Find Academic Supervisors

Jonathan D VictorView profile

Professor

• Computational Neuroscience
• Neurophysiology
• Sensory Physiology
• +3 more

Jonathan D Victor is Professor of Computational Neuroscience in Computational Biomedicine at the Institute for Computational Biomedicine, Professor of Neuroscience at the Brain and Mind Research Institute, and Fred Plum Professor of Neurology within the Department of Neurology at Weill Cornell Medical College (Cornell University). He serves as an Attending Neurologist at NewYork-Presbyterian Hospital and directs the Division of Systems Neurology and Neuroscience. His educational background includes: B.A. from Harvard University (1973) Ph.D. in Neurophysiology from The Rockefeller University (1979) M.D. from Cornell University Medical College (1980) Victor's research integrates computational neuroscience with clinical neurology, focusing on neural coding in sensory systems (vision, taste, smell), disorders of consciousness, and eye movement dynamics. He employs information theory, statistical modeling, and electrophysiology to decode how the brain processes natural stimuli and recovers from injury, with emphasis on perceptual spaces and neural network signatures. Analysis of his 2023-2025 publications reveals three dominant trends: computational modeling of sensory-motor transformations in natural behaviors (e.g., Drosophila locomotion), geometric frameworks for perceptual spaces (visual texture, depth processing), and EEG-based biomarkers for traumatic brain injury recovery (alpha coherence, thalamic stimulation). No scientific awards were explicitly documented in the source material. He secures major NIH/Foundation grants as Principal Investigator or Co-Investigator, including National Eye Institute projects on fixational eye movements (2022-2026), James S. McDonnell Foundation's Covid-19 consciousness recovery consortium (2020-2025), and National Cancer Institute's NeuroNex olfactory behavior study (2020-2026). These fund translational work bridging neural coding theory with clinical applications. Victor leads the Division of Systems Neurology and Neuroscience, leveraging collaborations with Weill Cornell's Brain and Mind Research Institute and Institute for Computational Biomedicine. His external relationships include consulting for Elsevier and Springer Science and Business Media on scientific publishing and data analysis.

Hagen RadtkeView profile

Researcher

• Marine Biogeochemistry
• Coastal Ocean Dynamics
• Climate Change Impact on Baltic Sea
• +4 more

Hagen Radtke is a Researcher at the Leibniz Institute for Baltic Sea Research (IOW) under the University of Rostock's Faculty of Mathematics and Natural Sciences . His work focuses on physical and biogeochemical modeling of the Baltic Sea , with emphasis on salinity dynamics , sediment-water interactions , and element cycling in marine ecosystems. Key Research Areas: Decadal variability in Baltic Sea salinity Mechanistic sediment process modeling Element tagging methods for nutrient pathways Numerical stability in ecosystem models Code generation tools for marine simulations Model validation through "Validator" software Publication Trends demonstrate expertise in Baltic Sea climate projections , microplastics transport , and coupled atmosphere-ocean modeling . His work intersects oceanography , biogeochemistry , and environmental informatics , with significant contributions to ERGOM SED (a benthic-pelagic coupled model) and BMIP (Baltic Model Intercomparison Project). Teaching includes "Fundamentals of Marine Biology - Oceanography" in the University of Rostock's Master's program, covering physical oceanography principles. He developed open-source model validation tools and pioneered mechanistic sediment modules for marine ecosystem projections.

Marc HOFFMANNView profile

Professor

• Statistics
• Nonparametric Statistics
• Stochastic Processes
• +3 more

Marc HOFFMANN is a Professor at Université Paris Dauphine-PSL and holds the Fundamental Chair at the Institut Universitaire de France since 2024. His academic journey includes roles at institutions such as INRIA (2020-2022), École Polytechnique (2007-2015), and Université Gustave Eiffel (2003-2012). Research Focus: Statistics of random processes, nonparametric statistics, and applications in financial modeling and population biology. Key Contributions: Adaptive estimation, confidence bands, inverse problems, rough volatility modeling, and growth-fragmentation processes. Advising: Supervised 19 PhD students with topics spanning statistical inference, Hawkes processes, and stochastic volatility. Collaborations include CIFRE grants with EDF, SCOR, and Banque de France. Scientific Awards : Fundamental Chair at Institut Universitaire de France (2024).

