جست‌وجوی استاد و پژوهشگر

• Metal Ion Chemistry
• Density Functional Theory
• Computational Chemistry
• +۵ مورد دیگر

Luis Aurelio Rodriguez Santiago is an Associate Professor in the Department of Chemistry at Universitat Autònoma de Barcelona, leading research in computational chemistry, nanocatalysis, and bioinorganic systems. He directs the Computational BioNanoCat research group and serves as Co-Principal Investigator on multiple significant research projects including computational design of electrocatalysts for sustainable nitrogen and NOx reductions, and green valorization of CO 2 and nitrogen compounds. His educational background includes a Ph.D. in Chemistry from Universitat Autònoma de Barcelona (1998) and a Chemistry degree from Universitat de Barcelona (1992). Prior to his current position, he held prestigious roles including Ramón y Cajal Researcher at UAB and Marie Curie Postdoctoral Fellow at Université d'Evry-Val-d'Essonne. Dr. Rodriguez Santiago's research focuses on computational modeling of metal-ion systems, particularly Cu(I) and Cu(II) chemistry, density functional theory applications, supramolecular metallopeptide assemblies, and nanocatalysis. His work bridges computational chemistry with experimental validation, producing significant contributions in electrocatalysis, amyloid fiber catalysis, and luminescent materials. The fingerprint analysis of his work shows strong emphasis on metal ion chemistry (97%), density functional theory (91%), and Cu-based systems (85%). His recent publications (2023-2025) demonstrate a clear trajectory toward sustainable chemistry applications, with emphasis on electrocatalysis for hydrogen production, computational design of catalysts for nitrogen cycle management, and bioinspired catalytic systems. These works frequently appear in high-impact journals like Inorganic Chemistry Frontiers, Chemistry - A European Journal, and Nanoscale Horizons. Dr. Rodriguez Santiago currently leads or participates in multiple significant research projects: COMPUTATIONAL DESIGN OF ELECTROCATALYSTS FOR SUSTAINABLE N2 AND NOX- REDUCTIONS (2024-2027) as Co-Principal Investigator CONFETI: Green Valorization of CO2 and Nitrogen compounds (2023-2026) as Investigator NANOCATALISIS COMPUTACIONAL (2021-2024) as Co-Principal Investigator Computational modeling of nanoparticles (2018-2021) as Investigator Atomistic perspective on beta-amyloid detection (2015-2017) as Co-Principal Investigator His research group Computational BioNanoCat specializes in applying computational methods to understand and design nanoscale catalytic systems, with particular expertise in metal-ion chemistry, peptide-based materials, and sustainable energy applications. The group maintains strong collaborations with international researchers and has produced over 80 research outputs and 6 datasets, primarily focusing on crystal structure determinations.

Niels Volkmannمشاهده پروفایل

استاد

• Bioengineering
• Computational Science and Engineering
• Structural Biology
• +۳ مورد دیگر

Niels Volkmann is a Professor affiliated with the Bioengineering and Electrical and Computer Engineering departments at the University of California, Santa Barbara. His research focuses on developing computational tools and cryo-microscopy techniques to bridge atomic and cellular scales, analyzing data from electron cryo-microscopy and cellular cryo-tomography. He aims to create three-dimensional mappings of cellular proteomes and study molecular interactions at near-atomic resolution in cryogenically preserved cells. Volkmann holds a PhD from the Max Planck Institute in Hamburg and a BS from the University of Hamburg. His work integrates artificial intelligence, data science, and correlative microscopy methods to advance structural biology and systems biology. Key research areas include protein structure elucidation, cell signaling complexes, and the interplay between matrix stiffness and cellular behavior. His publications highlight advancements in cryoEM workflow optimization, FAIR data stewardship, and the development of tools like Feret signatures and GoldX fiducial eraser. While no specific awards are listed, his contributions to computational methods and cryo-microscopy workflows have likely impacted structural biology research globally. Volkmann’s research also explores nanodisc applications, viral entry mechanisms (e.g., SARS-CoV-2), and the architectural basis of cellular components like the actomyosin interface and αE-catenin. His work emphasizes interdisciplinary approaches, combining bioengineering with computational and electrical engineering advancements.

