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Daniele CappellettiView profile

Associate Professor

• Stochastic Processes
• Probability Theory
• Mathematical Biology
• +7 more

Daniele Cappelletti is an Associate Professor in the Department of Mathematical Sciences (DISMA) at the Politecnico di Torino, where he conducts research in stochastic modeling of biochemical reaction networks. He holds a PhD from the University of Copenhagen and has held postdoctoral positions at ETH Zurich, University of Wisconsin-Madison, and the University of Copenhagen. He is affiliated with the 'Probability and Applications' research group and leads the ConStRAINeD project funded by the Italian PRIN program. PhD in Probability, University of Copenhagen (2012–2015) M.S. in Mathematics, Pisa University (2009–2012) B.S. in Mathematics, Pisa University (2005–2009) His research focuses on stochastic processes, probability theory, and mathematical biology, particularly in the modeling and analysis of chemical reaction networks. He investigates the long-term behavior, stability, and model reduction in both deterministic and stochastic frameworks, with applications in systems biology and synthetic biology. His work bridges theoretical mathematics with practical biological systems, especially those exhibiting absolute concentration robustness. The trend in his recent publications shows a strong emphasis on the mathematical foundations of stochastic reaction networks, including tier structures, non-explosivity, and approximation techniques. He has also extended his work into computational applications such as using chemical networks to approximate probability distributions and analyzing security in blockchain protocols, demonstrating interdisciplinary reach across mathematics, biology, and computer science. Daniele Cappelletti currently supervises PhD student Giulio Cuniberti in the Mathematical Sciences program at Politecnico di Torino. He has been involved in competitive research grants, most notably as Scientific Manager of the ConStRAINeD project (2023–2026), which aims to advance the convergence and stability theory of reaction network dynamics. He has not received any explicitly mentioned scientific awards in the provided text. He is actively involved in teaching across multiple programs, including Mathematical Engineering, Data Science and Engineering, and Management Engineering. He teaches courses on stochastic processes, statistics, and time series analysis, both as course instructor and collaborator. He is a member of the Doctoral College in Mathematical Sciences and participates in the College of Management and Production Engineering and the College of Mathematical Engineering.

Salvatore Ivan TrapassoView profile

Assistant Professor

• Applied harmonic analysis
• Fourier analysis
• Machine learning
• +5 more

Salvatore Ivan Trapasso is a Fixed-term Assistant Professor at the Department of Mathematical Sciences "GL Lagrange" (DISMA) , Polytechnic University of Turin , and a member of the SmartData@PoliTO - Big Data and Data Science Laboratory . His research focuses on Applied Harmonic Analysis , Fourier Analysis , Machine Learning , and Quantum Theory , with expertise in Mathematical Analysis (MATH-03/A) and Theoretical PDEs (PE1_11). Education : Implied PhD in Mathematics. Research Areas : Phase Space Analysis, Time-Frequency Methods, and Applications to Quantum Mechanics. His recent publications investigate phase space techniques for Feynman Path Integrals , Twisted Laplacian , Compressed Sensing , and Stability of Scattering Transforms . His work bridges Harmonic Analysis with Machine Learning and Quantum Dynamics . Notable scientific awards include the Axioms Young Investigator Award (2022) , Best Paper Award (ICGF 2020) , and the Quality Award 2019 from Polytechnic University of Turin. He serves on the Editorial Board of Advances in Operator Theory and as Associate Editor for University Texts in the Mathematical Sciences . Teaching roles include Lecturer for Mathematical Principles in the College of Architecture and Design , Collaborator for Mathematical Analysis I/II in Biomedical and Aerospace Engineering, and Contributor to advanced mathematical methods in Computer Science Engineering.

