Dr. Katrin Vogt is a researcher at the University of Konstanz, specializing in neuroethology and sensory systems. Her work focuses on understanding recurrent neural circuits governing state-dependent behavior, particularly in olfactory systems of Drosophila larvae. She leads a subproject investigating hunger-dependent serotonergic modulation in the antennal lobe, collaborating with a doctoral student. Her research bridges vertebrate and invertebrate models to identify conserved network principles across species. Dr. Vogt is part of a DFG-funded interdisciplinary team examining recurrent circuits' roles in flexible behavioral responses to environmental changes. Her research interests include neural circuitry modulation, sensory integration, and behavioral plasticity. Key projects involve analyzing how sensory inputs are modulated by internal states like hunger, and how recurrent connections enable adaptive responses. She has contributed to studies on visual and olfactory memory formation, multisensory integration, and navigational strategies in Drosophila. Publications highlight work on dopamine signaling in taste punishment, social behavior in larvae, and cross-species odor coding principles. Her findings aim to uncover fundamental mechanisms underlying sensory-driven behavior and neural plasticity in both vertebrates and invertebrates.
Aprajita Mohanty, Ph.D., is an Associate Professor of Clinical Psychology at Stony Brook University's Department of Psychology. She holds a Ph.D. from the University of Illinois-Urbana Champaign (2007). Her research focuses on the interplay between emotion, perception, and cognitive control, particularly in anxiety and psychotic disorders. Using fMRI, ERP, and computational modeling, her lab investigates how the brain anticipates emotional stimuli and how these processes contribute to psychopathology. Research Themes: Emotion-cognition interactions in anxiety and psychosis Threat perception and decision-making Predictive processing and neural markers of psychotic disorders Role of contextual learning in threat detection Key Contributions: Elucidated how anticipatory brain activity enhances threat perception in anxiety Identified transdiagnostic neural markers of psychotic disorders (e.g., mismatch negativity) Explored olfactory perception and odor identification in clinical populations Grants & Collaborations: Collaborates with Dr. Roman Kotov (Psychiatry) on emotion-cognition interactions in psychosis. Actively reviews graduate student applications for the 2024-2025 academic year. Labs/Teams: Directs the Emotion, Perception, and Cognition Lab at Stony Brook, integrating cognitive, clinical, and neuroscience methodologies.
Dr. Andrew Lin is a Senior Lecturer and School Director of One University at the University of Sheffield's School of Biosciences. He holds a PhD from the University of Cambridge and a BA in Biology from Harvard University. His career includes roles as a Lecturer (2019-2022), Vice-Chancellor’s Fellow (2015-2019), and Postdoctoral Fellow at the University of Oxford (2009-2015). Research focuses on how the brain encodes sensory information for memory formation, using Drosophila's olfactory system as a model. Key areas include sparse coding in Kenyon cells, synaptic inhibition/excitation balance, and neural circuit dysfunction links to epilepsy. Teaching includes modules like BMS11004 Introduction to Neuroscience and BMS248 Neural Circuits, Behaviour and Memory. He has secured grants from the European Research Council, BBSRC, and Wellcome Trust. Professional memberships include the FENS-Kavli Network and BBSRC Pool of Experts. Lab research employs techniques like in vivo two-photon imaging, electrophysiology, and genetic manipulation. PhD opportunities are available in neural circuitry and sensory processing.
Dr. Emily Gibson is an Associate Professor in the Department of Bioengineering at the University of Colorado School of Medicine. She holds a PhD from the University of Colorado Boulder (2004) and a BS from the Colorado School of Mines (1997). Her multidisciplinary research focuses on developing advanced optical technologies for neuroscience applications. Her primary research interests include: Development of implantable miniature microscopes for two-photon brain imaging in freely behaving animals Superresolution STED microscopy for subcellular imaging of protein dynamics Optical interfaces for neural modulation and sensing in central and peripheral nervous systems Applications in brain mapping, neural circuit analysis, and bioelectronic medicine Dr. Gibson's recent publications demonstrate a strong focus on neurophotonic tool development, including miniature microscopes, fiber-optic imaging systems, and superresolution techniques. Her work consistently applies these technologies to study neural coding, learning mechanisms, and neurodegenerative processes. She leads the Biophotonics Lab at CU Anschutz, which actively develops open-source neurophotonic tools. Current projects include BRAIN Initiative-funded work on voltage imaging and NSF-supported research on odor navigation. Her lab maintains active collaborations with neuroscientists and clinicians to translate optical technologies into neuroscience research and clinical applications.