Karl Duderstadtمشاهده پروفایل

استاد

• Biophysics
• Molecular Biology
• Structural Biology
• +۳ مورد دیگر

Prof. Dr. Karl Duderstadt is a Professor of Experimental Biophysics at the Technical University of Munich (TUM) and a group leader at the Max Planck Institute of Biochemistry. His research focuses on understanding the dynamic processes of chromosome duplication using single-molecule imaging techniques. He holds a B.A. in Physics from Oberlin College and a Ph.D. in Biophysics from UC Berkeley. Prior to his current roles, he conducted postdoctoral research at the University of Groningen under the Human Frontier Science Program. His academic career includes leadership of the Max Planck Research Group "Structure and Dynamics of Molecular Machines" since 2016. Key research areas include replisome dynamics, DNA replication stress, and the interplay between replication and transcription. He has received prestigious awards, including an ERC Starting Grant (2019) and an HFSP fellowship (2012–2015). Publications highlight advancements in single-molecule technologies, such as the Mars data analysis suite, and discoveries about replication fork protection mechanisms. His work bridges biophysics, structural biology, and molecular genetics, with applications to cellular and epigenetic stability.

Christopher Rowlandsمشاهده پروفایل

دانشیار

• Optical Physics
• Physical Chemistry
• Materials Engineering
• +۸ مورد دیگر

Dr. Christopher Rowlands is an Associate Professor in the Department of Bioengineering at Imperial College London, part of the Faculty of Engineering. His research focuses on biophotonic instrumentation, including advanced optical systems for imaging, algorithm development, and open-source software engineering. He holds affiliations with the Artificial Intelligence Network, CRUK Convergence Science Centre, and the Rowlands Lab. Education: BSc Chemistry at Imperial College London, PhD in Physics/Chemistry of Amorphous Materials at the University of Cambridge. Career highlights include postdoctoral work at the University of Nottingham, MIT, and Cambridge before joining Imperial College in 2017. Research interests span optical physics, physical chemistry, materials engineering, and neurotechnology. His lab develops novel microscopes (e.g., temporal focusing, multiphoton, SWIR) and algorithms for hyperspectral imaging, particle tracking, and source separation. The Rowlands Lab emphasizes interdisciplinary projects in microfluidics, super-resolution imaging, and biomedical applications. Currently supervises research projects in optical instrumentation, bioreactor monitoring, and automated microfluidic synthesis. The lab actively recruits students and postdocs for funded positions in bioengineering and photonics. Notable projects include the Rowlands Lab’s work on selective high-throughput STORM, high-speed 3D SIM, and SWIR imaging for deep-tissue applications. The lab’s open-source software and instrumentation designs are publicly accessible.

• Laser Physics
• Optical Systems Design
• Biomedical Optics
• +۳ مورد دیگر

Pál Andor Maák is an Associate Professor at the Department of Atomic Physics, Budapest University of Technology and Economics (BME). His research focuses on acousto-optic devices, laser systems, and biomedical applications of optical technologies. Key areas include the design of femtosecond lasers, nonlinear microscopy, and advanced imaging techniques for biological tissues. He leads the Physics Laboratory III and the Applied Physics Lab, specializing in confocal and two-photon microscopy systems. His work emphasizes interdisciplinary applications, such as acousto-optic deflectors for high-resolution imaging and thermal analysis of optical components. Notable contributions include patents on 3D sample measurement systems and multi-region microscopy. He has supervised numerous diploma theses and doctoral dissertations, fostering innovation in laser technology and material science. Education : Advanced training in laser physics and optical engineering. Labs : Physics Laboratory III, Applied Physics Lab. Grants/Projects : Ongoing research in acousto-optic device optimization and biomedical imaging applications. Publications span journals like Optics Express , Nature Methods , and Applied Optics , with a focus on experimental and theoretical advancements in photonics and optical systems.

• Organic Chemistry
• Biochemistry
• Molecular Biology
• +۷ مورد دیگر

Ivo Piantanida is a Full Professor at the University of Rijeka (Division of Biotechnology) and Head of the Laboratory for Biomolecular Interactions and Spectroscopy at the Ruđer Bošković Institute. He holds dual roles as a researcher and educator, leading projects in organic chemistry, molecular sensing, and drug design. His academic career includes positions as a PhD supervisor and lecturer in Molecular Biosciences at the University of Osijek. Dr. Piantanida's research focuses on the design and synthesis of small molecules targeting DNA/RNA interactions, with emphasis on multichromophore probes for structural recognition, antimicrobial agents , and photodynamic therapy . His work integrates organic chemistry with supramolecular chemistry, biophysics, and medicinal applications. Key achievements include the development of novel DNA/RNA sensors, such as triarylborane dyes and cyanine-peptide conjugates . He has led major grants, including a Horizon 2020 project (MARILIA) and Croatian Science Foundation initiatives, totaling over €5M in funding. His lab pioneered methods for mycotoxin detection and enzyme inhibition studies . Notable awards include the 2020 Croatian Academy of Sciences Award for outstanding contributions in chemistry, recognizing his work on molecular probes and antitumor agents. Over 200 peer-reviewed publications and 6 PhD/10 MSc supervised students underscore his impactful research.

