Olfactory Coding Professors and Supervisors | ApplySharif

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Gaia TavoniView profile

Assistant Professor

Washington University in St. LouisUnited States

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.

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Geraldine WrightView profile

Professor

University of OxfordUnited Kingdom

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.

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Gill BejeranoView profile

Professor

Stanford UniversityUnited States

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 .

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Anders LansnerView profile

Professor

KTH Royal Institute of TechnologySweden

Anders Lansner is a Professor of Computer Science at Stockholm University and holds an affiliated professorship at KTH Royal Institute of Technology. He leads the Lansner Lab (Computational Biology and Neurocomputing) at the Department of Computational Science and Technology (CST) within the School of Computer Science and Communication (CSC) at KTH. His research focuses on computational neuroscience and brain-like computing, emphasizing mathematical and computational models of neuronal networks in the neocortex and basal ganglia. Key projects include developing neuromorphic algorithms for supercomputers and FPGA-based hardware implementations. Lansner manages the computational neuroscience platform for the Stockholm Brain Institute (SBI) and the neuroinformatics platform for StratNeuro (Karolinska Institutet). His lab contributes to EU projects such as FACETS and NEUROChem, and collaborates with KTH’s Electronics Department on modular brain-inspired FPGA designs. Research interests span synaptic plasticity mechanisms, memory systems (episodic, semantic, and working memory), and applications in neuromorphic computing. He supervises graduate students and teaches courses in computational neuroscience. Lansner’s work bridges theoretical neuroscience with engineering, aiming to advance brain-inspired AI and hardware systems. His lab’s StreamBrain framework supports heterogeneous computing architectures for brain-like neural networks. Notable collaborations include cross-disciplinary efforts in neuromorphic hardware development (e.g., memristor-based learning engines) and olfactory system modeling. Lansner’s research addresses both fundamental brain mechanisms and technical applications in data analysis and neurorobotics.

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Antonio García CabotView profile

Associate Professor

University of AlcaláSpain

Antonio García Cabot is an Associate Professor in the Department of Computer Science at the University of Alcalá. His research focuses on artificial intelligence, educational technology, natural language processing, and mobile computing. He leads the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to the PMI group (Intelligent Mobile Platforms). He earned his Doctorate in Computer Science from the University of Alcalá in 2013 with a thesis titled *Propuesta de un sistema multi-agente para la adaptación de contenidos docentes a las competencias, contexto y dispositivo del usuario*. His work emphasizes accessibility in digital education, gamification in MOOCs, and software engineering innovations like automated code repair using LLMs. Research trends in his 2024-2025 publications include: Advancing AI applications in educational assessment (e.g., automated question generation, distractor design) Improving mobile app usability through gesture-based interfaces and sensor integration Developing large language model-based tools for vulnerability repair and teacher simulation analysis Systematic reviews on digital competence ecosystems and multilingual AI systems His contributions to open educational resources (OER) and accessible virtual campuses have been widely adopted in Latin America. Current research extends into embedded systems education and olfactory stimuli impacts on mobile app performance.

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Eva García LópezView profile

Professor

University of AlcaláSpain

Eva García López is a Professor in the Department of Computer Science at the University of Alcalá. She holds a PhD from the same institution, completing her thesis on improving the usability of interfaces for teaching objects in m-learning in 2013. Her research focuses on usability engineering, artificial intelligence, and educational technology, with emphases on mobile applications, accessibility, and gamification. She is affiliated with the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to TIFyC (Information Technologies for Training and Knowledge) and PMI (Intelligent Mobile Platforms). Eva’s work spans developing adaptive learning systems, enhancing digital content accessibility, and leveraging large language models for educational tools. Her projects include MOOC development, social gamification experiments, and usability evaluations of mobile instant messaging apps. She has also explored the impact of olfactory stimuli on user performance and the application of NLP in automated question generation. Her contributions include guidelines for accessible digital content creation and frameworks for personalized learning paths in web engineering curricula. Her research integrates interdisciplinary approaches, combining machine learning, human-computer interaction, and educational theory to address challenges in digital learning ecosystems. Notable contributions include frameworks for curriculum development, methodologies for usability evaluation, and tools for automated code vulnerability repair.