Robert JacksonView profile

Professor

• Tribology
• Friction
• Wear
• +11 more

Robert Jackson is the Albert Smith Jr. Professor in the Department of Mechanical Engineering at Auburn University’s Samuel Ginn College of Engineering. He holds a Ph.D., M.S., and B.S. in Mechanical Engineering from the Georgia Institute of Technology and is a leading researcher in tribology, contact mechanics, friction, wear, and lubrication. He serves as Editor-in-Chief of the ASME Journal of Tribology and leads a research group focused on multiscale modeling, electrical contact reliability, and sustainable biolubricants. His research interests include: tribology, friction, wear, surface engineering, surface fatigue, lubrication, nano-lubricants, surface texturing, and multiphysics modeling. He applies these to challenges in electric vehicles, aerospace systems, and biomedical devices. His work integrates experimental validation with finite element and statistical modeling to understand contact behavior across scales. His recent publications focus on electrical erosion in EV bearings, nanoparticle-enhanced greases, mixed lubrication models, and biolubricants from waste oil. These works reflect a strong trend toward sustainable engineering, advanced materials, and predictive modeling in mechanical systems. His interdisciplinary approach bridges mechanical, materials, and electrical engineering. ASME Fellow Fellow, Society of Tribologists and Lubrication Engineers (STLE) Ralph Beard Memorial Academic Award Editor-in-Chief, ASME Journal of Tribology Dr. Jackson advises graduate students such as Jack Janik and collaborates with researchers on projects involving electrical connectors, solenoid valves, and biolubricant development. His lab engages in both fundamental contact mechanics and applied industrial problems. He leads the tribology minor and student sections of ASME and STLE at Auburn.

Silvia Salinas BlemkerView profile

Professor

• Biomechanics
• Musculoskeletal Diseases
• Multi-scale Modeling
• +5 more

Dr. Silvia Salinas Blemker is a Professor of Biomedical Engineering at the University of Virginia, with a courtesy appointment in Mechanical and Aerospace Engineering. Her research focuses on understanding muscle structure-function relationships through computational and experimental models to develop treatments for musculoskeletal diseases. She earned her undergraduate and Master’s degrees in Biomedical Engineering from Northwestern University and a PhD in Mechanical Engineering from Stanford University. Her Multiscale Muscle Mechanophysiology (M3) Lab investigates skeletal muscle mechanics, regeneration, and disease mechanisms, particularly in conditions like muscular dystrophy and aging. The lab’s work integrates AI-driven MRI analysis, finite element modeling, and clinical collaborations to improve patient outcomes. Key projects include developing the FDA-approved Springbok Analytics tool for muscle health assessment and advancing understanding of muscle regeneration through agent-based modeling. Dr. Blemker has received prestigious awards such as the National Academy of Inventors Fellowship (2024) and the American Society of Biomechanics’ Goel Award (2024). She teaches courses in biomechanics and motion analysis. Her research has been featured in innovations like biomechanics-based injury prevention systems for athletes and novel imaging techniques for neuromuscular disease monitoring.

Mool C. GuptaView profile

Professor

• Photonics
• Photovoltaics
• Nanomaterials
• +4 more

Mool C. Gupta is the Langley Distinguished Professor and Founding Director of the NSF Industry/University Cooperative Research Center for Lasers and Plasmas at the University of Virginia. He holds affiliations with the Department of Electrical and Computer Engineering within the School of Engineering and Applied Science. Previously, he served as Director of the Applied Research Center at Old Dominion University and worked at Eastman Kodak Company and NASA's Jet Propulsion Laboratory. His academic roles include Adjunct Professor at Cornell University and Editor-in-Chief of the Handbook of Photonics . Education: Senior Research Fellow, California Institute of Technology (1978–1979) Postdoctoral Fellow, Cornell University (1976–1978) Ph.D. in Physics, Washington State University (1973) Research Interests: His work focuses on photon processing of materials, photovoltaics, nanomaterials, and optoelectronic devices. Key areas include laser processing for solar cell optimization, anti-icing surface technologies, and advanced materials characterization. His research bridges fundamental materials science with practical applications in energy and aerospace. Publications & Trends: Gupta's recent work emphasizes laser-based manufacturing, thermoelectric materials, and photovoltaic innovations. His 2023 study on silicon solar cell passivation and 2020 research on anti-icing surfaces highlight his dual focus on energy and materials engineering. He frequently publishes in journals like Applied Physics , Journal of Alloys and Compounds , and IEEE Transactions . Awards: Member of Kodak's Inventors' Gallery Fellow of the National Academy of Inventors Grants & Advising: Past PI for NSF, DARPA, AFOSR, and NASA projects. Courses taught include Photovoltaics and Electrical Engineering Projects . His lab collaborates on solar-land coexistence solutions and advanced materials for energy systems. Labs & Teams: Directs the NSF Center for Lasers and Plasmas, leveraging interdisciplinary teams for laser-materials innovation. His lab focuses on photonics, nanotechnology, and sustainable energy solutions.