Constantin Papeمشاهده پروفایل

استادیار

• Deep Learning
• Computer Vision
• Biomedical Imaging
• +۴ مورد دیگر

Constantin Pape is a Junior Professor at Georg-August University Göttingen in the Institute of Computer Science, where he leads the Computational Cell Analytics research group since March 2022. His work focuses on developing deep learning and AI methods for biology and medicine, with particular emphasis on biomedical imaging applications. His research spans two main areas: building foundation models for biology and medicine, and protein structure analysis in cryogenic electron microscopy and super-resolution microscopy. Dr. Pape's group is dedicated to open source and open science, contributing to projects like the bioimage.io modelzoo, ome.ngff image data format, and MoBIE Fiji plugin. His research is funded by the DFG through a Sachbeihilfe, the SFB1286 on Quantitative Synaptology, and the Multiscale Bioimaging Cluster of Excellence (MBExC). Dr. Pape's work on foundation models includes Segment Anything for Microscopy (Nature Methods, 2025) and extensions to histopathology and medical imaging. His group develops segmentation models for various applications, including SynapseNet for automatic synapse reconstruction. He has published extensively in top venues including Nature Methods, Cell, Science, and ECCV. His teaching includes a lecture on Deep Learning for Computer Vision and seminars on Deep Learning in Biology and Medicine at the University of Göttingen, as well as co-organizing the Deep Learning for Image Analysis course at EMBL and teaching advanced image analysis through the Hertha Sponer College.

Aleks Ponjavicمشاهده پروفایل

استادیار

• Single-molecule fluorescence imaging
• Light-sheet microscopy
• Super-resolution microscopy
• +۷ مورد دیگر

Dr. Aleks Ponjavic is a University Academic Fellow at the University of Leeds, affiliated with the Faculty of Engineering and Physical Sciences, specifically within the School of Physics and Astronomy and Food Science and Nutrition. His research is focused on developing and applying cutting-edge fluorescence microscopy techniques to study fundamental biological processes at the single-molecule level. His research interests lie at the intersection of physics, biology, and imaging technology. He specializes in single-molecule fluorescence imaging , light-sheet microscopy , and super-resolution microscopy , aiming to overcome the limitations of conventional optical imaging to observe protein behavior and cellular structures in unprecedented detail. His work addresses key biological questions such as immune cell recognition of pathogens and DNA conformational changes in gene regulation. The absence of listed publications in the provided text prevents a detailed analysis of article trends; however, based on his described research program, his work spans interdisciplinary domains in biophysics, bioimaging, and nanoscale cellular analysis. His technological focus suggests strong contributions to methodological advancements in microscopy. While no scientific awards are listed in the provided information, his position as a University Academic Fellow indicates recognition of research potential and early-career excellence. Aleks Ponjavic leads an active research group focused on improving imaging tools to visualize complex cellular processes under more physiological conditions. Although specific grants or funding sources are not mentioned, his research program implies involvement in competitive research projects. He mentors students and researchers in advanced microscopy and cellular biophysics, contributing to training the next generation of interdisciplinary scientists. His laboratory work centers on implementing innovative light-sheet and super-resolution techniques to enable single-molecule studies inside living cells, moving beyond traditional glass-liquid interfaces. This approach supports more realistic and biologically relevant observations of protein dynamics and 3D organization within cellular environments.

Richard Hailstoneمشاهده پروفایل

دانشیار

• Electron Microscopy
• Material Science
• Imaging Science
• +۳ مورد دیگر

Richard Hailstone is an Associate Professor at the Chester F. Carlson Center for Imaging Science within the College of Science at Rochester Institute of Technology (RIT). His work focuses on electron microscopy and materials characterization, with expertise in Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and Nuclear Magnetic Resonance Spectroscopy. Education: BS from Northern Illinois University, MS from Indiana University Research interests include improving scanning electron microscope resolution through point spread function determination and image restoration, alkali-activated materials for sustainable cement, and self-healing thermoplastic blends. He collaborates with industry and academic partners such as Eric Lifshin (SUNY Polytechnic), Nathan Cahill (RIT), and Brian Landi (RIT), with recent publications on quantum dots, carbon dots, and SEM wave optics. He manages the NanoImaging Laboratory at RIT, which houses advanced equipment like Tescan Mira3 and Zeiss Supra 40 VP SEMs, JEOL TEMs, and software tools like Nanojehm's Aura system for PSF analysis. Students under his mentorship, including Surya Kamal and Kevin Mogere Nyaburi, contribute to projects on nanomaterials and imaging algorithms.

