradoView profile

Researcher

• Neuroscience
• Neurodegenerative Diseases
• Cardiovascular Physiology
• +3 more

Marco Antonio Maximo Prado is a Researcher at the Robarts Research Institute, affiliated with The University of Western Ontario. His work focuses on neuronal communication mechanisms in neurological and cardiovascular disorders. Dr. Prado holds a Pharmacy degree, MSc in Biochemistry, PhD in Biochemistry, and a Cell Biology Diploma from UFMG, McGill, and Duke Universities. His research explores cholinergic synapses in Alzheimer’s disease, prion diseases, and cardiac dysfunction, using molecular, cellular, and behavioral approaches. Notable awards include the John Simon Guggenheim Fellowship and Senior Research Fellow from Brazil’s National Research Council. His lab investigates novel pharmacological targets for neurodegenerative and cardiovascular diseases, emphasizing transmissible spongiform encephalopathies and cholinergic modulation. Recent projects include studies on exercise-induced cholinergic effects on emphysema and the role of prion proteins in Alzheimer’s pathology. Education: Pharmacy (UFMG); MSc Biochemistry (UFMG); PhD Biochemistry (McGill University); Diploma Cell Biology (Duke University). Training at UFMG, McGill, and Duke. Awards: Guggenheim Fellowship (2005), IBRO Fellow (2003), and others. Research interests span neurodegenerative diseases, cardiovascular physiology, and translational medicine. Publications include work on cholinergic signaling in the heart, cholinergic deficiency in renal fibrosis, and antinociceptive properties of spider venom. His lab collaborates across disciplines, integrating pharmacology, genetics, and behavioral studies. Current efforts focus on developing therapies targeting cholinergic pathways and prion protein mechanisms.

Jhenny F. GalanView profile

Associate Professor

• Computational Chemistry
• Biophysical Chemistry
• Molecular Dynamics Simulations
• +2 more

Dr. Jhenny F. Galan is an Associate Professor in the Division of Foundational Sciences at Texas A&M University, specializing in Chemistry. Her academic journey includes a PhD in Physical and Computational Chemistry from the University of Connecticut and a BS in Chemistry from the University of the Philippines. Her research focuses on computational approaches to biological systems, including molecular dynamics simulations of proteins, forcefield validation, membrane translocation studies of foldamers, and conformational analysis of aromatic oligoamides. Key interests span computational chemistry, biophysical chemistry, and theoretical methods applied to macromolecular systems. Dr. Galan teaches undergraduate courses including Fundamentals of Chemistry, Physical Chemistry for Engineers, Physical Chemistry Laboratory, and Biochemistry. She actively presents her work at national conferences including ACS meetings and Gordon Research Conferences.

Lei (Stanley) QiView profile

Associate Professor

• CRISPR technology
• Genome engineering
• Epigenetics
• +3 more

Dr. Lei (Stanley) Qi is an Associate Professor in the Department of Bioengineering at Stanford University, with affiliations as an Institute Scholar at Sarafan ChEM-H and an Investigator at the Chan Zuckerberg Biohub. His work focuses on CRISPR technologies for genome and epigenome engineering. B.S., Tsinghua University, Math and Physics (2005) M.A., University of California, Berkeley, Physics (2007) Ph.D., University of California, Berkeley/UCSF, Bioengineering (2012) Dr. Qi pioneered CRISPR interference (CRISPRi) and activation (CRISPRa) through the development of nuclease-deactivated Cas9 (dCas9) systems. His lab has advanced technologies like MEGA (multiplexed transcriptome engineering), CRISPR-GO (3D genome manipulation), and Live-FISH for real-time enhancer-promoter interaction imaging. Current research explores Therapeutic epigenome editing for immune modulation, brain disorders, and aging reversal Functional spatial transcriptomics to decode RNA organization in disease Fundamental genome biology using live-cell imaging and AI to study 3D genome regulation Recent publications highlight his group’s innovations in compact CRISPR systems (CasMINI), spatial RNA control in neurons, and therapeutic applications for neuromuscular diseases and cancer. His work bridges synthetic biology with medicine, emphasizing clinical translation and equitable biotechnology education via frugal CRISPR kits. Labs & Collaborations : The Qi Lab collaborates with UCSF, Chan Zuckerberg Biohub, and Sarafan ChEM-H to develop clinical CRISPR tools. They utilize AI and high-throughput methods to optimize gene regulation and study epigenetic principles.