Alfredo BensoView profile

Professor

• Bioinformatics
• Systems Biology
• Artificial Intelligence
• +16 more

Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.

• Mechanobiology
• Computational Mechanics
• Soft Matter Physics
• +7 more

Marino Arroyo is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Research Center in Numerical Methods in Applied Science and Engineering (LaCàN). He is also associated with CIMNE and the Institute of Bioengineering of Catalunya (IBEC). His work focuses on computational and theoretical modeling of biological systems, particularly epithelial mechanics, active matter, and biomembranes. He holds the Icrea Academia Award, recognizing his contributions to mechanobiology and soft matter physics. Education: PhD in Mechanical Engineering, Northwestern University (2003) BS/MS in Civil Engineering, UPC Postdoc at Caltech with Michael Ortiz (2003-2004) Research Interests: Combines mathematical modeling, mechanics, and computations to study small-scale material behavior and biological systems. Current focus includes cell/tissue mechanobiology, active living materials, and bio-inspired materials. Key themes are nonlinear mechanics of 2D materials (graphene, biomembranes), continuum mechanics, and molecular-to-continuum modeling. Recent Article Trends: Focuses on multiscale epithelial mechanics, active gels, hydraulic fracture in biological systems, and mechanochemical feedback in cellular membranes. Recent work includes modeling curved epithelial shells, nematic patterns in cytoskeletal layers, and shape-programmable living surfaces. Scientific Awards: Icrea Academia Awardee Advising & Grants: Supervised over 20 PhD students, many of whom hold prestigious postdocs or academic positions. Collaborates with experimental groups (e.g., Xavier Trepat, Danijela Vignjevic). Current projects include NIH-funded studies on epithelial mechanics and ERC grants for computational modeling. Labs/Teams: Leads LaCàN's biomaterials group, integrating computational mechanics with experimental biology. Active in interdisciplinary collaborations across UPC, IBEC, and international institutions.

Felix SchindlerView profile

Researcher

• Numerical Analysis
• Machine Learning
• Scientific Computing
• +3 more

Felix Schindler is a Researcher at the Institute for Analysis and Numerical Analysis , part of the Department of Mathematics and Computer Science at the University of Münster . His work bridges numerical analysis, machine learning, and scientific computing, with a focus on model reduction for partial differential equations (PDEs), adaptive algorithms, and computational efficiency. Research Interests include: Numerical analysis of parametric and multiscale PDEs Localized reduced basis methods (LRBM) and adaptive enrichment Integration of model order reduction (MOR) with machine learning (ML) Conservative flux reconstruction techniques Development of software libraries like dune-xt and pyMOR Recent Publications highlight trends in applying deep kernel models for surrogate modeling, localized training strategies for PDE-constrained optimization, and hybrid full/reduced-order pipelines for reactive flow prediction. His work emphasizes certified error control, hierarchical adaptivity, and cross-disciplinary computational frameworks. Collaborations span institutions such as AIMS Senegal, Springer Nature, and DUNE project teams. He actively contributes to conferences like GAMM, ENUMATH, and Algoritmy.