• Statistical Bioinformatics
• Computational Biology
• Spatial Transcriptomics
• +4 more

Dr. Shila Ghazanfar is an Australian Research Council DECRA Fellow at the University of Sydney, Faculty of Science. She is an expert in statistical and computational analysis of spatial transcriptomics and single-cell RNA-seq data, with a focus on developing bioinformatic approaches for integrating complex biological datasets across various omics modalities. Her educational background includes: Undergraduate studies in statistics and statistical bioinformatics at The University of Sydney PhD in statistics and statistical bioinformatics at The University of Sydney Royal Society Newton International Fellowship at The University of Cambridge under Dr. John Marioni in computational biology Dr. Ghazanfar's research interests center on developing statistical bioinformatic and biomedical data science approaches for meaningful integration of complex and high-dimensional biological datasets. Her multidisciplinary expertise spans statistics, statistical bioinformatics, and computational biology, enabling her to devise strategies to jointly model processes generating diverse data sources. Her work aligns with the University of Sydney Faculty of Science Research Strengths in Complex Systems, Precision and Digital Health, and Data and Decisions. Analysis of her recent publications (2021-2025) reveals strong focus areas including spatial transcriptomics infrastructure development, single-cell data integration methodologies, and applications in cancer research and cardiovascular biology. Key trends show progression from foundational method development to increasingly sophisticated multi-modal integration approaches, with significant emphasis on creating open-source computational tools for the research community. Her scientific recognition includes: Australian Research Council DECRA Fellowship Royal Society Newton International Fellowship Dr. Ghazanfar actively mentors research students, including Angel GUAN working on melanoma immunotherapy research. Her grant portfolio demonstrates substantial research support: 2023: Statistical Bioinformatics for Single Cell, Spatial and Multiomic Biotechnologies (Faculty of Science) 2022: Defining spatiotemporal mechanisms for peripheral nerve regeneration (Partnership Collaboration Award) 2022: Multiscale data integration for single cell spatial genomics (Chan Zuckerberg Initiative) Australian Research Council DECRA for statistical approaches in spatial genomics As a member of the Charles Perkins Centre, Dr. Ghazanfar participates in interdisciplinary research addressing complex health challenges through computational biology approaches, with collaborations spanning multiple domains from basic science to clinical applications.

Wesley TanseyView profile

Assistant Professor

• Statistical Machine Learning
• Computational Oncology
• Bayesian Statistics
• +3 more

Wesley Tansey serves as Assistant Professor in the Computational Oncology group within the Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center (MSKCC). His research bridges statistical machine learning with cancer biology, focusing on developing novel computational frameworks for oncology applications. Dr. Tansey's research program centers on Bayesian statistical methods for biological data analysis, with particular emphasis on spatial transcriptomics (evidenced by his BayesTME framework), drug response modeling , and multi-omics integration . His lab develops scalable algorithms for high-dimensional biological data, including UnitedMet for metabolite imputation and MultiTME for spatial profiling analysis. Current projects address combinatorial drug screening optimization, tumor microenvironment characterization, and predictive oncology platforms for rare cancers. His recent publications (2023-2025) demonstrate strong focus areas: Bayesian active learning for drug screening (6+ publications) Spatial biology methods (BayesTME, MultiTME) Metabolomics-transcriptomics integration (UnitedMet) Causal inference in biological systems Scientific recognition includes serving as Area Chair for AISTATS 2022 and frequent invited talks at major conferences including SIAM's Mathematics of Data Science meeting. Dr. Tansey actively mentors lab members including Sophie Jaro (Spotlight presenter at ICML Workshop), Haoran Zhang (contributed talk presenter), Christopher Tosh (Associate Research Scientist), and Jeff Quinn (Bioinformatics Software Engineer). His lab receives research funding supporting development of computational oncology platforms with clinical translation potential. The VIVO Lab maintains active GitHub repositories for core methodologies including BayesTME, reflecting strong software engineering practices in computational biology.

• Multiscale Materials Modelling
• Virtual Design
• Nanotechnology
• +1 more

Celso Ricardo Caldeira Rego is a postdoctoral researcher at the Karlsruhe Institute of Technology (KIT), affiliated with the Institute of Nanotechnology. His research focuses on multiscale materials modeling and virtual design, contributing to advancements in nanomaterials engineering and computational methods for material innovation. His work intersects Materials Science , Computational Modeling , and Nanotechnology , emphasizing cross-disciplinary approaches for industrial and academic applications. The Institute of Nanotechnology provides state-of-the-art infrastructure for his collaborative projects.