Shaul Druckmann is an Associate Professor at Stanford University in the departments of Neurobiology, Psychiatry and Behavioral Sciences, and by courtesy in Electrical Engineering. He is affiliated with Stanford Bio-X and the Wu Tsai Neurosciences Institute. Key Research Areas: Neural circuit dynamics, computational neuroscience, sensory-motor integration, and brain-wide information representation. Academic Roles: Advisor, mentor, and instructor for graduate and doctoral programs at Stanford. His work combines theoretical modeling, in vivo imaging , and genetic dissection to uncover how neural circuits process information and generate behavior. Recent trends in his research emphasize cross-species comparative analysis (Drosophila, rodents, C. elegans) and interdisciplinary applications in neuroprosthetics. 2023-2024 Awards: Award for Excellence in Graduate Teaching, Stanford University McKnight Scholar, McKnight Foundation Sloan Research Fellow, Sloan Foundation Advising & Teaching: Dr. Druckmann mentors doctoral students across Neurobiology, Psychiatry, and Applied Physics. He teaches foundational courses like Introduction to Mathematical Tools in Neuroscience and Neuroscience Computational Core , while supervising independent studies in bioengineering and physics. Laboratory: The Druckmann Lab at Stanford employs advanced imaging , computational modeling , and connectome analysis to bridge theoretical neuroscience with applications in medical devices and cognitive frameworks.
Dr. Sophie Forster is an Associate Professor and Reader in Cognitive Neuroscience at the University of Sussex's School of Psychology, where she leads the Sussex Attention Lab. Her research focuses on attentional mechanisms, particularly how individuals become distracted by external stimuli or internal thoughts. Key interests include attentional failure, clinical attention disorders (e.g., ADHD), and the interplay between perceptual load and cognitive control. She has held grants from the ESRC, BIAL Foundation, and AHRC, investigating topics like mind-wandering and perceptual decoupling. Teaching roles include courses on attention, clinical cognition, and cognitive psychology. Professional activities include editorial roles at Journal of Experimental Psychology: Human Perception and Performance and ESRC peer review. Education: PhD from University College London (UCL), post-doctoral work at UC Berkeley, and an ESRC fellowship at UCL before joining Sussex in 2013. Research labs and collaborations include the Sussex Attention Lab and cross-disciplinary projects on autism and neurodiversity. Key research themes: 1) Attentional capture and distraction, 2) Mind-wandering and its cognitive consequences, 3) Application of perceptual load theory to clinical contexts (e.g., eating behavior, addiction). Recent grants include studying internal distraction and attentional decoupling mechanisms. Her work bridges cognitive neuroscience, experimental psychology, and clinical applications. Grants (selected): ESRC grant on 'Watching the mind travel' (2022–2024) BIAL Foundation grant on perceptual decoupling (2023–2024) AHRC project on autism and art engagement (2023–2024) Teaching focuses on third-year 'Attention: Distraction, daydreaming and diversity' and second-year 'Cognitive Psychology'. Office hours include drop-in sessions via bookable appointments .