Justin MeyerView profile

Professor

• Evolutionary Biology
• Microbial Ecology
• Viral Evolution
• +7 more

Justin Meyer is a Professor and Vice Chair in the Department of Ecology, Behavior & Evolution at the University of California San Diego (UCSD), where he leads the Meyer Lab focused on experimental microbial ecology and evolution. His research bridges theoretical evolutionary biology with practical applications in phage therapy and synthetic biology, using bacteriophage lambda as a key model system. Dr. Meyer received his Ph.D. from Michigan State University and was a Systems Biology Departmental Fellow at Harvard Medical School, where he was awarded the James S. McDonnell Foundation Fellowship for Studying Complex Systems. He joined the UCSD faculty in 2014, establishing his research program at the intersection of evolutionary theory and microbial systems. Meyer's research spans several interconnected areas in evolutionary biology. His lab investigates fundamental questions about speciation, novelty, evolvability, and complexity using microbial experimental systems. Through innovative approaches combining trackable microbial platforms and synthetic biology, his team generates new datasets to test evolutionary and ecological theories that were previously untestable. A key focus is understanding how bacteriophage λ evolves to exploit alternative receptors, providing critical insights into host-pathogen interactions and the mechanisms of evolutionary innovation. Analysis of Meyer's recent publications (2021-2024) reveals a strong emphasis on the molecular mechanisms of viral evolution, particularly how protein instability and phenotypic heterogeneity drive host-range expansion. His work increasingly integrates theoretical models with experimental approaches to understand fitness landscape deformations during coevolution. The research has significant implications for developing more robust phage therapeutics through "evolutionary training" protocols that pre-evolve bacteriophages to counter bacterial resistance. Scientific recognition includes: James S. McDonnell Foundation Fellowship for Studying Complex Systems Systems Biology Departmental Fellowship at Harvard Medical School Meyer actively mentors the next generation of scientists through his lab at UCSD. His team includes postdoctoral researchers, PhD students, and undergraduate researchers working collaboratively on projects spanning from basic evolutionary questions to applied phage therapy development. His lab has secured funding supporting research on coevolutionary dynamics, viral speciation, and the development of synthetic phage platforms for removing antibiotic resistance genes from microbiomes. The Meyer Lab operates from the Muir Biology Building at UCSD, maintaining active collaborations with researchers across disciplines including synthetic biology, microbiology, and medical researchers developing novel antimicrobial therapies. The lab's work on "evolutionary training" of bacteriophages and gene drive technologies represents a unique integration of theoretical evolutionary biology with practical therapeutic applications.

Dirk PeschkaView profile

Researcher

• Partial Differential Equations
• Fluid Dynamics
• Materials Science
• +7 more

Dr. Dirk Peschka is a researcher at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, Germany, where he contributes to the Partial Differential Equations Research Group (FG1) . He is affiliated with the Berlin Mathematics Research Center MATH+ , the Society for Applied Mathematics and Mechanics (GAMM) , and the German Physical Society (DPG) . Research Interests Mathematical modeling of fluid dynamics and materials science using partial differential equations (PDEs). Applications in thin film dynamics, semiconductor devices, and reactive multiphase flows. Development of gradient flow frameworks and thermomechanical models via GENERIC formalism. Analysis of contact line behavior, dewetting processes, and fluid-structure interaction. Numerical methods for semiconductor simulations and geoscience applications. Publications Trends His recent work (2022–2025) emphasizes energy-based modeling of thin films, reactive flows, and semiconductor degradation. Key themes include contact line dynamics, gradient flows, and multiscale analysis of materials and fluid systems. Memberships Weierstrass Institute for Applied Analysis and Stochastics (WIAS) Berlin Mathematics Research Center MATH+ Society for Applied Mathematics and Mechanics (GAMM) German Physical Society (DPG)

Christopher BrunsdonView profile

Professor

• Spatial Statistics
• Data Science
• Spatial Analysis
• +3 more

Christopher Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation at Maynooth University's Faculty of Social Sciences. Previously, he held positions at the University of Liverpool, Leicester, Glamorgan, and Newcastle. His academic credentials include a BSc in Mathematics from Durham University and an MSc in Medical Statistics and PhD in Geography from Newcastle University. Research interests focus on spatial statistics, data science, and spatial analysis, with emphasis on open-source software (especially R) and reproducible methods. Applied domains include crime pattern analysis, health geography, and environmental applications. Current projects include 'Mapping Lineages: Quantifying the Evolution of Maps of the British Isles' and 'Building city dashboards'. Brunsdon's recent publications (2018-2020) demonstrate strong methodological contributions to geocomputation, spatial regression, and geodemographics. Trends include reproducibility in spatial science, multiscale modeling, and applications in health geography and urban analytics. He leads the National Centre for Geocomputation, fostering innovation in spatial data science. Grant leadership includes an ERC Advanced Grant (RIGAR) and industry collaborations like consultancy for SiteZeus.

