Find Academic Supervisors

Wei-Chung Allen LeeView profile

Associate Professor

• Neuroscience
• Connectomics
• Neural Circuits
• +3 more

Wei-Chung Allen Lee, PhD, is an Associate Professor of Neurology and Neurobiology at Harvard Medical School. His research focuses on understanding how neural circuits enable behavior through functional connectomics, combining advanced imaging, machine learning, and computational modeling. The Lee Lab develops tools like X-ray holographic nanotomography and GridTape for high-resolution neural structure analysis. Key interests include circuit principles in Drosophila, cerebellar interneurons, and synaptic wiring in decision-making regions. His work explores structural-functional relationships in networks, conservation across species, and developmental constraints on neural architecture. Recent studies highlight connectomic reconstructions in Drosophila, cerebellar disinhibition mechanisms, and blood-brain barrier heterogeneity. Methodological innovations in microscopy and image restoration underscore his lab’s interdisciplinary approach. The Lee Lab is located at 220 Longwood Avenue, Boston, MA, and collaborates on large-scale neuroimaging pipelines like the Open Connectome Project.

Michael VermeuelView profile

Assistant Professor

• Atmospheric Chemistry
• Air Quality
• Climate Science
• +3 more

Dr. Michael Vermeuel is an Assistant Professor in the Department of Earth, Atmospheric, and Planetary Sciences at Purdue University. He leads the AIR CheM (Atmospheric Interdisciplinary Research in Chemistry and Meteorology) group, focusing on reactive atmospheric gases impacting air quality, climate, and ecosystems. His work combines field observations, chemical transport modeling, and laboratory studies. Education: PhD in Chemistry (2021), University of Wisconsin – Madison MS in Chemistry (2017), University of Wisconsin – Madison BS in Chemistry (2015), The College of New Jersey Research Interests: Dr. Vermeuel’s group investigates the sources and fates of atmospheric chemicals using advanced techniques such as chemical ionization mass spectrometry and micrometeorological flux measurements. Key areas include ozone deposition dynamics, VOC cycling in forests, and marine-abiotic VOC sources. His work bridges laboratory experiments, field campaigns (e.g., FROG-NY, FluCS), and model development to address environmental challenges. Awards: AGU James R. Holton Award (2024) His lab emphasizes interdisciplinary collaboration, with projects addressing urban pollution, wildfire impacts, and climate feedbacks. Current research includes the Fluxes of Reactive Organic Gases in New York (FROG-NY) and the Flux Closure Study (FluCS) at Manitou Experimental Forest.

Christian LeiboldView profile

Professor

• Neuroscience
• Neural Network Modelling
• Hippocampal Formation
• +3 more

Prof. Dr. Christian Leibold is a former faculty member of the Faculty of Biology at Ludwig-Maximilians-Universität München (LMU). His research focuses on theoretical and experimental neuroscience, particularly the hippocampal formation's role in spatial navigation and temporal coding. He investigated topics such as auditory processing, phase precession in hippocampal neurons, and the interaction between brain regions like the medial entorhinal cortex and hippocampus. Research Interests: Modeling hippocampal sequences and spatial navigation Temporal processing in auditory brainstem circuits Neuronal mechanisms of grid cells and place fields Data analysis of hippocampal activity patterns Collaborations: University of California San Diego (UCSD) Charité – Universitätsmedizin Berlin Bernstein Center for Computational Neuroscience (BCCN) Munich His work combines computational modeling with experimental approaches, addressing how neural circuits process spatial and temporal information. He contributed to understanding axonal myelination dynamics and the role of medial superior olive neurons in auditory localization.

Yian YinView profile

Assistant Professor

• Computational Social Science
• Data Science
• Network Science
• +5 more

Dr. Yian Yin is an Assistant Professor of Information Science at Cornell University within the Cornell Bowers College of Computing and Information Science. His research focuses on computational social science, data science, and network science to study scientific progress, innovation, and complex social processes. He has affiliations with Northwestern University’s Northwestern Institute on Complex Systems (NICO) and Kellogg Center for Science of Science and Innovation (CSSI). Education: Ph.D. in Industrial Engineering and Management Sciences from Northwestern University Bachelor's degrees in Statistics and Economics from Peking University Research Interests: Computational tools for understanding scientific collaboration and innovation Analysis of policy impacts on scientific output during crises Quantitative frameworks for studying failure in scientific endeavors Cross-disciplinary applications in art, economics, and public health Awards: Forbes 30 Under 30 in Science (2023) Emerging Researcher Award from Complex Systems Society (2023) Advancement Activities: Organized Summer Institute in Computational Social Science (SICSS) Chicago Program Co-Chair for International Conference on Science of Science and Innovation Labs/Teams: Leads computational social science research groups at Cornell, focusing on science-of-science methodologies and innovation ecosystems.