John MollonView profile

Professor

• Visual Neuroscience
• Color Vision
• Neural Circuitry
• +5 more

Professor John Mollon is the Professor of Visual Neuroscience at the University of Cambridge and a Fellow and Lecturer in Psychology at Gonville and Caius College. His work focuses on color vision, neural circuitry, and visual perception, with a particular emphasis on primate evolution and optics history. He has contributed significantly to understanding color deficiencies, retinal genetics, and the neural mechanisms underlying visual processing. Affiliations: Department of Psychology (University of Cambridge), Gonville and Caius College Research Interests: Color vision evolution, psychophysics of color discrimination, genetic basis of visual anomalies, and clinical applications of color perception research. His research spans over five decades, including seminal studies on primate color vision evolution, the genetic basis of color blindness, and the development of diagnostic tools like the Cambridge Colour Test. Recent work explores neural coding in cortical networks and the impact of genetic variation on visual performance. Key contributions include analyzing the spectral sensitivity of primate retinas, investigating tetrachromacy, and linking genetic markers to visual disorders. His articles frequently bridge evolutionary biology, clinical ophthalmology, and cognitive neuroscience.

Mark BearView profile

Professor

• Neuroscience
• Synaptic Plasticity
• Visual Cortex Development
• +5 more

Dr. Mark Bear is the Picower Professor of Neuroscience at MIT's Department of Brain and Cognitive Sciences and a principal investigator at the Picower Institute for Learning and Memory. He previously served as Director of the Picower Institute (2007–2009) and was on the faculty of Brown University School of Medicine for 17 years before joining MIT in 2003. His research focuses on synaptic plasticity mechanisms underlying learning, memory, and neurodevelopmental disorders like fragile X syndrome and autism. Key contributions include discovering the mGluR theory of fragile X syndrome, which revolutionized treatment approaches, and pioneering methods to reverse amblyopia in animal models. Education: B.S. from Duke University, Ph.D. in neurobiology from Brown University, followed by postdoctoral training at the Max Planck Institute for Brain Research (Frankfurt, Germany) and Brown University under Wolf Singer and Leon Cooper. Research interests encompass visual cortex development, hippocampal plasticity, and translational studies for neurodevelopmental disorders. His lab employs electrophysiology, molecular biology, and behavioral assays to study synaptic modifications. Recent work explores non-ionotropic NMDA receptor signaling, retinal inactivation therapies for amblyopia, and electrophysiological biomarkers for fragile X syndrome. Publications highlight groundbreaking discoveries in synaptic plasticity mechanisms, amblyopia recovery pathways, and therapeutic strategies for autism spectrum disorders. His work bridges basic neuroscience with clinical applications, particularly in fragile X syndrome and amblyopia treatment.

Ming WangView profile

Professor

• Biostatistics
• Data Integration
• Causal Inference
• +12 more

Ming Wang, PhD is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine. She also serves as Director of the Masters Program in Biostatistics . Her research focuses on statistical method development for biomedical and human health problems, including causal inference, longitudinal data analysis, and computational methods for genomic and imaging data. She collaborates on studies involving cancer, cardiovascular disease, kidney disease, neurodegenerative disorders, and child abuse. Education : PhD in Biostatistics, Emory University (2013) MSc in Biostatistics, University of Louisville (2008) BSc in Applied Mathematics, Peking University (2006) Research Interests : Methodological: Bayesian statistics, missing data, spatial statistics, risk prediction Clinical: Prostate cancer, kidney disease, cardiovascular outcomes, neurodegeneration Key Awards : Elected Member, International Statistical Institute (2021) Dean's Excellence in Teaching Award (2019) NISS/ASA Junior Faculty Presentation Award (2016) Professional Roles : Associate Editor: Biometrics , Statistics in Medicine , Journal of Biopharmaceutical Statistics Statistical Editor: Journal of the American Society of Nephrology Her work bridges statistical innovation with clinical impact, particularly in leveraging large-scale health data for precision medicine and population health strategies.

Marin KobilarovView profile

Associate Professor

• Intelligent Robotics
• Autonomous Systems
• Mechanical Control Systems
• +3 more

Marin Kobilarov is an Associate Professor in the Department of Mechanical Engineering at Johns Hopkins University’s Whiting School of Engineering. He leads the Laboratory for Autonomous Systems, Control, and Optimization, a subset of the Laboratory for Computational Sensing and Robotics. His research focuses on intelligent robotic vehicles capable of autonomous navigation and task execution in complex environments, with applications in aerial vehicles, medical robotics, and space systems. Dr. Kobilarov holds a BS in Computer Science and Applied Mathematics from Trinity College (2003) and a PhD in Computer Science from the University of Southern California (2008). Before joining Johns Hopkins in 2012, he completed postdoctoral fellowships at the California Institute of Technology and the United Technologies Research Center, specializing in control systems and dynamical systems. His research interests span robotics, autonomous systems, and medical applications, including surgical robotics for ophthalmology and microsurgery. Notable projects include developing perception-aware navigation frameworks, UAV pick-and-place systems, and autonomous retinal surgery tools using imitation learning and real-time imaging. His publications emphasize trajectory optimization, multi-agent coordination, and safety-critical control, with recent work addressing challenges in occluded environment navigation and uncertainty-aware planning for heterogeneous robot teams. Awards include prestigious postdoctoral fellowships from the Keck Institute for Space Studies and United Technologies Research Center. Dr. Kobilarov’s lab collaborates across disciplines to advance robotics in dynamic environments, with ongoing work on surgical automation, autonomous aerial systems, and robust control algorithms. His research bridges theoretical control methods with practical engineering solutions for real-world robotic applications.