Sergey KarabasovView profile

Professor

• Computational Fluid Dynamics
• Aeroacoustics
• Aerodynamics
• +5 more

Professor Sergey Karabasov is a leading academic in computational modeling and aeroacoustics at Queen Mary University of London’s School of Engineering and Materials Science . As Director of the Centre for Intelligent Transport , he bridges aerospace engineering with environmental technology and bioengineering. Education: PhD (1999, Moscow State University), DSc (2010, Keldysh Institute) Affiliations: Fellow of the Royal Aeronautical Society (FRAeS), Fellow of the Higher Education Academy (FHEA), Associate Fellow of AIAA (AFAIAA) Research Interests span multiscale fluid dynamics, computational aeroacoustics, and high-performance computing. His work addresses: Future Mobility: Noise reduction in urban air mobility and conventional aircraft Environmental Technologies: Turbulence modeling for renewable energy and climate systems Digital Twins: Physics-based and data-driven simulations for aerospace and bioengineering Article Trends focus on: Hybrid LES-acoustic models for jet noise Multiscale methods in nanofluidics and molecular systems GPU-accelerated algorithms (e.g., CABARET) for complex flows Climate dynamics (Southern Ocean jets, Chandler wobble) Scientific Awards include: Fellowships at Royal Aeronautical Society and Higher Education Academy Associate Fellowship at AIAA Guest Editor for Royal Society Phil.Trans. A theme issues (2014, 2019) Advising includes current PhD student Hussain Ali Abid and alumni working on: Jet noise optimization Graphene suspension rheology Hybrid molecular-continuum simulations Labs & Teams involve the Centre for Intelligent Transport , GPU-Prime.Ltd consultancy, and collaborations with institutions like Cambridge University and Keldysh Institute.

Wanqing ShenView profile

Associate Professor

• Mechanics of Materials
• Civil Engineering
• Micromechanics
• +7 more

Wanqing Shen is an active Associate Professor (Maître de Conférences-HDR) at the Polytechnic School of Lille, University of Lille, specializing in Civil Engineering within the Department of Civil Engineering. They hold an accreditation to supervise research (HDR) and are affiliated with UMR 9013 - Laboratory of Multiphysics Multiscale Mechanics. 2018: Habilitation à diriger des recherches (HDR), "Nonlinear behavior of heterogeneous porous materials", University of Lille 2011: Ph.D., "Micro-macro modeling of mechanical behavior for ductile porous materials: application to the Callovo-Oxfordian argillite", University of Lille 2008: Master in Civil Engineering, University of Lille Professor Shen's research focuses on the mechanical behavior of heterogeneous porous materials, with expertise in micromechanics, multiscale modeling, and Thermo-Hydro-Chemo-Mechanical coupling in geomaterials. Their work bridges theoretical mechanics with practical civil engineering applications, particularly in understanding rock and soil behavior through advanced numerical methods and constitutive modeling. The research has significant implications for underground engineering and geological material analysis. Shen serves as Associate Editor for "AI & Materials" and as Academic Editor for "Deep Underground Science and Engineering", while also contributing to the editorial boards of "Rock Mechanics Bulletin" and the Early Career Editorial Board of "Deep Underground Science and Engineering". These roles reflect their standing in the mechanics and civil engineering research community. Prize of Excellent Scientific Research and Supervision (2021) Prize of Excellent Scientific Research and Supervision (2017) Chinese Government Award For Outstanding Self-Financed Students Abroad (2011) Allocations de Recherche du Ministère de l'Enseignement Supérieur et de la Recherche (2008) As an educator, Shen has served as Pedagogical Head and Head of Engineer Project for GC5 since 2020, and previously for GC3 (2015-2019). They teach advanced courses including Micromechanics (Master 2), Constitutive Laws (Master 1), and various engineering mechanics courses. From 2020-2022, they co-led the GEOM research group (Multiphysics Couplings and Multiscale Approaches in Geomaterials) within LaMcube, demonstrating active leadership in their research community.

