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Michale S FeeView profile

Professor

• Neuroscience
• Animal Behavior
• Neural Circuits
• +4 more

Michale S Fee is the Department Head of Brain and Cognitive Sciences and holds the Glen V. and Phyllis F. Dorflinger Professorship at MIT. He is also an Investigator at the McGovern Institute for Brain Research. Dr. Fee earned his PhD in Applied Physics from Stanford University (1992) and joined MIT in 2003. His research focuses on neural mechanisms underlying vocal learning in songbirds, neural circuit dynamics, and the development of advanced neural recording technologies. Education: PhD in Applied Physics, Stanford University, 1992 Research Interests: Dr. Fee investigates how complex sequential behaviors like birdsong are generated and learned. His work combines electrophysiology, imaging, and computational modeling to study neural circuits involved in vocal control. Key areas include: Neuronal sequence generation in the avian brain Role of basal ganglia and thalamic pathways in motor learning Design of wearable neural recording devices for in vivo studies Grants & Labs: He leads the McGovern Institute's efforts in neural circuitry research and oversees departmental initiatives at the MIT Department of Brain and Cognitive Sciences. His lab develops innovative tools such as head-mounted microscopes for large-scale neural recordings.

Jasper van ThorView profile

Professor

• Molecular Biophysics
• Ultrafast Spectroscopy
• X-ray Crystallography
• +4 more

Professor Jasper van Thor is a faculty member at Imperial College London's Department of Life Sciences, part of the Faculty of Natural Sciences. He holds the title of Professor of Molecular Biophysics and leads the Ultrafast Spectroscopy Laboratory and Molecular Biophysics group. His research focuses on ultrafast molecular dynamics using techniques like femtosecond crystallography and spectroscopy, particularly studying light-sensitive proteins such as photoreceptors, fluorescent proteins, and photosynthetic systems. He has pioneered work on structural dynamics using X-ray free electron lasers (XFELs) and developed open-source software tools like the Ultrafast Spectroscopy Modelling Toolbox and PyLDM for data analysis. Education: MSc (1993) and PhD (1999) in Chemistry from the University of Amsterdam, followed by postdoctoral research at the University of Oxford under Dame Louise Johnson, supported by EMBO and HFSP fellowships. He joined Imperial College in 2007, establishing the Ultrafast Spectroscopy Lab. Research Interests: Ultrafast structural changes in proteins, photoactivation mechanisms, coherent vibrational dynamics, XFEL applications in biology, and theoretical modeling of population dynamics. His work bridges molecular biophysics, chemistry, and materials science, with contributions to understanding photosynthesis and protein signaling. Key Achievements: Director of Imperial's Frontiers of Ultrafast Measurement network and PI of the LUXD lab. Developed novel methods for femtosecond infrared crystallography and revealed mechanisms like the 'hula-twist' isomerization in fluorescent proteins. Authored influential papers on protein structural dynamics and spectroscopic analysis tools. Awards: EMBO Research Fellowship (2000), HFSP Long-Term Fellowship (2000), Royal Society University Research Fellowship (2002). Recognized for contributions to ultrafast structural biology. Grants & Labs: Active in XFEL collaborations globally (LCLS, SACLA, European XFEL). Oversees the Electron Microscopy Centre and Energy Futures Lab affiliations. His lab develops open-source software for data analysis, emphasizing reproducibility and accessibility.

• Virology
• Molecular Biology
• Infectious Diseases
• +3 more

Associate Professor Timothy Newsome is affiliated with the School of Life and Environmental Sciences at the University of Sydney. He leads research in virology, focusing on mechanisms of viral spread and host-pathogen interactions, particularly with vaccinia virus and SARS-CoV-2. His work integrates advanced microscopy, single-cell analysis, and molecular biology to understand viral dynamics. Key research themes include actin-based motility in viral dissemination, cytokine regulation during infections, and development of drug discovery strategies. He collaborates with The Centre for Drug Discovery Innovation to identify antiviral targets. Recent publications highlight innovations in high-throughput single-cell analysis of viral infections and the role of SMAD proteins in infection outcomes. His grants include projects on Mpox drug targets (2023) and evolution of Monkeypox virus (2022). Newsome’s career trajectory includes appointments as Lecturer (2007), Senior Lecturer (2012), and current role as Associate Professor since 2019. He contributes to both basic science and translational research in infectious diseases.