Patrick WalshView profile

Associate Professor

• Eighteenth-Century History
• Irish History
• Colonial History
• +4 more

Dr. Patrick Walsh is an Associate Professor in Eighteenth-Century Irish History at Trinity College Dublin's Department of History. His research focuses on Ireland's colonial and imperial history, with a comparative perspective emphasizing economic history. He co-directs the Trinity Colonial Legacies project, a public history initiative collaborating with institutions like the Office of Public Works and the Royal Dublin Society. Dr. Walsh teaches undergraduate and postgraduate modules on Irish, Atlantic, economic, and financial history, including the history of capitalism. His current projects include a monograph on state formation in eighteenth-century Ireland and an exploration of financial legacies of Irish property ownership. He actively engages with policymakers and heritage professionals to bridge academic and public history.

Marianne MaertensView profile

Professor

• Computational Psychology
• Visual Perception
• Cognitive Neuroscience
• +3 more

Prof. Marianne Maertens is a Professor in Computational Psychology at Technische Universität Berlin's Institute of Computer Engineering and Microelectronics. Her research focuses on understanding how the human brain creates meaningful perceptual categories from sensory input. She holds a Ph.D. in Psychology from the University of Leipzig and a Diploma in Psychology from Martin-Luther-Universität Halle-Wittenberg. Professional Experience: Since 2019: Professor, TU Berlin 2011–2018: Junior Research Group Leader (DFG Emmy Noether & Heisenberg Programs) 2008–2011: Postdoctoral Researcher under Prof. Felix Wichmann, TU Berlin 2006–2008: Postdoctoral Researcher under Prof. Stefan Pollmann, Otto-von-Guericke Universität Magdeburg 2005–2006: Visiting Scholar at NYU’s Center for Neural Science, Lab of Prof. Robert Shapley Research Interests: Her work bridges psychology and neuroscience, investigating mechanisms of visual perception, sensory processing, and neural computations. She employs computational models to explore how the brain translates retinal stimuli into coherent perceptual experiences. Lab & Contact: Located in Room MAR 5.018, TU Berlin. Office hours by appointment. Administrative support provided by Bianca del Mestre (MAR 5.019).

Valentina CiprianiView profile

Senior Lecturer

• Genetic Epidemiology
• Statistical Genomics
• Rare Mendelian Disorders
• +6 more

Dr. Valentina Cipriani is a Senior Lecturer in Statistical Genomics at Queen Mary University of London (QMUL), affiliated with the William Harvey Research Institute (WHRI) in the Faculty of Medicine and Dentistry. She holds a PhD in Public Health and Education from the University of Pavia, Italy, with visiting research at Imperial College London. Her work focuses on computational methods for genotyping and sequencing data to uncover genetic determinants of rare Mendelian and common complex diseases. She leads initiatives in rare disease diagnostics, AMD genetics, and precision medicine, contributing to large consortia like the International AMD Genomics Consortium (IAMDGC) and the 100,000 Genomes Project. Education: PhD in Public Health and Education, University of Pavia (Italy) Visiting PhD at Imperial College London under Prof. David Balding MSc in Statistics, Sapienza University of Rome (Italy) Research interests include: Statistical analysis of genetic data for rare and common diseases Computational tools for variant prioritization (e.g., Exomiser) Genetic basis of AMD and complement-mediated diseases Therapeutic development for geographic atrophy Large-scale genomic studies and clinical translation Key research trends in her articles focus on: Improving diagnostic yield for rare diseases via gene burden analysis Complement system dysregulation in AMD pathogenesis Pharmacogenetic insights for oncology therapies Integration of phenotype-driven approaches in variant prioritization Grants and collaborations include: £528k Barts Charity grant for rare disease prevalence analysis NIHR/BRC funding for genomic medicine Partnerships with UCL, Moorfields Eye Hospital, and international institutions Labs/Teams: Co-founder of Complement Therapeutics (gene therapy for AMD), active in the IAMDGC and Monarch Initiative.