Andrei PisliakovView profile

Senior Lecturer

• Theoretical Biophysics
• Computational Biophysics
• Biomolecular Simulations
• +8 more

Dr. Andrei Pisliakov is a Senior Lecturer and Dundee Fellow at the University of Dundee, affiliated with the School of Science and Engineering. His research bridges theoretical physics, chemistry, and biology through computational biophysics. PhD: Theoretical Chemistry, Technical University of Munich MSc: Physics, Belarus State University His work focuses on developing and applying computational methods like atomistic molecular dynamics (MD), quantum mechanics/molecular mechanics (QM/MM), and hierarchical multiscale simulations to study membrane proteins, proton transfer in biological systems, and bioenergetics. Key applications include RNA processing enzymes, SARS-CoV-2 helicase, respiratory enzymes, and GPCR signaling. Recent research trends highlight interdisciplinary collaborations in structural biology and biochemistry, notably identifying novel interaction sites in mRNA capping enzymes. His 15 most recent publications emphasize computational approaches to RNA regulation, viral protein modeling, and proton dynamics in membrane systems. FPR Fellow, RIKEN Institute Dundee Fellow, University of Dundee Dr. Pisliakov's career spans postdoctoral work at UC Berkeley and the University of Southern California, followed by contract research at RIKEN Institute. He has contributed to understanding ultrafast energy transfer in photosynthetic complexes, enzyme catalysis, and proton transport mechanisms in bioenergetic systems.

• Calculus of Variations
• Multiscale Methods
• Atomistic Models
• +4 more

Dr. Leonard Kreutz is a Researcher at the Department of Mathematics , Technical University of Munich (TUM), leading an Emmy Noether Junior Research Group since 2023. He has held postdoctoral positions at Carnegie Mellon University, WWU Münster, and Universität Wien, and was an acting professor at TUM in 2019. Education: PhD (2018) from Gran Sasso Science Institute, Honors Master (2014) and Bachelor (2013) in Mathematics at TUM. Research Interests: His work focuses on the Calculus of Variations , Multiscale Methods , and Discrete-to-Continuum Limits , particularly in modeling crystallization, elastic materials with voids, and topological singularities in spin systems. He explores free-discontinuity problems and geometric rigidity in variable domains. Publications span 2023–2017, emphasizing atomistic models , nonlinear elasticity , and homogenization across mathematics, materials science, and physics. Collaborative projects with leading experts like M. Cicalese and A. Braides dominate his output. Scientific Award: Emmy Noether Junior Research Group Grant (2023–present). Collaborations include institutions such as Carnegie Mellon University, WWU Münster, and the University of Vienna. His research intersects with groups focused on Mathematical Finance , Numerical Analysis , and Quantum Information Theory at TUM.

Esmae WoodsView profile

Research Fellow

• Computational Physics
• Theoretical Physics
• Algorithm Development
• +7 more

Esmae Woods is a Research Fellow in the Department of Engineering, specializing in theoretical and computational physics with a focus on algorithmic and software development. She completed her PhD at the University of Cambridge, where she studied dynamical processes on energy landscapes, particularly in large ill-conditioned systems. Currently, she contributes to the MaThRad project, advancing Monte Carlo simulations for radiation transport applications such as criticality safety calculations. Education: PhD in Physics, University of Cambridge Her research bridges computational physics, numerical analysis, and biophysics. She develops algorithms to address challenges in energy landscape analysis, rare event simulations, and Markov chain modeling. Recent work emphasizes Monte Carlo methods for radiation transport and multiscale modeling of chromatin organization. Publications highlight her contributions to fields including energy transfer in photosynthetic systems, polaritonic rate suppression, and the structural dynamics of chromatin. Her methods are particularly impactful for systems where numerical instability complicates direct computation. Woods collaborates with researchers like Eugene Shwageraus and David J. Wales, advancing mathematical and computational frameworks in interdisciplinary contexts.