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Martin Paul NawrotView profile

Professor

University of CologneGermany

Prof. Dr. Martin Paul Nawrot is a faculty member at the Institute of Zoology , University of Cologne . His research focuses on neural information processing , reinforcement learning , and synaptic plasticity in biological and artificial systems. He also develops large-scale brain simulations to study attractor dynamics for sensory-motor integration, motor control, and decision-making in primates and insects. Current research areas include neuromorphic computing , spiking neural networks , and computational neuroscience Key projects involve modeling insect behavior , neural coding , and cross-species AI applications His recent publications (2023-2025) explore Drosophila larva locomotion , synaptic plasticity mechanisms , and neuromorphic hardware for real-time simulations. These works span neural circuits , behavioral modeling , and computational tools like GeNN and NEST. Despite his academic prominence, no scientific awards are mentioned in the available texts.

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Jeff LichtmanView profile

Professor

Harvard UniversityUnited States

Jeff Lichtman serves as the Jeremy R. Knowles Professor of Molecular and Cellular Biology and Santiago Ramón y Cajal Professor of Arts and Sciences at Harvard University, where he leads research within the Department of Molecular and Cellular Biology in the Faculty of Arts and Sciences. His laboratory focuses on the physical basis of long-lasting memory and experience-driven neural circuit restructuring through advanced connectomic approaches. Dr. Lichtman's research program centers on connectomics and neural circuit development , utilizing transgenic Brainbow models for in vivo visualization and automated serial electron microscopy for nanometer-resolution mapping. His lab investigates synaptic competition during mammalian development, circuit rearrangement in peripheral nervous systems, and the structural underpinnings of memory formation. Key research areas include cellular and molecular neuroscience with emphasis on developmental processes, synaptic connectivity dynamics, and experience-dependent circuit refinement. Analysis of his 2021-2025 publications reveals dominant methodological innovation in machine learning-guided microscopy (e.g., SmartEM) and correlative imaging techniques , with expanding applications across model systems including zebrafish, octopus, and human tissue. Recent work increasingly addresses Alzheimer's disease pathology within connectomic frameworks while maintaining core focus on developmental circuit formation. The Lichtman Lab maintains active development of high-throughput tools for neural circuit mapping, including Fishexplorer for zebrafish circuit dissection and large-scale human cerebral cortex reconstructions, with ongoing projects examining both peripheral and central nervous system connectivity.

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Elizabeth GlaterView profile

Associate Professor

Pomona CollegeUnited States

Elizabeth Glater is an Associate Professor of Neuroscience at Pomona College, where she has been affiliated since 2014. Currently on leave for the 2025-2026 academic year, she continues to lead research on the genetic and neuronal basis of behavior using Caenorhabditis elegans as a model organism. Education: Ph.D. from Harvard University, M.A. from Brown University, B.A. with High Honors from Swarthmore College Research Interests : Dr. Glater's work focuses on how genetic variation and environmental factors modify neural circuits to produce diverse behaviors. Her lab investigates C. elegans food choice mechanisms, olfactory recognition of pathogens, and the role of natural genetic variation in behavior. Scientific Awards : National Science Foundation Research Starter Grant (2012-13) for studying genetic mechanisms of food preference Collaborations & Teaching : Collaborates with Charles Taylor (Chemistry Department, Pomona College) to analyze odorants via SPME-GC-MS. Teaches courses like Genes and Behavior with Laboratory , Introduction to Neuroscience with Laboratory , and Senior Experimental Thesis .