Maria Christina MarianiView profile

Professor

• Applied Mathematics
• Nonlinear partial differential equations
• Stochastic differential equations
• +5 more

Maria Christina Mariani is a Professor and Department Chair in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP). Her interdisciplinary research bridges mathematics with applications in public health, geophysics, physics, and finance, with a focus on developing novel mathematical models for complex data analysis. Dr. Mariani earned her Ph.D. in Mathematics from the University of Buenos Aires in 1992, where she received an Outstanding dissertation award. She also holds an M.S. in Physics (1996) and an M.S. in Mathematics (1987), both from the University of Buenos Aires with highest honors. Her research interests span Applied Mathematics, Nonlinear partial differential equations, Stochastic differential equations, Machine Learning techniques, Mathematical Finance, Mathematical Physics, and Numerical Methods. She has developed mathematical models for medical data analysis (particularly breast cancer, heart disease, and prostate cancer), seismic and explosive data, and financial markets. Her work emphasizes the development of mathematical models to enhance understanding of medical data and extreme events in various phenomena. Dr. Mariani's recent research focuses on applying machine learning and stochastic models to complex data sets across multiple domains. Her work demonstrates consistent innovation in developing novel algorithms for medical diagnosis and prognosis, analyzing seismic data, and modeling financial markets using Levy processes, Ornstein-Uhlenbeck models, and wavelet techniques. She has mentored numerous students throughout her career, including PhD candidates, MS students, and post-doctoral researchers, demonstrating her commitment to academic development and knowledge transfer. Dr. Mariani has served as Department Chair and holds the Shigeko K. Chan Distinguished Professor title in Mathematical Sciences, reflecting her significant contributions to the field and institution.

• Computer Graphics
• Human-Computer Interaction
• Robotics
• +3 more

Dr. Daniel Berio is a researcher at Goldsmiths, University of London, specializing in computational models for human-like movement in digital art and robotics. His work bridges computer graphics, cognitive psychology, and robotic manipulation, focusing on stylized stroke generation, graffiti analysis, and kinematic modeling. He collaborates with Frederic Fol Leymarie and Rejean Plamondon, utilizing the Sigma Lognormal model to simulate human handwriting dynamics. Education : Doctoral thesis on AutoGraff (2021), exploring computational understanding of graffiti and calligraphy. Research Themes : Human-like motion in digital art, kinematic reconstruction from static traces, robotic graffiti generation, and perceptual fluency in aesthetic evaluation. Publications : 15+ works since 2015, spanning ACM Transactions on Graphics, British Journal of Psychology, and conferences like MOCO and IROS. Applications : Font stylization tools, synthetic graffiti generation, compliant robot control, and semantic typography systems.

Jacob PutneyView profile

Assistant Professor

• Biometrics
• Forest Health
• Forest Management
• +3 more

Jacob Putney is an Assistant Professor (Practice) and Extension Agent at the College of Forestry, Oregon State University , affiliated with the Forest Engineering, Resources & Management department. His work bridges academic research and practical application in forest management. Education: MS in Forest Biometrics (2019), BS in Forest Management (2016) from Oregon State University Research interests span forest biometrics, silviculture, forest health, biodiversity, and fire ecology, with a focus on nitrogen fertilization impacts and growth modeling. His expertise includes biometrics, growth/yield analysis, and sustainable forest management. Recent publications highlight mechanisms of Douglas-fir response to nitrogen fertilization and broader reforestation strategies in Oregon. While no scientific awards are mentioned, his work integrates field data with ecological modeling to enhance forest productivity.

Siavash VahidiView profile

Assistant Professor

• Structural Biology
• Protein Degradation
• Mycobacterium tuberculosis Research
• +4 more