Mohammad SarhilView profile

Researcher

• Phase-field Modeling
• Computational Mechanics
• Materials Science
• +5 more

Mohammad Sarhil is a researcher at the University of Duisburg-Essen and a PostDoc at TU Dortmund University, affiliated with the Institute of Mechanics and Jörg Schröder's Lab. He holds a Dr.-Ing. (PhD) in Mechanics with distinction from 2024. Diploma in Structural Engineering (2012) from Latakia University, Syria M.Sc. in Computational Mechanics (2015) from University of Duisburg-Essen His research focuses on phase-field modeling , micromorphic continua , and metamaterials , particularly for fatigue analysis in fiber-reinforced concrete and higher-order homogenization theories. Key trends include finite element formulations, parameter identification, and multiscale residual stress analysis. Scientific recognition includes: DAAD scholarship Best Graduate award (Latakia University) His work bridges computational mechanics, generalized continuum theories, and fracture mechanics with applications in structural and materials engineering.

• Computational Chemistry
• Organic Chemistry
• Quantum Chemistry
• +4 more

Daniele Padula serves as an Associate Professor in the Department of Biotechnology, Chemistry and Pharmacy at the University of Siena, where he teaches Applied Computational Chemistry, Organic Chemistry, and Heterocyclic Organic Chemistry for Chemistry, Biotechnology, and Pharmacy degree programs. His institutional contact details include office location (II lotto, III floor, room B_03_86) and direct communication channels through university email and phone systems. Padula's research integrates computational and organic chemistry methodologies to investigate fundamental properties of organic electronic materials. His primary focus areas include quantum-mechanical modeling of charge transport mechanisms, design of chiral photoluminescent systems with inverted singlet-triplet gaps, development of accurate force fields for molecular simulations, and computational exploration of photoswitches and organic semiconductors. This interdisciplinary work bridges theoretical chemistry with practical applications in optoelectronics and materials science. Analysis of his 15 most recent publications (2024-2025) reveals three dominant research thrusts: (1) Advanced computational protocols for quantum-mechanically derived force fields (evident in JOYCE3.0 development), (2) Fundamental studies of chiral phenomena in organic materials for circularly polarized luminescence applications, and (3) Multiscale modeling of charge and exciton transport mechanisms in organic semiconductors. His work increasingly incorporates machine learning techniques to accelerate materials discovery while maintaining quantum chemical accuracy. Scientific awards: No awards or fellowships were documented in the provided materials. Advising and grant activities: The available documentation does not specify doctoral students, postdoctoral researchers, or externally funded research projects. His teaching portfolio indicates supervision of graduate and undergraduate theses within his computational chemistry courses. Research infrastructure: While specific laboratory facilities aren't detailed, his publication record suggests active participation in computational research groups with access to high-performance computing resources, likely through the University of Siena's computational chemistry infrastructure and potential collaborations with experimental groups for validation studies.

• Computational mechanics
• Nonlinear finite element method
• Advanced finite beam formulations
• +2 more

Jens Wackerfuß is a Full Professor of Structural Analysis and Executive Director of the Institute of Structural Mechanics at the University of Kassel, Germany, positions he has held since 2014. He also leads an Emmy Noether Junior Research Group at the university, demonstrating his significant research leadership. His academic background includes a Dr.-Ing. (Civil Engineering) from Technical University Darmstadt in 2005 and a Dipl.-Ing. (Civil Engineering) from the same institution in 1997. His professional journey includes post-doctoral work at UC Berkeley (2007-2008) and leadership of an Emmy Noether Junior Research Group at Technical University Darmstadt (2010-2013). Professor Wackerfuß's research spans computational mechanics with particular expertise in nonlinear finite element methods, advanced beam formulations, multiscale methods, and molecular mechanics. His work bridges theoretical developments with practical engineering applications, and he has developed the research code dockSIM for computational structural analysis. His teaching portfolio includes Structural Analysis I and II for Bachelor's students and Finite Element Methods, Material Models, and Multiscale Methods for Master's students. His recent publications (2022-2024) reveal a strong focus on constraint handling in finite element analysis, graphene modeling, and innovative structural formulations. Key trends include efficient methods for nonlinear multi-point constraints, coupling different structural elements, and applying computational methods to nanoscale materials. His scientific achievements have been recognized with several prestigious awards: Emmy Noether Programme of the German Research Foundation (DFG) in 2010 Zienkiewicz Medal and Prize in 2009, London (UK) Research fellowship of the German Research Foundation (DFG) at TU Darmstadt in 2008 Research fellowship of the German Research Foundation (DFG) at UC Berkeley in 2007 Professor Wackerfuß supervises doctoral and master's students through his Research Colloquium for Thesis and Doctoral Students. His grant portfolio includes significant funding from the German Research Foundation (DFG), particularly through the Emmy Noether Programme which supports outstanding early-career researchers. He leads the Institute of Structural Mechanics at the University of Kassel and maintains the research code dockSIM. His team focuses on developing advanced computational methods for structural analysis, with particular expertise in nonlinear systems, constraint handling, and multiscale modeling approaches that bridge molecular and continuum mechanics.