Suzanne A. BlumView profile

Professor

• Organic Chemistry
• Organometallic Chemistry
• Catalysis
• +5 more

Suzanne A. Blum is a Professor in the Department of Chemistry at the University of California, Irvine. Her research focuses on organic, organometallic, and materials chemistry, with an emphasis on catalysis, chemical imaging, and microscopy. She leads the Blum Laboratory, which explores reaction mechanisms using advanced techniques like FLIM and SAXS. Her work integrates sustainable chemistry practices and has produced innovations in surfactant-dependent partitioning, palladium carbenes, and organozinc reagent formation. She has mentored numerous PhD students, many of whom have received prestigious fellowships and awards. Key research themes include catalyst recycling, reaction design for organometallic systems, and mechanistic insights from imaging technologies. Notable contributions include studies on self-assembly in polymers, surfactant effects on reagent distribution, and the ACS Cope Scholar Award. Her lab collaborates widely, exemplified by joint work on palladium carbenes with Joe Patterson and Nehal Idris. Current projects span from zinc metal activation pathways to sustainable reaction systems. Dr. Blum has supervised over a dozen graduate students, including Drs. Pía López, Martin Stang, Erin Hanada, and Hannah Peacock. Her team’s work has been recognized through awards like the Allergan Fellowship and Humboldt Postdoctoral Fellowship. The lab also emphasizes scientific communication, hosting workshops on data presentation and experimental design. Facilities include cutting-edge equipment like the PicoQuant FlexLambda for time-resolved fluorescence studies.

Benjamin BerkelsView profile

Associate Professor

• Image Processing
• Computer Vision
• Variational Methods
• +3 more

Benjamin Berkels is an apl. Professor (equivalent to Associate Professor) at the Institute for Geometry and Practical Mathematics (IGPM) within the Faculty of Mathematics, Computer Science and Natural Sciences at RWTH Aachen University, Germany. His office is located at Rogowski, Raum 124, Schinkelstraße 2, 52062 Aachen. He has held his current position since May 2025 and also serves as Akademischer Rat at IGPM since October 2024. Previously, he was a Juniorprofessor for Mathematical Image and Signal Processing and Junior Research Group Leader at AICES, RWTH Aachen from 2013 to 2024, with several interim professorships at RWTH Aachen and the University of Lübeck. Dr. Berkels received his educational foundation with a Dipl.-Math. from the University of Duisburg-Essen in 2005, followed by a Dr. rer. nat in Mathematics from the University of Bonn in 2010, and completed his Habilitation-equivalent with a positive intermediate evaluation as Juniorprofessor from RWTH Aachen in 2016. His professional journey includes postdoctoral positions at the University of Bonn and the University of South Carolina, establishing his expertise in mathematical image analysis before returning to Germany for his faculty positions. His research focuses on the intersection of mathematical theory and practical image analysis applications, with core interests in Image Processing, Computer Vision, Variational Methods, Joint Methods, Registration, and Segmentation. Berkels' work demonstrates exceptional interdisciplinary reach, applying advanced mathematical techniques to solve complex problems in materials science, microscopy, medical imaging, and environmental monitoring. His recent publications reveal a strategic expansion into machine learning applications while maintaining strong foundations in variational methods and mathematical image analysis. Analyzing his 15 most recent publications reveals a clear research trajectory emphasizing atomic-scale image analysis for materials characterization. Approximately 70% of his recent work focuses on applying sophisticated image processing techniques to electron microscopy data for materials science applications, particularly in analyzing grain boundaries, phase transformations, and defect structures. The remaining publications show increasing integration of machine learning approaches, especially deep learning and GANs, for industrial and scientific image analysis problems. This demonstrates his ability to bridge fundamental mathematical research with practical applications across multiple scientific domains. Dr. Berkels maintains an exceptionally active research profile with consistent publication output across high-impact journals in both mathematics and materials science. His extensive collaboration network spans multiple continents and disciplines, with frequent co-authorship with materials scientists, microscopists, and computer vision researchers. While specific grant information isn't provided in the text, his sustained research output and leadership of a junior research group suggest successful grant acquisition throughout his career. His work at IGPM positions him at the forefront of mathematical approaches to image analysis with significant impact on materials characterization techniques.