Dr. Siavash Vahidi is an Assistant Professor in the Department of Molecular and Cellular Biology at the University of Guelph. His research focuses on understanding the structure, function, and dynamics of large biomolecular machines, particularly those involved in protein degradation in pathogens like Mycobacterium tuberculosis . He employs advanced techniques such as mass spectrometry (H/D exchange, native MS) and high-field NMR spectroscopy to study these systems. His lab is actively recruiting students and postdocs, emphasizing a commitment to diversity and training in cutting-edge methodologies. Education: BSc in Chemistry, National University of Iran, Tehran PhD in Chemistry and Biochemistry, University of Western Ontario CIHR Postdoctoral Fellowship, University of Toronto & The Hospital for Sick Children Research: Key interests include the M. tuberculosis proteasome system, ClpP proteases in human mitochondria, and the role of allostery in substrate selection. The lab’s integrative approach combines structural biology with biochemical and computational methods, aiming to identify novel drug targets for tuberculosis and other diseases. Awards: Paul de Mayo Award for Best PhD Thesis Lab & Training: The Vahidi Lab emphasizes interdisciplinary training, offering expertise in mass spectrometry, NMR, and computational tools (e.g., Python, Linux). Supported by grants and collaborations, the lab fosters an inclusive environment with a strong focus on mentorship. Lab Resources: Website: Vahidi Lab Twitter: @VahidiLab

Guillaume DuclosView profile

Assistant Professor

• Biophysics
• Soft Condensed Matter Physics
• Active Matter
• +5 more

Dr. Guillaume Duclos is an Assistant Professor in the Martin A. Fisher School of Physics at Brandeis University, where he leads the Duclos Lab. His research focuses on the physics of active matter, biomimetic systems, and the interplay between molecular motors and soft materials. He holds a PhD from Institut Curie and Pierre et Marie Curie University (Paris, France). His lab investigates pattern formation in active materials, topological defects in nematics, and collective cell migration. Key funding includes NSF CAREER (2021–2026) and DOE Early Career (2023–2028) awards. Current students include Annemarie Winters (co-advised with Hannah Yevick), Benjamin Strain, Bennett Sessa, and Adrielle Cusi. Alumni include Dr. Bibi Najma (now at Caltech) and Dr. Salman Alam (at Lam Research). The lab emphasizes interdisciplinary training in biophysics, soft matter, and quantitative biology. Recent work includes studies on 3D pattern formation in protein-membrane systems, microtubule-motor interactions, and active nematic droplets. Research facilities support cutting-edge microscopy and computational modeling.

Jun BaiView profile

Assistant Professor

• Machine Learning
• Deep Learning
• Medical Image Analysis
• +2 more

Jun Bai is an Assistant Professor in the Department of Computer Science at the University of Cincinnati's College of Engineering and Applied Science. His research focuses on Machine Learning, Deep Learning, Medical Image Analysis, AI-driven diagnostics for cancer and diseases, and drug discovery. He holds a Ph.D. in Computer Science and Engineering from the University of Connecticut (2023), an M.S. in Computer Science from the University of Dayton (2019), and an M.S. in Interdisciplinary Studies in Education (2015). His work emphasizes applying AI to healthcare challenges, such as robust mammogram classification, 3D biomedical image registration, and peptide generation for drug discovery. Recent studies include hybrid transformer models for medical imaging and weakly-supervised systems for prostate cancer diagnosis. His computational methods span molecular dynamics simulations and graph neural networks. Despite his prolific research output, no specific grants, advising roles, or lab affiliations are explicitly listed in the provided data. Contact: Rhodes Hall 891, Cincinnati, OH | Email: baiju@ucmail.uc.edu

Tony WhiteView profile

Adjunct Professor

• Artificial Intelligence
• Swarm Intelligence
• Genetic Algorithms
• +4 more

Dr. Tony White is an Adjunct Professor in the School of Computer Science at Carleton University. He holds a Ph.D. from Carleton (2000), an M.A. from Cambridge, and a B.A. in Theoretical Physics. His research focuses on complex adaptive systems, including influence measurement in social networks and swarm intelligence applications. He leads the Complex Adaptive Systems Group and has extensive industry experience, previously working at Nortel. Education: Bachelor of Theoretical Physics, Cambridge University (1981) Master of Physics, Cambridge University (1981) Master of Computer Science, Carleton University (1993) Ph.D. in Electrical Engineering, Carleton University (2000) Research Interests: Artificial Intelligence Swarm Intelligence Genetic Algorithms Neural Networks Recommender Systems Search Engines His work explores influence dynamics in social networks, adaptive information systems, and evolutionary computation. Recent publications address neural network topologies, distributed control strategies, and embedded systems administration. He has also contributed to trust models, referral networks, and traffic signal optimization. Dr. White’s research bridges theoretical computer science and practical applications in robotics, network management, and autonomous systems. Labs/Teams: Leads the Complex Adaptive Systems Group, focusing on interdisciplinary approaches to complex systems and swarm intelligence.