• Complex fluids
• Statistical Physics
• Fluctuation relations in small systems
• +19 more

Tapio Ala-Nissilä is Professor of Physics at Aalto University School of Science, Finland, where he heads the Multiscale Statistical and Quantum Physics (MSP) group. He simultaneously serves as Head of the Interdisciplinary Centre for Mathematical Modelling and Professor of Applied Mathematics & Theoretical Physics at Loughborough University, UK, and as Adjunct Professor of Physics at Brown University, USA. His research spans statistical physics, quantum mechanics, and soft matter systems with emphasis on computational approaches. Key interests include complex fluids, nanofluids, polymer translocation, quantum thermodynamics, and open quantum systems. He extensively employs molecular dynamics, Monte Carlo methods, and density functional theory to study nanoscale phenomena in biological, material, and quantum contexts. Recent publications (2024-2025) reveal strong interdisciplinary trends across quantum materials, biophysics, and environmental engineering. Work focuses on thermal properties of 2D materials like graphene, protein dynamics in viral systems, novel surface phenomena in liquid-repellent materials, and advanced computational methods for many-body quantum systems. He directs the Multiscale Statistical and Quantum Physics group at Aalto University investigating fundamental quantum and statistical phenomena, and leads the Interdisciplinary Centre for Mathematical Modelling at Loughborough University fostering cross-departmental collaboration in applied mathematics.

• Numerical Analysis
• Scientific Computing
• Mathematical Modeling
• +12 more

Patricio Farrell is an applied mathematician and Research Group Leader at the Weierstrass Institute Berlin (WIAS), focusing on numerical analysis, scientific computing, and mathematical modeling for semiconductor devices. His work bridges applied analysis and practical applications, particularly through structure-preserving numerical methods for drift-diffusion systems and nonlinear PDEs. Key applications include next-generation semiconductors, perovskite photovoltaics, and neuromorphic computing. He actively collaborates with institutions like Inria Lille, the University of Oxford, and the Helmholtz Zentrum Berlin. Vice Chair of KOMSO (Committee for Mathematical Modeling, Simulation and Optimization) Editor of Open Mathematics Scientific Ambassador for Brain City Berlin Developed ChargeTransport.jl , an open-source Julia tool for semiconductor simulations used in academia and industry His research interests span numerical analysis, nonlinear PDEs, finite volume methods, and meshfree techniques, with applications in perovskites, nanowires, memristors, quantum wells, and laser design. He has secured ~€1.5M in third-party funding from organizations like the Leibniz Association and MATH+. Scientific Awards: Capital's Top 40 under 40

Jian-Guo LiuView profile

Professor

• Applied Mathematics
• Partial Differential Equations
• Kinetic Theory
• +7 more

Jian-Guo Liu is a Professor of Mathematics and Physics at Duke University, with primary affiliations in the Departments of Mathematics and Physics. His research encompasses applied mathematics, partial differential equations, kinetic theory, computational fluid dynamics, and stochastic algorithms. Professor Liu's work bridges theoretical modeling and numerical methods, particularly in complex systems involving nonlinear dynamics, fluid behavior, and emergent phenomena. Research interests focus on multiscale modeling of physical systems, including stochastic processes in chemical reactions, fluid-structure interactions, and materials science. Recent publications demonstrate strong emphasis on mathematical foundations of biological and physical systems, with recurring themes in Fokker-Planck dynamics, mean-field games, tumor growth modeling, and computational methods for interfacial phenomena. Publications showcase consistent focus on analytical and numerical solutions to high-dimensional problems, with applications ranging from medical imaging to electrochemistry. The work exhibits advanced techniques in asymptotic analysis, stochastic approximations, and geometric evolution equations.