Henry P. SchriemerView profile

Professor

• Photovoltaics
• Solar Energy
• Smart Grid
• +8 more

Henry P. Schriemer is a Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa's Faculty of Engineering. His career bridges fundamental physics, photonics innovation, and applied renewable energy systems, with significant contributions to both academic research and industrial photonics development. His educational foundation includes a B.Sc. in Mathematics (1987) and Ph.D. in Physics (1997), both from the University of Manitoba. Early career milestones featured postdoctoral research at Queen's University and a prestigious FOM Postdoctoral Fellowship at Amsterdam's van der Waals-Zeeman Institute. Schriemer's research spans Nanophotonics, Optoelectronics, and Complex Systems, with current emphasis on Photovoltaics and Smart Grid technologies. His photovoltaic work integrates multiphysics simulation, spectral irradiance modeling, and system reliability testing, while his smart grid research pioneers blockchain-secured demand response and game-theoretic energy management. This dual focus addresses critical challenges in renewable energy integration and grid stability. Analysis of his 2020-2024 publications reveals a decisive shift toward solar energy systems and grid modernization. His team develops predictive spectral models incorporating weather dynamics, advanced demand response frameworks using Stackelberg game theory, and novel instrumentation like the CanSIM network for solar resource assessment. These works consistently bridge atmospheric science, power systems engineering, and cybersecurity. His scientific achievements include: FOM Postdoctoral Fellowship (1998) for nanophotonics research at van der Waals-Zeeman Institute NCIT Research Fellowship in Photonics (2003-2005) at University of Ottawa Industry recognition as innovator of strain-engineered planar lightwave circuits Schriemer has authored over 50 refereed publications in Science, Physical Review, and IEEE journals. His industrial contributions include foundational work in diffusive acoustic wave spectroscopy and optical scattering techniques, while his academic leadership manifests through the CanSIM network and IEEE 2030/2030.5 standard implementations. He maintains active collaborations across atmospheric science, power systems, and semiconductor physics domains. His laboratory operations focus on photovoltaic testbeds, solar spectral irradiance instrumentation, and smart grid simulation platforms. The CanSIM network provides critical northern-climate solar data, while his module-level power electronics research directly addresses rapid cloud-shading challenges in real-world PV deployments.

George AzzopardiView profile

Associate Professor

• Pattern Recognition
• Image Processing
• Machine Learning
• +5 more

George Azzopardi is an Associate Professor in Pattern Recognition at the University of Groningen, affiliated with the Bernoulli Institute. He leads the PRISMA team, focusing on robust AI, medical imaging, and interdisciplinary applications in astronomy and forensics. His roles include coordinating the Applied AI theme at the Jantina Tammes School and leading WG4 of the EU GLITSS COST Action. Education: PhD in Computer Science (University of Groningen, 2013), MSc in Advanced Methods in Computer Science (Queen Mary University London, 2008), BSc in Computer Science (Goldsmiths College London, 2006). Research Interests: Brain-inspired algorithms, image processing, predictive analytics, and applications in radio astronomy, forensics, and medical diagnostics. His work emphasizes robustness in AI models and cross-domain collaborations. Publications span advancements in COSFIRE filters, deep learning robustness, and interdisciplinary applications like radio galaxy classification and biometric systems. Recent trends include enhancing model explainability and combating adversarial attacks. Awards: Ben Feringa Impact Award (2023), ENLIGHT Impact Award (2024) Advising: Supervises PhD students in AI-driven medical imaging, radio astronomy, and computer vision. Collaborates with institutions like ASTRON, UMCG, and industry partners Ziel NL and KAIOS. Labs/Teams: PRISMA team develops robust AI tools for medical and astrophysical data analysis, with projects on biostructure segmentation and camera forensics.

Michael WernerView profile

Research Professor

• Cell Biology
• Cytoskeleton Dynamics
• Cytokinesis
• +4 more

Michael Werner is a Research Professor in the Department of Biology at the University of North Carolina at Chapel Hill. His research focuses on cytoskeletal dynamics, particularly how the cytoskeleton regulates cell division, oocyte formation, and ciliary beating. He employs advanced microscopy and data analysis techniques to study cellular processes like cytokinesis and syncytial germline organization. His work combines experimental and computational approaches to understand mechanical and biochemical feedback mechanisms driving cellular behaviors. Werner's research interests span multiple subdisciplines, including cytokinesis, microtubule dynamics, and cilia biology. He has contributed to studies on septin functionality, cilia orientation defects, and the role of CLAMP/Spef1 in cell polarity. His lab’s recent work explores the interplay between mechanical forces and biochemical signals in cellular contractility, with implications for developmental biology and disease mechanisms. In teaching and outreach, Werner emphasizes active learning strategies and problem-driven instruction to foster student engagement in cell biology. He maintains an open lab website and collaborates widely in the field, though specific grant details or awards are not explicitly mentioned in available texts.

• Atomic Resolution Imaging
• Electron Microscopy
• Theoretical Physics
• +3 more

Scott Findlay is an Associate Professor in the School of Physics and Astronomy at Monash University. He holds an ARC Future Fellowship (2020–present) and has expertise in theoretical physics and advanced electron microscopy techniques. His research focuses on atomic resolution imaging via scanning transmission electron microscopy (STEM), including novel detector geometries, compositional analysis of nanostructures, and quantitative structure determination. He has led multiple ARC-funded projects, including 'UltraTEM' and 'Nanoscale field mapping in functional materials.' Education: PhD in Physics (Theoretical Aspects of Scanning Transmission Electron Microscopy), The University of Melbourne (2005) BSc (Hons) in Physics, The University of Melbourne (2001) Research Interests: Developing theoretical models and numerical simulations to enhance STEM capabilities, particularly in dynamic scattering analysis. Current projects include optimizing segmented/pixel detectors for imaging, quantifying material composition at the nanoscale, and analyzing thick nanostructures. Articles Trends: Recent work emphasizes 4D-STEM advancements, including denoising algorithms, scattering matrix reconstruction, and atom-counting techniques. His research bridges theory and experiment, addressing challenges in dynamical scattering and phase retrieval. Awards: AMMS Microscopy and Microanalysis Award (2018) Exceptional Educational Service Award (2021) Outstanding Reviewer for Microscopy and Microanalysis (2017) Advising & Grants: Supervises PhD students and has secured over AUD 10 million in ARC grants. Coordinates Monash's Level 2 Physics curriculum and chairs the School's Education Committee. Labs/Teams: Collaborates with institutions like the University of Tokyo and the University of Melbourne on projects such as magnetic field mapping and electron ptychography.

Candace HaiglerView profile

Professor

• Cellulose Biology
• Plant Cell Wall Biogenesis
• Cotton Fiber Development
• +6 more

Candace Haigler is a Professor and Director of Crop Science Graduate Programs at NC State University's College of Agriculture and Life Sciences, within the Department of Crop and Soil Sciences. Her research focuses on cellulose synthesis, plant cell wall biogenesis, and cotton fiber development. She leads a multidisciplinary lab employing techniques like bioinformatics, genomics, molecular genetics, microscopy, and plant transformation to study cotton fiber and tracheary element cell walls. Her work aims to improve cellulose-based crops, such as wood and forage, through genetic engineering and marker-assisted breeding. Key research themes include understanding cellulose nanofibril assembly, microtubule regulation in fiber growth, and leveraging genomic resources for crop improvement. Publications highlight advancements in cotton fiber gene expression modeling, alternative cellulose biosynthesis pathways, and structural biology of cellulose synthases. Collaborations span plant biology, computational science, and materials research to address agricultural challenges. As a leader in graduate education, Haigler oversees the Crop Science Graduate Programs, fostering next-generation researchers in plant sciences. Her lab’s findings contribute to transitioning cotton from a bulk commodity to a value-added material tailored for specific applications.

Andrew BartonView profile

Associate Professor

• Marine Ecology
• Climate Impacts on Marine Ecosystems
• Biogeochemistry
• +5 more

Andrew Barton is an Associate Professor in the Integrative Oceanography Division at the Scripps Institution of Oceanography, UC San Diego. His research focuses on marine plankton physiology and ecology, climate impacts on marine ecosystems, and interactions between plankton and biogeochemical cycles. He holds a BA from Cornell University, an MS from Cornell, and a PhD from MIT. Education: B.A. Science of Earth Systems, Cornell University M.S. Geological Sciences, Cornell University Ph.D. Climate Physics and Chemistry, Massachusetts Institute of Technology Research interests include marine macroecology, biogeography, biodiversity, and the physiological responses of marine microbes to environmental changes. His work emphasizes the interplay between plankton communities and global biogeochemical cycles under climate variability. Recent studies explore microbial dispersal mechanisms, harmful algal bloom drivers, and Arctic Ocean plankton dynamics. Publications highlight advancements in trait-based modeling frameworks (e.g., XSO and Phydra libraries) and interdisciplinary approaches to understanding plankton behavior and ecosystem resilience. His research integrates field observations, satellite data, and computational models to address pressing marine ecological questions.

Patrizio CampisiView profile

Professor

• Digital Signal Processing
• Image Processing
• Biometrics
• +12 more

Patrizio Campisi is a Full Professor in the Section of Applied Electronics at the Department of Engineering, Roma TRE University, Rome, Italy. He leads cutting-edge research in digital signal and image processing with applications to secure multimedia communications and biometrics. He has held visiting positions at the University of Toronto, Beckman Institute (UIUC), and École Polytechnique de Nantes, and has been a Marie Curie Fellow (2010–2014). His educational background includes a Laurea (summa cum laude) in Electronic Engineering from Sapienza University of Rome and a Ph.D. in Electrical Engineering from Roma TRE University. His research focuses on secure biometric recognition (signature, keystroke, EEG, vein), digital watermarking, blind image deconvolution, HDR imaging, and privacy-preserving technologies. He has contributed significantly to template protection, multimodal biometrics, and forensic image analysis. His work bridges engineering, computer science, and security, with strong applications in mobile authentication, border control, and social media safety. The recent publications reflect a strong trend in biometrics, image forensics, and privacy-enhancing technologies, with a focus on real-world applications in mobile systems, healthcare, and law enforcement. Key themes include secure authentication, de-identification, and computational imaging. IEEE Second International Conference on Biometric Systems 2008 Best Student Paper Award IEEE Biometric Symposium 2007 Best Paper Award IEEE International Conference on Image Processing 2006 Best Student Paper Award Marie Curie Fellow (2010–2014) NATO-CNR Advanced Fellowship (2003) IEEE Senior Member Prof. Campisi has supervised numerous students and leads the BioMedia4n6 lab. He has secured major EU grants including H2020 projects AMBER, COSMOS, and ENCASE. His editorial leadership includes serving as Editor-in-Chief of IEEE Transactions on Information Forensics and Security (2018–2020) and Chair of the IEEE Information Forensics and Security Technical Committee (2017–2018). He is actively involved in research networks such as COST Actions on de-identification and biometrics-forensics integration, and has contributed to EU policy via the BEST Thematic Network on biometrics and fundamental rights. His lab, BioMedia4n6, focuses on biometrics, multimedia forensics, and privacy-aware systems.

• Immunology
• Infection and Immunity
• Antigen Trafficking
• +12 more

Santiago González F. is an Extraordinary Professor at the Università della Svizzera italiana (USI), affiliated with the Faculty of Biomedical Sciences and the Institute for Research in Biomedicine (IRB) in Bellinzona, Switzerland. He leads the Infection and Immunity research group, focusing on immune responses to infections and cancer. His work integrates molecular immunology, intravital imaging, and nanotechnology to understand immune cell dynamics in vivo. PhD in Microbiology, University of Santiago de Compostela, Spain PhD in Immunology, University of Copenhagen, Denmark Postdoctoral Fellow, Harvard Medical School, USA (2007–2011) His research centers on the mechanisms of antigen trafficking, dendritic cell function, and immune regulation during influenza infection and tumor metastasis. He has made seminal contributions to understanding how SIGN-R1 mediates influenza recognition and how subcapsular sinus macrophages promote melanoma spread. His lab employs cutting-edge intravital microscopy and develops tools like CANCOL for immune cell tracking. The recent publications highlight a strong trend in immune cell dynamics, inflammation modeling, and vaccine development. His work spans from fundamental immunology to translational applications, including mRNA nanovaccines and immunomodulatory drugs. There is a consistent focus on lymph node biology, innate immunity, and real-time imaging of immune responses. Marie Curie Training Site Fellowship (2004) Marie Curie International Outgoing Fellowship (2008) Marie Curie Career Integration Grant (2013) Recognition by Faculty of 1000 Santiago González has secured significant research funding through the European Union’s Marie Curie program and ERC grants, enabling the establishment and growth of his independent research group at IRB. He mentors a multidisciplinary team of scientists and students, contributing to PhD and postdoctoral training programs. His collaborations include partnerships with Rockefeller University and national biotechnology centers. He directs the Infection and Immunity laboratory at IRB, which specializes in intravital imaging, immune cell tracking, and vaccine development. The lab has developed innovative platforms such as stealth mRNA nanovaccines and computational tools for image analysis. The team actively engages in technology transfer and participates in European research networks.

Maryse Lapierre-LandryView profile

Academic

• Biomedical Engineering
• Medical Imaging
• Machine Learning
• +3 more

Maryse Lapierre-Landry, PhD, is a Research Assistant Professor in the Department of Biomedical Engineering at Case Western Reserve University's Case School of Engineering, with an affiliation to the School of Medicine. Her research focuses on advancing image processing techniques, including machine learning, for applications in biomedical optical imaging. Key areas include automated analysis of 3D microscopy and optical coherence tomography (OCT) data for applications such as corneal nerve evaluation, embryonic heart development, and vascular segmentation. Dr. Lapierre-Landry bridges the gap between novel optical instruments and biomedical scientists by developing algorithms for complex datasets. Her work addresses challenges in segmenting blood vessels in embryonic hearts, analyzing corneal nerve patterns, and optimizing tissue segmentation without vascular contrast agents. Publications span topics like deep learning for 3D histology, nuclei detection in microscopy, and 4D OCT imaging of beating hearts. Her research emphasizes practical solutions for biomedical imaging challenges in ophthalmology, cardiology, and developmental biology. Dr. Lapierre-Landry has contributed to over 20 peer-reviewed articles since 2013, with recent work focusing on corneal nerve activity, vagus nerve segmentation via micro-CT, and multiplexed virtual histology. Her interdisciplinary approach integrates engineering, computer science, and biology to advance medical diagnostics and research tools.

Todd C. HufnagelView profile

Professor

• Structural Materials
• Nanomaterials
• X-ray Scattering
• +3 more

Todd C. Hufnagel is a Professor of Materials Science and Engineering at Johns Hopkins University's Whiting School of Engineering. He serves as Associate Director of the Materials Science in Extreme Environments University Research Alliance (MSEE URA), a consortium addressing threats from chemical, biological, and nuclear weapons through material science research. His expertise includes structural materials, nanomaterials, X-ray scattering, and metals analysis. Dr. Hufnagel earned his BS in Metallurgical Engineering from Michigan Technological University (1989) and his MS and PhD in Materials Science and Engineering from Stanford University (1991 and 1995). He has been at Johns Hopkins since 1996. His research focuses on dynamic material behavior, fracture mechanics, and advanced imaging techniques like X-ray phase contrast imaging. Notably, he co-developed the AXIOM system, a cutting-edge tool for materials analysis, and contributed to the MSEE URA's mission to enhance material resilience in extreme conditions. His awards include the Whiting School of Engineering Teaching, Advising, and Mentoring Award. His work spans experimental and computational studies of metallic glasses, fracture processes, and parameter optimization for microstructural design. He collaborates widely, integrating data science tools like OpenMSIStream to streamline laboratory workflows.