Kevin Eliceiriمشاهده پروفایل

استاد

• Biomedical Engineering
• Optical Imaging
• Computer Science
• +۶ مورد دیگر

Kevin Eliceiri is a Professor of Medical Physics and Biomedical Engineering at the University of Wisconsin–Madison, where he also serves as Director of the Center for Quantitative Cell Imaging. His primary affiliation is with the Department of Biomedical Engineering in the College of Engineering, with additional ties to the Wisconsin Institute for Discovery. Research Interests Development of optical imaging methods for cell signaling and cancer progression Software tools for multidimensional bioimage analysis (e.g., ImageJ/Fiji, PyImageJ, napari integration) Quantitative fluorescence lifetime imaging (FLIM) Label-free imaging techniques and polarization microscopy Tumor microenvironment characterization using collagen fiber analysis Machine learning in biomedical image processing Recent publications emphasize advancements in polychromatic polarization microscopy for pancreatic cancer diagnostics, collaborative bioimage analysis frameworks, and live tumor fragment platforms for immunotherapy assessment. His work bridges computational methods with clinical applications. Lab Affiliation Lead Investigator, Laboratory for Optical and Computational Instrumentation (LOCI) since 2000 Director, Center for Quantitative Cell Imaging

Serhii Kostrikovمشاهده پروفایل

استادیار

• Computational Auditory Modeling
• Drug Delivery Systems
• Neurodegeneration
• +۳ مورد دیگر

Serhii Kostrikov is an Assistant Professor at the Department of Health Technology at Technical University of Denmark . His research integrates computational auditory modeling with advanced bioimaging techniques to study neurological and oncological systems. Key collaborations include institutions like Karolinska Institute and Harvard Medical School . Research Focus Areas : Computational modeling of auditory nerve dynamics and cochlear pathology Development of targeted drug delivery systems for neurological and oncological applications 3D microscopy analysis of tumor microenvironment and vascular remodeling in neurodegeneration Publication Trends (2022–2025): 50% focus on neurodegenerative vascular changes , 33% on TLR-based immunotherapy , and 16% on computational auditory neuroscience . His work frequently addresses lipid membrane interactions and microenvironmental dynamics across disciplines. Professional Roles : PhD researcher (2017–2020) in Targeted Drug Delivery Systems for the Brain Peer reviewer for Cell Death and Disease and International Journal of Pharmaceutics Conference presenter at 3D Microscopy and Cochlear Pathology events

• Immunology
• Cellular Immunotherapy
• Medical Laboratory Technologies
• +۳ مورد دیگر

Björn Önfelt is a Visiting Professor in Molecular Immunology with a focus on Cellular Immunotherapy at the Department of Medicine, Huddinge, Karolinska Institutet. His research explores immune responses to human viral infections and cancer, particularly through the lens of natural killer (NK) cell dynamics and cytotoxicity. Specializes in NK cell migration and cytotoxic response Develops microchip-based imaging tools for single-cell analysis Investigates immune synapse formation and membrane nanotubes Contributes to hematopoietic stem cell transplantation research His work bridges immunology, bioengineering, and medical laboratory technologies, utilizing advanced imaging techniques like cryo x-ray microscopy and acoustofluidic platforms. Key findings include mechanisms of CD16 shedding in NK cells, DNAM-1/LFA-1 coordination in educated NK cells, and predictive biomarkers for graft outcomes in transplantation. Scientific awards and honors: None explicitly mentioned in the provided texts. He collaborates with the Hans-Gustaf Ljunggren group and contributes to interdisciplinary research combining immunology with microengineering. His lab employs acoustic trapping, microwell arrays, and fluorescence lifetime imaging to study immune cell behavior at high resolution.