Federico Javier HernándezView profile

Lecturer

• Computational Chemistry
• Photochemistry
• Photophysics
• +5 more

Dr. Federico Javier Hernández serves as a Lecturer in Computational Chemistry at the Centre for Chemical Research within the School of Physical and Chemical Sciences at Queen Mary University of London. His expertise centers on computational photochemistry and photophysics, with emphasis on excited-state mechanisms in complex molecular environments including aggregates, organic crystals, and solution-phase systems. Hernández completed his undergraduate studies in Physical Chemistry at the University of Córdoba (UC), Argentina, followed by a hybrid experimental and theoretical-computational PhD in Chemistry jointly awarded by UC and the University of Quilmes under Professors Gustavo Pino and Juliana Palma. His doctoral research investigated photophysical and photochemical processes relevant to Atmospheric Chemistry and Biochemistry. His laboratory focuses on elucidating fundamental mechanisms behind phenomena such as aggregation-induced emission, radiative quenching, singlet fission, ultralong organic phosphorescence, charge/exciton transport, and thermally activated delayed fluorescence. These investigations employ advanced computational methodologies including plane-wave DFT, multiscale electronic structure methods (QM:QM' and QM:MM), nonadiabatic dynamics simulations (surface hopping and Ehrenfest dynamics), and machine learning integration for materials discovery. This work directly supports rational design of functional molecules for optoelectronic applications and energy storage/conversion technologies. Analysis of Hernández's 15 most recent publications (2022-2025) reveals consistent focus on nonadiabatic dynamics in condensed phases, excited-state mechanisms in molecular aggregates, and atmospheric reaction kinetics. Key trends include development of computational benchmarks for photochemical processes, application of machine learning to photodynamics, and investigation of polaritonic effects in vibrational spectroscopy. His work bridges theoretical chemistry with practical materials design for optoelectronics. No major scientific awards or fellowships are documented in the available information. While current PhD advisees are not listed, Hernández maintains an active research group within the Centre for Chemical Research. His collaborative network spans international institutions including University College London, University of Bristol, and University of Santiago de Chile. He contributes to academic instruction through CHE 209 – Introductory Programming for Chemists and leverages his ORCID profile (https://orcid.org/0000-0001-7497-9424) for scholarly identification. His research infrastructure integrates high-performance computing with data science approaches to tackle complex photochemical problems.

• Biomedical Imaging
• Developmental Biology
• Optical Microscopy
• +5 more

Jan Huisken is a Professor at the University of Göttingen, Germany, holding the Alexander von Humboldt Professorship since October 2021. He remains an affiliate of the Morgridge Institute for Research in Madison, Wisconsin, where he served as Director of Morgridge Medical Engineering since 2016. Previously, he was a Visiting Professor in the Department of Integrative Biology (2010-2017) and a Research Group Leader at the Max Planck Institute of Molecular Cell Biology and Genetics (2005-2009). His educational background includes: PhD in Physics, University of Freiburg (conducted at EMBL-Heidelberg) Postdoctoral work at EMBL-Heidelberg (2000-2004) Postdoctoral work at UCSF (2004-2005) Dr. Huisken's research focuses on developing noninvasive biomedical imaging techniques, particularly optical microscopy, to study developmental processes in living organisms. His lab specializes in organogenesis in zebrafish, with emphasis on the cardiovascular system and endoderm. He pioneers quantitative microscopy tools including selective plane illumination microscopy (SPIM) and high-speed fluorescence microscopy to capture cellular dynamics during organ formation. His publication portfolio reveals a dominant trend in advancing light-sheet microscopy for multiscale embryonic imaging, with recurring applications in cardiovascular dynamics, endoderm formation, and vascular growth. This work consistently bridges physics and biology, creating custom microscopes that solve fundamental biological problems through interdisciplinary collaboration. His notable scientific achievement is: Alexander von Humboldt Professorship Dr. Huisken leads an interdisciplinary laboratory where biologists and physicists jointly develop cutting-edge microscopy instrumentation and immediately apply it to biological discovery. The lab operates across the full experimental spectrum from transgenic model systems and optical engineering to computational image analysis, fostering a unique environment where technological innovation directly drives biological insight.