Leslie M. Kay is a Professor of Psychology and Deputy Dean for Research at The University of Chicago. Her research focuses on olfactory neurophysiology, oscillatory dynamics, and the interplay between context and cognition in sensory processing. Education: BA in Liberal Arts from St. John's College, Santa Fe; PhD in Biophysics from UC Berkeley At the Institute for Mind & Biology, her lab investigates how behavioral context affects olfactory and limbic system neurophysiology through psychophysical and electrophysiological approaches. Key research areas include: Roles of respiratory rhythms in neural synchronization Theta/gamma oscillation mechanisms Odor perception across sensory pathways Neurocognitive strategies in odor processing
Paul Miller is a Professor of Biology at Brandeis University and a member of the Volen National Center for Complex Systems. His research focuses on computational neuroscience, integrating dynamical systems theory with experimental data to understand neural mechanisms underlying decision-making, memory, and sensory processing. He holds a Ph.D. from the University of Bristol (UK) and a B.A. from Cambridge University. Before joining Brandeis in 2000, he was at Georgetown University and conducted postdoctoral work in theoretical physics at Oak Ridge National Laboratory. Education: B.A., Cambridge University (1991) Ph.D., University of Bristol (1994) Research Interests: Computational Neuroscience emphasizes modeling neural circuits for short-term/long-term memory, decision-making processes, and the dynamics of neural ensemble activity. His work bridges theoretical approaches (e.g., hidden Markov modeling, spiking neuron networks) with experimental data from cortical and hippocampal systems. He explores how quasistable attractor states enable robust computation and how homeostatic mechanisms stabilize neural activity. Notable Contributions: Developed models explaining how integral feedback control enables robust sequential decision-making, elucidated synaptic mechanisms for spatiotemporal discrimination, and analyzed the role of calcium/calmodulin-dependent protein kinase II (CaMKII) in long-term memory stability. His textbook An Introductory Course in Computational Neuroscience (MIT Press) is widely used in graduate programs. Labs/Teams: Leads the Computational Neuroscience Lab at Brandeis, collaborating with experimentalists to validate theoretical models. Active in interdisciplinary projects involving neurophysiology, systems biology, and mathematical neuroscience.
Jay Gottfried is the Arthur H. Rubenstein University Professor at the University of Pennsylvania's Perelman School of Medicine. His research focuses on human olfactory neuroscience, investigating how odor perception is processed in limbic circuits related to emotion, learning, and memory. He employs advanced techniques like functional MRI (fMRI) and intracranial EEG to study olfactory systems, with recent work exploring olfactory navigation using grid-like neural representations and interactions between sensory cortices. Education: A.B. in Molecular Biology from Princeton University; M.D. and Ph.D. in Physiology and Neuroscience from NYU School of Medicine. Postdoctoral training in olfactory neuroscience at University College London. Research Interests include odor coding, oscillations in the piriform cortex, and translational studies linking olfactory dysfunction to neurodegenerative diseases. Notable projects involve odor categorization, fear learning, and sleep-dependent memory consolidation. His lab bridges human and rodent studies to elucidate olfactory mechanisms. Key findings include temporal segregation of nostril odor signals, grid-cell-like representations in olfactory navigation, and the role of piriform cortex in integrating sensory information. He collaborates on developing high-resolution imaging and EEG techniques to map olfactory circuits.
Dr. Enrique Blair is an Associate Professor in the Department of Electrical and Computer Engineering at Baylor University, where he has served since 2015, advancing to his current rank in 2021. His academic journey includes prior roles as a Military Instructor at the U.S. Naval Academy and service in the U.S. Navy submarine force. He is actively engaged in research, teaching, and mentoring within the College of Engineering. His research focuses on the theoretical and computational aspects of quantum engineering, particularly in quantum-dot cellular automata (QCA), open quantum systems, and quantum information sciences. He explores molecular computing paradigms, quantum decoherence, and the quantum mechanical basis of olfaction, aiming to develop ultra-dense, low-power nanoelectronic devices and novel quantum technologies. His interdisciplinary work bridges electrical engineering, physics, chemistry, and materials science. The recent articles highlight a strong trend in molecular QCA design, quantum simulation for NISQ devices, and the application of ab initio methods to understand counterion effects and molecular stability. His research increasingly integrates machine learning