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Kevin DalyView profile

Professor

West Virginia UniversityUnited States

Kevin Daly is a Professor at West Virginia University School of Medicine with appointments in both the Department of Neuroscience and the Rockefeller Neuroscience Institute. He holds the Eberly Family Distinguished Professor in Biology position and maintains his laboratory in the 4200 Life Sciences Building. His research is supported by multiple funding sources including the National Institute on Deafness and Other Communication Disorders (NIDCD) and the National Science Foundation (NSF). Daly's research focuses on understanding how motor neural networks communicate with sensory networks through corollary discharges or predictive motor signals. His laboratory investigates how sensory networks disambiguate environmentally generated stimuli from motor-driven reafference, with particular relevance to understanding sensory-based hallucinations in human brain diseases such as schizophrenia and Parkinson's disease. His work has significant implications for understanding the neural basis of sensory processing disorders. Analyzing his publication record from 2010-2024 reveals a consistent focus on sensory-motor integration, particularly in insect models. His research demonstrates how behaviors like flight affect sensory processing, with numerous publications examining how wing beat frequencies interact with olfactory systems in Manduca sexta and Drosophila. His more recent work has expanded into connectomics using electron microscopy reconstructions to map neural circuits with unprecedented detail. Daly maintains active collaborations with leading neuroscience institutions including Harvard University (The Lee Lab), Columbia University (The Card Lab), and Case Western Reserve University (The Dacks Lab). His laboratory provides state-of-the-art research opportunities for students, featuring advanced techniques like GCaMP imaging, optogenetics, and AI-based behavioral analysis. The Daly lab emphasizes collaborative mentorship, with graduate students expected to train and mentor undergraduate researchers while pursuing their individual development plans. The Daly Laboratory specializes in studying ascending histamine immunoreactive neurons (AHNs) in Drosophila, which represent just 2 pairs among approximately 1,860 ascending neurons connecting the ventral nerve cord to the brain. His team utilizes cutting-edge approaches including 2-photon microscopy, super-resolution fluorescence imaging, and advanced genetic tools to investigate how these circuits process sensory information during behavior. The lab's research environment fosters collaboration both within the laboratory and across institutional boundaries.

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Marc H GershowView profile

Associate Professor

New York UniversityUnited States

Marc H Gershow is an Associate Professor and Director of Undergraduate Studies for Physics at New York University's College of Arts and Science. His research focuses on understanding sensory processing and decision-making in model organisms like Drosophila larvae and C. elegans. He develops advanced microscopy techniques, including CRASH2p and 3D tracking two-photon imaging, to study neural activity in freely behaving animals. His work bridges neuroscience, physics, and engineering to uncover how organisms integrate sensory information with learned and innate behaviors. Education & Background While specific educational details are not explicitly listed, his research trajectory suggests a strong background in biophysics and neuroscience. His lab homepage indicates ongoing projects in olfactory circuits, sensory integration, and neurophysiological imaging. Research Interests Gershow's lab investigates neural mechanisms underlying navigation, olfactory learning, and decision-making. Key areas include: Olfactory circuits in Drosophila larvae and C. elegans Development of closed-loop imaging systems (e.g., CRASH2p) Multi-neuronal recording in unrestrained animals Integration of learned and innate sensory valences Awards & Recognition NSF CAREER Award (2015) NIH Director's New Innovator Award (2015) Lab & Collaborations His lab integrates engineering and biology, with a focus on creating tools for real-time neural activity analysis. Collaborations likely span physics, neuroscience, and computational biology. The lab homepage provides further details on ongoing projects and publications.

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Jessica NgView profile

Research Fellow

Princeton UniversityUnited States

Jessica Ng is a Research Fellow at Princeton University affiliated with the High Meadows Environmental Institute (HMEI). Her primary research focuses on extractivism and the energy transition, particularly examining lithium mining and decolonial climate justice frameworks. She explores just transition strategies rooted in land and labor movements, bridging environmental humanities, earth history, and energy engineering disciplines. Her academic work combines environmental policy analysis with technical investigations into sustainable resource management. Though her current HMEI affiliation emphasizes socio-environmental research, her scholarly outputs include significant contributions to insect olfactory neuroscience, reflecting prior research on mosquito host-seeking mechanisms and odor coding systems. Ng holds a Princeton University email address (jn0090@princeton.edu). Her publications span both environmental humanities and biological research, demonstrating interdisciplinary engagement. While no specific awards or grants are listed, her dual focus areas indicate active participation in both climate justice advocacy and life sciences research. Her work uniquely connects ecological systems analysis with social justice frameworks, offering critical perspectives on resource extraction's socio-environmental impacts. Though no formal student advisement is recorded, her research teams likely engage graduate students in these interdisciplinary projects.