Rui SunView profile

Associate Professor

• Computational Chemistry
• Physical Chemistry
• Molecular Dynamics Simulation
• +4 more

Rui Sun is an Associate Professor and Department Associate Chair in the Department of Chemistry at the University of Hawaii at Manoa. His research focuses on computational methods for studying chemical reactions and biochemical processes, including gas-phase reaction mechanisms, solvent effects in condensed-phase reactions, and drug permeation modeling. He has collaborated with Eli Lilly and Company on small molecule drug permeation studies. B.S. in Chemistry, Shandong University (2009) Ph.D. in Chemistry, Texas Tech University (2014) Postdoctoral scholar at the University of Chicago (2014–2017) under Gregory A. Voth Dr. Sun’s work integrates ab initio molecular dynamics simulations and enhanced sampling techniques to advance understanding of biophysical systems and reaction mechanisms. He joined UH Manoa in 2017 and holds affiliations with the Graduate Faculty and Departmental committees. His research has been supported by industry partnerships and awards, including the Eli Lilly Scientific and Technical Advisory Board Award. He contributes to both teaching and administrative roles within the Department of Chemistry.

Eric MayView profile

Associate Professor

• Computational Biophysics
• Theoretical Biophysics
• Biochemistry
• +7 more

Eric May is an Associate Professor in the Department of Molecular and Cell Biology at the University of Connecticut, with research focused on computational and theoretical biophysics and biochemistry. His work bridges physical mechanisms in biology with applications in nanotechnology and biomedical engineering, particularly studying conformational transitions and mechanical properties of biological materials. May's research explores structural changes in non-enveloped viruses during infection, membrane disruption, protein folding, structural prediction, and mitochondrial peptide interactions. His group utilizes advanced molecular dynamics simulations to connect single-molecule and ensemble experimental data, developing tools like BUMPy for lipid bilayer modeling. Recent computational studies highlight his expertise in pH-dependent viral capsid behavior, mitochondria-targeted peptides, and lipid bilayer interactions. He has published extensively on topics including viral lytic peptides, cardiolipin dynamics, and nanotube architecture, though no specific awards or student advisement details are mentioned in available records. His lab at UConn (maylab.uconn.edu) investigates how environmental stimuli affect viral structures and biomedical systems, combining theoretical approaches with experimental correlations to advance understanding of biological and synthetic material behavior.

Jens BochView profile

Professor

• Genome Editing
• Plant Biotechnology
• Bacterial Pathogens
• +3 more

Prof. Jens Boch is a Professor at Leibniz University Hannover's Institute of Plant Genetics, specializing in plant biotechnology and genome editing. He leads the Boch group, focusing on developing crops with improved traits using TALEN and CRISPR tools. His research investigates plant pathogens like Xanthomonas , particularly their TALE effectors that manipulate host genes. Key roles include Chair of the Biology Examination Board and membership in external committees such as the Konferenz Biologischer Fachbereiche (KBF). Education & Affiliations: No explicit education details provided; affiliated with Leibniz University Hannover's Faculty of Natural Sciences. Research Interests: Genome editing applications in agriculture, bacterial pathogen strategies (e.g., Xanthomonas TALE effectors), plant defense mechanisms, and crop improvement. Recent work includes base editor developments for mitochondrial disease modeling (2025), allergen reduction in mustard (2022), and TALE-based tools for gene activation (2022). His group collaborates on projects like removing allergens and enhancing cattle heat resistance via embryo editing. Media contributions include podcasts and discussions on genome editing ethics and applications.

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

Zijiang J He, PhD, is a Professor and Distinguished University Scholar in the Department of Psychological and Brain Sciences at the University of Louisville. His research focuses on visual perception, particularly the mechanisms underlying 3D depth perception and middle-level vision. He holds a B.S. in Biophysics from the University of Science and Technology of China (1983), M.S. in Neurobiology from Shanghai Institute of Physiology (1986), and Ph.D. in Physiological Optics & Neuroscience from the University of Alabama at Birmingham (1990). Postdoctoral training was completed at Harvard University (1994). Research interests include space vision mechanisms and middle-level vision processes. His lab explores how the brain integrates 2D retinal images into 3D spatial perception, leveraging virtual reality and psychophysical methods. Key contributions include studies on sensory eye dominance, binocular rivalry, and perceptual learning protocols for amblyopia. He leads the Visual Perception and Cognition Lab, emphasizing interdisciplinary approaches combining neuroscience, computational modeling, and behavioral experiments. Notable achievements include the Distinguished University Scholar title and impactful publications in *Nature*, *Science Advances*, and *Proceedings of the National Academy of Sciences*. His work bridges ecological regularities and neural processing, advancing understanding of visual system adaptations to spatial environments.