for material discovery and emphasizes robustness in quantum circuits against environmental noise and external fields. The publications reflect a consistent focus on foundational quantum phenomena with practical applications in computing, sensing, and security. Research Grant, Office of Naval Research, Code 312 Nanoscale Computing Devices and Systems (May 2020 - May 2023) Summer Sabbatical, Baylor University (Summer 2019) Senior Member, IEEE (2019) Outstanding Faculty Award (untenured, tenure-track faculty), Baylor University (2018) Proposal Development Award, Office of the Vice Provost for Research, Baylor University (2017) Rising Star Program, Baylor University (2017-2018) Undergraduate Research and Scholarly Achievement Award, Office of the Vice Provost for Research, Baylor University (2017-2018) Rising Star Program, Baylor University (2016-2017) Graduate Research Fellowship Program, National Science Foundation (2010-2015) National Defense Science and Engineering Graduate Fellowship, American Society for Engineering Education (2010-2013) Dr. Blair has advised multiple Ph.D. and Master’s students, including Colin Burdine, Nischal Gautam, and Nishat Liza, and has mentored numerous undergraduate researchers. His research is supported by competitive grants, particularly from the Office of Naval Research, reflecting the strategic importance of his work in nanoscale computing. He integrates teaching and research, offering courses such as Quantum Mechanics for Engineers and Introduction to Quantum Computing, and promotes scholarly productivity through tools like Emacs Org Mode and LyX. He leads an active research team focused on molecular QCA and quantum information, with current members including Ph.D. students and undergraduates. The team conducts simulations, theoretical modeling, and design of quantum devices, contributing to advancements in nanoelectronics and quantum computing. Collaborations with experts in chemistry, physics, and computer science further extend the impact of the research.
Prof. Alexandre Pouget is a leading Professor at the University of Geneva , affiliated with the Faculty of Medicine and Department of Basic Neuroscience . His research focuses on uncovering general principles of representation and computation in neural circuits , particularly how the brain handles uncertainty through probabilistic inference in domains like Decision Making Multisensory Integration Number Representation Visual Processing Perceptual Learning His work applies Bayesian inference to neural coding, with notable contributions to understanding odor demixing and confidence vs. certainty in cognitive tasks. He leads a dynamic research group at CMU (C08.1538.A) with postdocs and graduate students, and his collaborations span institutions like University College London Simons Foundation Human Frontiers Science Programme Swiss National Science Foundation While no specific scientific awards are listed, his publications in Nature Neuroscience and Nature highlight his impact. His lab emphasizes interdisciplinary approaches combining computational modeling , neurophysiology , and behavioral analysis .
Gaia Tavoni, PhD, is an Assistant Professor in the Department of Neuroscience at Washington University in St. Louis School of Medicine, where she leads the Tavoni Lab. Her research investigates fundamental principles of brain function through theoretical and computational approaches, focusing on neural coding, sensory processing, decision-making, and memory optimization. Education: BS in Physical Engineering, Polytechnic of Turin (2010) International MS in Physics of Complex Systems (2012) PhD in Physics, École Normale Supérieure, Paris (2015) Post-doc in Theoretical Neuroscience, University of Pennsylvania (2020) Research Interests: Dr. Tavoni develops unified frameworks connecting computational, algorithmic, and implementational perspectives in neuroscience. Key areas include: multimodal sensory coding principles, neuroplasticity mechanisms, economic decision circuits, Bayesian inference theories, and memory optimization in heterogeneous networks. Her lab employs biophysical models, information theory, and statistical mechanics to study how neural networks optimize behavior. Publication Trends: Recent work demonstrates strong emphasis on normative theories of neural computation, with publications spanning sensory integration, memory capacity optimization, and adaptive inference. Articles frequently integrate mathematical modeling with experimental neuroscience to explain cortical feedback mechanisms, decision circuits, and cognitive trade-offs. Awards: Sloan Fellowship (2024) PRX Life Reviewer Excellence Award (2024) Swartz Foundation Fellowship (2017) Computational Neuroscience Postdoctoral Fellowship (2015) Lab & Team: Directs a team including postdoctoral researchers (Mahsa Khoshkhou, Ryan McGee, Kaining Zhang), graduate student Eleonora Bano, and research assistant Timothy Crimmins. The lab focuses on neural circuit optimization and collaborates with groups like the Padoa-Schioppa Lab for economic decision research.
