جست‌وجوی استاد و پژوهشگر

• Pharmaceutical Policy
• Medication Adherence
• Healthcare Quality Improvement
• +۵ مورد دیگر

Richard Segal, Ph.D., is a Professor in the Department of Pharmaceutical Outcomes & Policy at the University of Florida College of Pharmacy, with a joint appointment in the Department of Pharmacotherapy and Translational Research. His research focuses on improving medication use safety and quality, particularly through optimizing prescribing practices and collaborative healthcare models. A renowned leader in pharmacy education, he has received numerous teaching awards including the 2024 Faculty Teaching Excellence Award and the 2021 University of Florida Teacher of the Year. His contributions span over 200 peer-reviewed publications and include seminal work on Therapeutic Outcomes Monitoring (TOM), a pharmacist-led intervention to reduce drug-related issues. Key research areas include medication adherence in marginalized populations, healthcare quality improvement, and health equity in diabetes and chronic disease management. Dr. Segal has led and co-investigated over 30 grants, including major initiatives like the Florida-California Cancer Equity Center and studies funded by the NIH and CDC. He teaches advanced research and clinical pharmacy courses, mentoring students in pharmaceutical outcomes and policy. His accolades include the 2011-2016 American Managed Care Pharmacy Crisafi Endowed Chair and the 2001 Blue Cross Blue Shield Research Mentorship Award. His work has shaped national medication therapy management practices and policy.

Lisa Ehrlingerمشاهده پروفایل

پژوهشگر

• Data quality
• Knowledge graphs
• Ontologies
• +۵ مورد دیگر

Lisa Ehrlinger is a Senior Researcher at the Information Systems Research Group within the Digital Engineering Faculty of the University of Potsdam. She holds a PhD in Engineering Sciences ("passed with distinction") and an MSc in Computer Science from Johannes Kepler University Linz (JKU), both with distinction. Her work bridges academic research and industrial application. Her research focuses on Data Quality , Knowledge Graphs , Ontologies , Semantic Technology , Data Catalogs , and Data Integration , particularly with NoSQL databases. She has over 7 years of applied research experience at the Software Competence Center Hagenberg GmbH (SCCH), including project management and team leadership. Her recent publications emphasize SHACL validation , Data Stream Pollution , Dashboard Design , and Ontology-Driven Analysis , reflecting trends in data quality automation , semantic modeling , and industrial data governance . She co-chaired the Quality of Databases (QDB) workshop (2023, 2024) and serves on the MIT CDOIQ Symposium review board (since 2023). