جست‌وجوی استاد و پژوهشگر

David E. Breenمشاهده پروفایل

استاد

• Biomedical Image Informatics
• Geometric Modeling
• Textile Modeling and Design
• +۱۲ مورد دیگر

David E. Breen is a Professor in the Department of Computer Science within the College of Computing & Informatics (CCI) at Drexel University. He leads the Geometric Biomedical Computing Group and is affiliated with the Metadata Research Center and the Center for Biological Discovery from Big Data. His research spans interdisciplinary domains including biomedical image informatics, geometric modeling, textile modeling, and bio-inspired self-organization algorithms. Education: PhD, Computer and Systems Engineering, Rensselaer Polytechnic Institute MS, Computer and Systems Engineering, Rensselaer Polytechnic Institute BA, Physics, Colgate University His research interests focus on computational methods for biomedical applications, including shape and image analysis for cancer diagnosis, 3D reconstruction of biological tissues, and video analysis of animal behavior. He also investigates geometric modeling techniques for textiles and self-organizing systems. His work integrates computer science with biology, medicine, and engineering to solve complex problems in biomedical computing. The recent publications highlight a strong trend in computational modeling of textiles, biomedical image informatics, and AI-driven data analysis. Key themes include geometric modeling of knitted fabrics, deep learning for medical image classification, agent-based modeling of cancer metastasis, and metadata generation for biological image collections. His work bridges fundamental geometric algorithms with practical applications in healthcare and digital archives. Scientific Awards: No specific awards mentioned in the provided text. Breen has advised numerous students and collaborators across multiple domains, particularly in biomedical computing and textile modeling. His research has been supported through affiliations with major centers and collaborations with institutions such as Johns Hopkins University and the Max Planck Institute. He has been involved in projects related to NSF Center for Visual & Decision Informatics and has contributed to over 100 technical publications. He leads the Geometric Biomedical Computing Group , which conducts research at the intersection of biology, medicine, engineering, and computer science. The group develops algorithms and software for geometry-related computing problems in biomedical applications. Collaborations include the Drexel Integrated Laboratory for Cellular Tissue Engineering, Dr. Dan Marenda's Lab, and Dr. Aleister Saunder's Lab in Drexel's Biology Department.

Meghan Balkمشاهده پروفایل

پژوهشگر ارشد

• Ecological and Evolutionary Biology
• Paleobiology
• Functional Morphology
• +۷ مورد دیگر

Meghan Balk is a Postdoctoral Fellow with the Evolution and Paleobiology Group at the Natural History Museum, University of Oslo. Her work combines museum collections and trait databases to investigate how inter- and intra-specific traits change across time and space. She is passionate about digitizing museum data and enabling FAIR data principles for continued exploration of data-driven science across evolutionary biology and ecology. Balk received her Ph.D. from the University of New Mexico in 2017 with a concentration in Interdisciplinary Science through the Department of Biology. She earned her B.S. from the University of California, Davis in 2010 in the Department of Evolution, Ecology, & Biodiversity, with a minor in Paleobiology through the Department of Geology. Her academic journey reflects a strong foundation in both biological sciences and geological perspectives on evolutionary processes. Her research employs both micro- and macroscopic approaches to understand abiotic and biotic drivers of phenotypic evolution. She investigates within and among lineage phenotypic evolution using fossil and modern records of organisms like bryozoans. Her work on abiotic drivers examines body size changes in species like the bushy-tailed woodrat across geological time, while her research on biotic drivers explores predator-prey relationships in the fossil record, particularly focusing on species like Otodus megalodon. She utilizes machine learning and computational approaches to extract morphological trait data from specimen images. Balk's publication record demonstrates expertise across evolutionary biology, paleontology, ecology, and computational approaches. Her recent work focuses on developing FAIR and modular workflows for image-based knowledge discovery in the emerging field of imageomics. She has made significant contributions to understanding body size evolution across geological time, predator-prey relationships in the fossil record, and promoting open science principles for trait-based research. Her work bridges traditional paleontological methods with cutting-edge computational techniques. Balk is actively involved in several research projects including ROCKS PARADOX (Dissecting the paradox of stasis in evolutionary biology) and Machine-readable Nature (MaNa). She collaborates with researchers across institutions to create ontologies and workflows for trait data, such as the Functional Trait Resource for Environmental Studies (FuTRES) project and the Biology-Guided Neural Networks project. She teaches courses including Foundational Open Science Skills workshop, Git for Mere Mortals webinar, and R Basics Crash course, emphasizing the importance of reproducible research practices.

Kelly Diamondمشاهده پروفایل

استادیار

• Integrative Biology
• Functional Morphology
• Computational Anatomy
• +۴ مورد دیگر

Kelly Diamond is an Assistant Professor of Biology at Rhodes College. She holds a bachelor's degree from the University of Central Florida, a master's, and a PhD from Clemson University, and completed a postdoctoral fellowship at Seattle Children's Research Institute. Her research integrates mathematics, physics, and machine learning to analyze how animal morphology influences survival-related functions. University of Central Florida - BSc Clemson University - MSc, PhD Seattle Children's Research Institute - Postdoctoral Researcher Her primary research focuses on quantitative anatomy, functional morphology, and biomechanics across evolutionary transitions. Current projects include using CRISPR-modified zebrafish to study gene impacts on skeletomuscular systems, and analyzing shape and locomotion changes in growing horned lizards. She also investigates waterfall-climbing mechanics in gobiid fishes and develops machine learning tools for morphological analysis. Recent publications demonstrate expertise in computational anatomy, 3D morphological visualization, and species classification algorithms. Her work bridges integrative biology with technological innovation through collaborations with the Imageomics Institute and development of educational tools like SlicerMorph. She actively engages in community outreach via the Ask an Animal Scientist website and lab community initiatives emphasizing inclusivity and mental health. Principle Investigator, Shape and Scales Lab Developed SlicerMorph open platform for 3D morphology analysis Advocates inclusive lab policies and cross-cultural collaborations

Jane Greenbergمشاهده پروفایل

استاد

• Metadata
• Knowledge Organization
• Linked Data
• +۶ مورد دیگر

Jane Greenberg is the Alice B. Kroeger Professor, PhD Program Director in Information Science, and Director of the Metadata Research Center at Drexel University’s College of Computing & Informatics (CCI). Her research focuses on metadata, knowledge organization, linked data, data science, and information economics. She leads initiatives like the Biology-guided Neural Network (BGNN) project and the HIVE linked data application, with work integrated into the Imageomics Institute and the NSF Dryad Data Repository project. PhD, Department of Library and Information Science, University of Pittsburgh MS, specialization in bibliographic control, Columbia University’s School of Library Service BA, double major in political science and art history, University of Rochester Greenberg’s research addresses metadata implementation, ontological ownership, and data sharing ecosystems, contributing to open science principles. Her work includes automatic metadata generation workflows and machine-readable knowledge organization systems. Scientific awards include: 2023 ASIS&T Research in Information Science Award 2016 ELATE at Drexel® Fellow 2014 Data Science Fellow Best Research Paper at Metadata and Semantic Research International Conference (2020) Best Student-Led Research Paper at ACM/IEEE Joint Conference on Digital Libraries (2021) She has secured over $79 million in research funding from organizations like NSF, NIH, Microsoft Research, and the National Library of Medicine. Greenberg founded the Metadata Research Center in 2004 and leads programs such as the IMLS LIS Education and Data Science Integrated Network Group (LEADING), which trains data science fellows across disciplines. The Metadata Research Center, under her leadership, has advanced metadata science through projects like the Metadata Capital Initiative (MetaDataCAPT'L) and the Helping Interdisciplinary Vocabulary Engineering (HIVE) linked data project.

• Synaptic Physiology
• Super-Resolution Microscopy
• STED Microscopy
• +۱۲ مورد دیگر

Prof. Dr. Silvio O. Rizzoli is a full Professor and Director of the Department of Neuro- and Sensory Physiology at the University Medical Center Göttingen, Faculty of Medicine. He leads a pioneering research group in synaptic function and super-resolution microscopy, with a focus on STED imaging and quantitative synaptology. His laboratory is part of multiple interdisciplinary programs including IMPRS in Molecular Biology, Neurosciences, and Cellular and Molecular Physiology of the Brain. BSc in Biochemistry, University of Bucharest (1996–2000) PhD in Physiology, University of Colorado, Denver (2000–2004) Postdoctoral Fellow, Max Planck Institute for Biophysical Chemistry (2004–2007) Group Leader, European Neuroscience Institute Göttingen (2007–2012) Professor (W3), University Medical Center Göttingen (2012–2014) Director, Department of Neuro- and Sensory Physiology (2014–present) His research focuses on overcoming the diffraction limit in optical microscopy to study synaptic vesicle recycling, protein domain patterning, and the molecular architecture of synapses. Using STED, electron microscopy, and NanoSIMS, his lab investigates the functional organization of presynaptic compartments, developing concepts like stoichiometric biology to link molecular distribution with function. His group has demonstrated the role of a small pool of 'perfect' vesicles in neurotransmission and their buffering function in vivo. The recent publications reveal a strong emphasis on super-resolution imaging, synaptic proteomics, and vesicle dynamics. The work integrates advanced microscopy with biochemical and biophysical approaches to analyze protein clusters, vesicle trafficking, and nanoscale organization in neurons. Key themes include the development of nanobody-based imaging (Imageomics), expansion microscopy (ONE Microscopy), and ultra-resolution techniques (ULTRARESOLUTION). Prof. Rizzoli leads major funded projects including: Imageomics (Horizon 2020 FET-OPEN) ULTRARESOLUTION (ERC Synergy Grant) The Neuron Nanomap NanoSIMS 50L He is the Director of the Göttingen EXM Forum (GEF25), promoting accessibility of super-resolution microscopy. His lab collaborates widely across engineering, physics, and life sciences to develop next-generation imaging tools. Though no formal students are listed, his leadership in training environments like IMPRS indicates active mentorship. The lab’s work has broad implications for neuroscience, diagnostics, and biomedical imaging.

• Super-Resolution Microscopy
• Synaptic Vesicle Recycling
• Nanoscale Imaging
• +۳ مورد دیگر

Professor Silvio Rizzoli directs the Department of Neuro- and Sensory Physiology at the University Medical Center Göttingen, specializing in super-resolution microscopy techniques to investigate synaptic function at the nanoscale. Holds a PhD in Physiology from the University of Colorado (2004) and leads research on synaptic vesicle recycling using STED microscopy. His groundbreaking work enables visualization of sub-synaptic structures below the diffraction limit. Research employs STED microscopy to map synaptic vesicle pools and protein domains, developing novel imaging probes and correlative methods like NanoSIMS. Recent work focuses on ultra-resolution techniques combining expansion microscopy with fluctuation analysis to achieve molecular-scale resolution. Honored as Fellow of the Royal Society of Edinburgh. Leads ERC Synergy and FET-OPEN projects developing next-generation nanoscopy including ONE Microscopy and Imageomics platforms. Manages core facilities including NanoSIMS 50L and coordinates international collaborations across physics, chemistry, and neuroscience disciplines.

Anuj Karpatneمشاهده پروفایل

دانشیار

• Knowledge-guided Machine Learning (KGML)
• Spatio-temporal Data Mining
• Environmental Science Data Analysis
• +۵ مورد دیگر

Anuj Karpatne is an Associate Professor in the Department of Computer Science at Virginia Tech, leading the Knowledge-guided Machine Learning (KGML) Lab. He joined VT in 2018 and earned tenure in 2023. His research focuses on integrating scientific knowledge into machine learning, pioneering the KGML paradigm to create explainable and generalizable AI solutions for interdisciplinary scientific challenges. He holds a PhD from the University of Minnesota (2017) and an M.Tech. from IIT Delhi (2011). Research Interests: Knowledge-guided ML frameworks (KG-Loss, KG-Neural Architectures, Hybrid-Science-ML) Applications in physics (fluid dynamics, quantum mechanics), environmental sciences (aquatic systems, remote sensing), and biology (organismal biology, virology) Interdisciplinary collaborations across 15+ institutions for NSF-funded projects Recent Contributions: Developed Fish-Vista dataset for biological trait analysis Co-organized KDD 2024 workshop on Generative Models for Sustainable Development Secured $18M NSF PIPP II grant as co-PI for pandemic prediction systems Grants & Leadership: Lead PI on NSF CAREER Grant ($586K) for unifying ML with scientific knowledge Co-PI on NSF Imageomics Institute ($15M) integrating biology with AI Site PI for macrosystems biology grant ($1.1M) modeling lake water quality Labs & Teams: KGML Lab at VT collaborates with 30+ scientists across disciplines Leadership roles in NSF PIPP Institute and Imageomics Center

• Radiology
• Diagnostic Imaging
• Magnetic Resonance Imaging
• +۷ مورد دیگر

Joan Carles Vilanova Busquets is an Associate Professor in the Department of Medical Sciences at the School of Medicine, University of Girona. He is also the Director of the Magnetic Resonance Institute at Clínica Girona, a Staff Consultant at the Institute of Diagnostic Imaging (IDI) of the Catalan Institute of Health, and the Chief of the Prostate Imaging Unit at the Dr. Josep Trueta University Hospital in Girona, Spain. His career is marked by significant leadership in national and international radiology societies. MD, Medicine, University of Barcelona (1988) PhD, Medicine, University of Barcelona (2008) Board Certified Radiologist, University Hospital Dr. J. Trueta, Girona Fellowship, American Forces Institute of Pathology (AFIP), Washington, DC, USA Dr. Vilanova's research is centered on advanced diagnostic imaging, particularly multiparametric MRI. His primary interests include the application of MRI in prostate cancer diagnosis and staging, musculoskeletal radiology, soft tissue tumor imaging, whole-body MRI, and functional imaging in oncology. His work bridges clinical practice with cutting-edge technological applications in medical imaging. The 15 most recent articles reflect a strong focus on the application of advanced MRI techniques in oncology. Key trends include the development and refinement of clinical guidelines for imaging soft tissue tumors and prostate cancer, the use of radiomics and artificial intelligence for diagnosis, and the technical optimization of MRI protocols for specific conditions like the diabetic foot and hepatobiliary disorders. His publications frequently appear in high-impact radiology journals and often involve collaborative, multi-institutional research. Dr. Vilanova has received numerous scientific honors, including: Recognition of the professional career of the Medical Association of Girona (2016) Award for research in Spanish Radiology - SERAM (Sevilla, 2008) Magna cum Laude at the European Congress of Radiology (ECR 2006) and the Radiological Society of North America (RSNA 2009) Multiple Cum Laude awards at international conferences (RSNA 2010, 2012, 2015; SERAM 2014) He has been a prolific advisor and researcher, with over 300 publications and participation in 40 research projects. He has held key leadership positions, such as Chairman of the Spanish Society of Musculoskeletal Radiology (SERME) and the Scientific Committee of the Spanish National Congress of Radiology (SERAM). He is also an active educator, focusing on integrating radiology into broader medical curricula. Dr. Vilanova leads a prominent research lab at the University of Girona and is a key member of the Aging Imageomics Study. His current work involves several teams focused on AI in medical imaging, prostate cancer imaging, and the application of functional MRI in various pathologies.