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Madeleine BartlettView profile

Research Fellow

University of WaterlooCanada

Madeleine Bartlett is a Research Fellow at the University of Waterloo, affiliated with the Post Doctoral Scholars and Visitors groups. Her work bridges neuroscience and artificial intelligence, focusing on biologically plausible algorithms and their applications in robotics and human-robot interaction. Her research explores how neural mechanisms inspire computational models for reinforcement learning, action representation, and social signal processing. Key areas include integrating biological constraints into machine learning systems and developing robots capable of interpreting human social cues, particularly for therapeutic applications in autism spectrum disorder (ASD). Her publications highlight contributions to continuous action representations in basal ganglia models, biologically-based memory systems for reinforcement learning, and statistical rigor in human-robot interaction studies. She has also pioneered methods for estimating engagement in social HRI using novel neural architectures like Legendre memory units. While no formal awards or grants are listed, her work demonstrates significant innovation at the intersection of neuroscience-inspired AI and socially assistive robotics. She contributes to advancing robots as therapeutic tools through validated autonomous systems that mimic human guidance patterns observed in ASD therapy contexts.

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James JeanneView profile

Assistant Professor

Yale UniversityUnited States

James Jeanne is an Assistant Professor in the Department of Neuroscience at Yale School of Medicine. He holds affiliations with the Interdepartmental Neuroscience Program, Molecular Medicine, Pharmacology, and Physiology, as well as the Wu Tsai Institute. His research focuses on understanding how neural circuits implement computations supporting behavior, particularly in Drosophila melanogaster. He earned a B.S.E. in Electrical Engineering from Princeton University (2005), a Ph.D. in Computational Neuroscience from UC San Diego (2012), and completed postdoctoral work at Harvard Medical School (2017). Primary Research Themes: Sensory processing, working memory, decision-making, and neural circuit mechanisms in Drosophila Techniques: 2-photon optogenetics, whole-cell electrophysiology, connectomics, and calcium imaging Recent awards include the 2020 Klingenstein-Simons Fellowship and 2019 Smith Family Foundation Award. His lab investigates how circuit architecture enables flexible behavioral responses to sensory stimuli, with recent work exploring synaptic plasticity's role in odor tracking and decision-making algorithms in mushroom body circuits. Key collaborations include work with Rachel Wilson (Harvard), Timothy Gentner, and Tatyana Sharpee. His team has published in high-impact journals like Nature Communications , Current Biology , and Neuron .

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Andreas HerzView profile

Professor

Ludwig Maximilian University of MunichGermany

Andreas Herz is a Professor and Senior Scientist at the Division of Neurobiology, Faculty of Biology, Ludwig-Maximilians-Universität München (LMU). He is a Board Member and Speaker of the Bernstein Center Munich, a leading institution in computational neuroscience. His research integrates theoretical modeling with experimental data to explore neural dynamics, information processing, and spatial navigation. Institution: Ludwig-Maximilians-Universität München School: Faculty of Biology Department: Division of Neurobiology Leadership: Speaker, Bernstein Center Munich Email: herz@bio.lmu.de Herz’s research focuses on computational and theoretical neuroscience, particularly the neural basis of spatial navigation, population coding in grid cells, dendritic spine biophysics, and sensory information processing. He employs methods from dynamical systems, probability theory, and information theory to model single neurons and large-scale networks. His work spans model systems from grasshoppers to rodents and zebrafish, aiming to uncover general principles of neural computation. The recent publications highlight a strong trend in understanding grid cell dynamics, spatial memory, and dendritic computation. His work frequently involves decoding neural population activity, analyzing in vivo electrophysiological data, and developing theoretical frameworks for neural coding. Themes include burst firing, phase precession, remapping, and energy-efficient neural coding. He has mentored numerous PhD and MSc students through the Graduate School of Systemic Neurosciences (GSN), including Alexander Mathis, Johannes Nagele, and Michaela Poth. His group actively collaborates with experimental labs, contributing to interdisciplinary advances in neuroscience.

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