David C. Sheridan is an accomplished Associate Professor and Department Chair within the Department of Biology & Earth Science at Otterbein University. With a strong academic foundation in physiology and psychology, he teaches a range of courses in human and animal anatomy & physiology. His professional profile reflects a deep commitment to both education and research in the physiological sciences. Dr. Sheridan's educational journey is marked by advanced degrees from prestigious institutions. He earned his Ph.D. and M.S. in Physiology from The University of Wisconsin, complemented by dual Bachelor of Arts degrees in Psychology and History from The University of Minnesota. This diverse academic background informs his interdisciplinary approach to physiology. His research program is centered on integrative physiology, with two primary thrusts: investigating reaction times across sensory modalities and examining physiological adaptations during exercise. These interests are deeply rooted in neuroscience, particularly sensory systems, and extend to molecular mechanisms of muscle function as evidenced by his publication record. Dr. Sheridan employs a variety of experimental techniques to unravel complex physiological processes. A review of his scholarly output indicates a sustained focus on the molecular underpinnings of excitation-contraction coupling in skeletal muscle. His work frequently appears in high-impact journals such as Biophysical Journal and Proceedings of the National Academy of Sciences, demonstrating expertise in calcium channel function, protein topology, and neural circuit dynamics. The interdisciplinary nature of his research bridges biophysics, neuroscience, and exercise physiology. In his role as an educator and department chair, Dr. Sheridan mentors undergraduate students in research projects, fostering the next generation of scientists. While specific grant details are not publicly enumerated, his publication history suggests successful research funding. His leadership extends to shaping the academic direction of the Biology & Earth Science department at Otterbein University.
Professor Geraldine Wright is the Hope Professor of Entomology at the University of Oxford's Department of Biology. She holds roles as Section Director of Graduate Studies (Admissions & Progression) and Professorial Fellow at Jesus College. Her research focuses on insect sensory systems, nutritional regulation, and pollinator health, with emphasis on honeybees and bumblebees. Key themes include chemical sensation mechanisms, learning processes linking sensory cues to food, nutrient intake regulation, and plant-insect interactions. Research spans four levels: chemical sensation, learning, feeding regulation, and ecological impacts of plant compounds. Explores how pesticides and toxins affect pollinator behavior and physiology. Develops methods to deliver essential nutrients to invertebrates via engineered microorganisms. Her work integrates neurophysiological, behavioral, and ecological approaches to address threats to pollinators, including pesticide exposure and nutritional stress. Recent studies highlight the role of sterols in bee health and the design of biopesticides safe for pollinators. Publications emphasize the interplay between diet, neurobiology, and environmental challenges faced by insects. Her lab's findings inform strategies to mitigate declines in pollinator populations through targeted nutritional interventions and toxin mitigation.
Gill Bejerano is a Professor at Stanford University with joint appointments in Developmental Biology, Computer Science, Pediatrics (Genetics), and Biomedical Data Science. His career spans mathematics, computer science, and genomics, with key contributions to understanding conserved non-coding elements, RNA splicing, and genomic disease mechanisms. Ph.D. in Computer Science (Machine Learning in Biology), Hebrew University (2004) B.Sc. Mathematics, Physics, Computer Science (summa cum laude), Hebrew University (1997) His research focuses on genomic evolution , non-coding DNA , RNA splicing , and genomic medicine . He pioneered methods like GREAT for functional enrichment analysis and tools for secure genomic data sharing. Recent publications highlight work on echolocating mammals , RNA splicing prediction , clinical variant interpretation , and genomic privacy . Collaborations span computational biologists, clinicians, and engineers. Scientific Awards : Mallinckrodt Fellowship Sloan Research Fellowship Human Frontiers Fellowship Best Paper & Tomorrow's PI Awards Okawa Foundation Award David and Lucile Packard Fellowship Microsoft & Sony Scholar Awards He advises interdisciplinary trainees and consults for start-ups/Fortune 500 companies, bridging genomics , machine learning , and clinical diagnostics .