Caroline BrennanView profile

Professor

• Molecular Genetics
• Developmental Biology
• Neurobiology
• +3 more

Prof Caroline Brennan is a Professor of Molecular Genetics and Interim Head of the School of Biological and Behavioural Sciences at Queen Mary University of London. Her research focuses on using zebrafish as a model to study developmental and behavioral processes underlying psychiatric and metabolic disorders. Key interests include neurobiology, comparative cognition, addiction, and the genetic basis of behavior. She leads a multidisciplinary lab collaborating with human geneticists and evolutionary biologists to explore disease mechanisms and therapeutic targets. Her work spans translational research, with grants from NIH, EU Horizon 2020, and the Leverhulme Trust. Notable contributions include studies on AIP deficiency in zebrafish, numeracy in fish, and the genetic basis of nicotine preference. She oversees a team of PhD students and postdocs, mentoring research in areas like stress responses, neurodegeneration, and environmental impacts on mental health. Recent achievements include participation in the Royal Society Summer Science Exhibition and leadership in international collaborations. Awards include Fellow of the Royal Society and membership in the Royal Society Industry Fellows' College.

Yun LiView profile

Professor

• Statistical Genetics
• Multi-omics Dissection
• Genetic Dissection of Complex Diseases
• +8 more

Dr. Yun Li is a Professor in the Department of Genetics and Department of Biostatistics at the University of North Carolina at Chapel Hill (UNC-Chapel Hill), affiliated with the UNC School of Medicine. He also holds an adjunct position as an Associate Professor in Applied Physical Sciences. His research focuses on developing statistical methods for genetic and genomic studies, including genotype imputation (e.g., MaCH software), multi-omics integration, and analysis of complex diseases such as metabolic, autoimmune, cardiovascular, and neuropsychiatric disorders. He leads the Li Lab, which has contributed to projects like the 1000 Genomes Project, TOPMed, and BACPAC consortium. Dr. Li’s work emphasizes methodological advancements for low-coverage sequencing, epigenetic studies, single-cell RNA-seq, and chromatin organization analysis. Education: Ph.D. in Biostatistics from the University of Michigan (2009). Leadership includes roles in the NIH PRIMED consortium and the 4DN Predictive Modeling Working Group. The lab has developed tools such as HUGIn for Hi-C data exploration and CUE for DNA methylation imputation. Collaborations span multi-omic studies, precision medicine, and population genetics across diverse populations. Research interests span statistical genetics, genomic data integration, and translational applications. The lab actively participates in consortia addressing genetic dissection of complex traits, leveraging single-cell and spatial transcriptomics, and chromatin 3D architecture.

Usman AlimView profile

Associate Professor

• Computer Graphics
• Visualization Techniques
• Volume Rendering
• +6 more

Usman Alim is an Associate Professor in the Department of Computer Science at the University of Calgary, and Director of the Data Science Program. He holds a dual Bachelor's in Mathematics and Physics from the University of Rochester (2001), an M.Sc. in Computer Science from Rochester Institute of Technology (2007), and a Ph.D. in Computer Science from Simon Fraser University (2012). His research focuses on global illumination, physically-based modeling, and signal processing applications in computer graphics and visualization. He is particularly noted for innovations in volume visualization, VR interfaces, and haptic systems. Key research areas include: Interactive visualization systems for multivariate data Uncertainty visualization in geological and medical datasets Efficient rendering techniques for large-scale datasets Low-code frameworks for data workflow automation Notable achievements include winning the 2019 IEEE SciVis Contest's Best Report Cover and multiple awards in Compute Canada's Visualize This contest. His work bridges theoretical foundations with practical applications in fields like environmental science, healthcare, and urban analytics. Current initiatives include advancing haptic interaction design, developing cloud-deployable medical imaging pipelines, and exploring AI-driven solutions for oil sands analysis. He teaches graduate courses like DATA 601 (Data Visualization) and special topics in computer science, contributing to both academic research and applied data science education.

Kevin DrewView profile

Assistant Professor

• Molecular Interactions
• Proteomics
• Computational Biology
• +4 more

Kevin Drew is an Assistant Professor in the Department of Biological Sciences at the University of Illinois Chicago's College of Liberal Arts and Sciences. His research focuses on developing computational and biochemical tools to systematically characterize molecular interactions in cells, with applications in understanding disease mechanisms and therapeutic development. Education includes a Ph.D. in Biology – Molecular Biophysics from New York University School of Medicine (2014), M.S. in Computer Science from University of Chicago (2005), and B.S. in Computer Science from University of Iowa (2003). Research interests span molecular interactions, proteomics, computational biology, structural biology, machine learning applications in biology, macromolecular assemblies, and drug design. The Drew Lab employs biochemical, computational, and proteomic approaches to identify cellular macromolecular assemblies, characterize their structural states, determine 3D structures, and develop interaction modulators. Publications demonstrate consistent focus on proteomics, computational modeling of protein complexes, and biomolecular interaction analysis. Recent work emphasizes high-throughput methods for complex identification, evolutionary conservation of interactions, and therapeutic targeting of protein interfaces. No awards or student advising information was available. Lab activities at the Drew Lab include systematic characterization of macromolecular assemblies using interdisciplinary approaches.