David Hardmanمشاهده پروفایل

پژوهشگر ارشد

• Muscle Physiology
• Optogenetics
• Cell Biology
• +۳ مورد دیگر

David Hardman is a Research Fellow at the Centre for Medical Informatics within the Usher Institute, part of the College of Medicine and Veterinary Medicine at the University of Edinburgh. His work bridges biomedical engineering, computational biology, and muscle physiology to develop innovative quantitative approaches for cellular analysis. Hardman's research spans skeletal muscle physiology, optogenetics, and computational modeling. He employs agent-based simulations to optimize muscle cell culture conditions and develops quantitative techniques for measuring cell behavior and quality. His work integrates light-based control systems for precise muscle contractility assays and investigates molecular mechanisms in cancer progression, particularly in cutaneous squamous cell carcinoma. His publication trends reveal a focus on quantitative methodologies for muscle cell analysis, combining in vitro models with computational approaches. Key themes include optimizing muscle cell generation protocols, developing optogenetic contractility assays, and modeling oxygen transport in engineered muscle tissues using mathematical simulations. Hardman operates within the Centre for Medical Informatics at the Usher Institute, a hub for interdisciplinary health data science research. His work involves close collaboration with cell biologists, computational scientists, and clinicians to advance muscle-on-chip technologies and disease modeling.

• Neural Networks
• Information Processing
• Statistical Physics
• +۱۳ مورد دیگر

Viola Priesemann is a Professor of Physics at the University of Göttingen and heads the Max Planck Research Group on the Theory of Neural Systems at the Max Planck Institute for Dynamics and Self-Organization in Göttingen. She also holds affiliations with the Cluster of Excellence 'Multiscale Bioimaging', the Campus Institute for Data Science, and the Max Planck-University of Toronto Centre for Neural Science and Technology. Her research focuses on understanding the fundamental principles of collective information processing in both neural and social networks. She employs approaches from statistical physics and information theory to investigate self-organization and learning processes in living networks. Her work spans several interconnected areas: neural criticality and subsampling effects in network analysis, information processing in neural circuits, and the spread of information (and misinformation) in social networks. During the COVID-19 pandemic, she applied her expertise in spreading dynamics to study viral transmission and the effectiveness of interventions, becoming a member of the German government's expert panel on the pandemic. Her recent publications reveal a strong focus on understanding how neural networks maintain optimal information processing through controlled criticality, how subsampling affects our ability to infer network properties, and the parallels between information spread in neural and social networks. Her work bridges theoretical physics, computational neuroscience, and epidemiology, demonstrating how principles from statistical physics can illuminate collective phenomena across vastly different scales. Medal for Scientific Journalism of the German Physical Society (DPG) Communitas Award of the Max Planck Society Member of the Junge Akademie Dannie-Heineman Award of the Academy of Science and Humanities, Göttingen Science award of Lower-Saxony - Wissenschaftspreis Niedersachsen Young Scientist Award for Socio- and Econophysics from the German Physical Society Professor Priesemann actively mentors numerous PhD students and postdocs in her research group, fostering interdisciplinary collaboration between physics, neuroscience, and data science. Her lab investigates topics ranging from neural plasticity and learning to epidemic modeling and information spread in social networks. She has secured significant research funding, including a German-Israel Foundation Young Investigator Grant and projects within the Cluster of Excellence 'Multiscale Bioimaging' and the Max Planck-University of Toronto Centre. Her research group maintains strong connections with experimentalists and theorists across multiple institutions, creating a vibrant environment for studying the principles of living adaptive networks. She has initiated several interdisciplinary research projects, including a major initiative on curiosity and hierarchical information processing across species.

• RNA Biology
• Single-Molecule Imaging
• Gene Editing
• +۷ مورد دیگر

David Grunwald is an Associate Professor at the University of Massachusetts Chan Medical School , affiliated with the T.H. Chan School of Medicine and Morningside Graduate School of Biomedical Sciences across multiple departments including Biochemistry and Molecular Biotechnology, Biophysical Chemical and Computational Biology, and others. His research spans RNA biology, single-molecule imaging, and gene editing. Education: BS in Biophysics from Humboldt University Berlin PhD in Biophysics from Ludwig Maximilian University of Munich Research Interests: Grunwald investigates RNA dynamics, focusing on nucleocytoplasmic transport, CRISPR-Cas9 nuclear behavior, and nucleoporin interactions in diseases like ALS. His work bridges biophysics and molecular biology, utilizing advanced microscopy techniques. Publication Trends: His recent articles emphasize microscopy metadata standards (e.g., FAIR bioimage data), RNA transport mechanisms, and CRISPR-based imaging. Collaborative efforts with institutions like the National Cancer Institute and Frederick National Laboratory for Cancer Research highlight interdisciplinary approaches. Networks: Grunwald collaborates with experts in RNA therapeutics, biochemistry, and developmental biology. Key co-authors include Caterina Strambio-De-Castillia and Thoru Pederson. His work intersects with concepts like cell nucleus dynamics, molecular imaging, and zebrafish models.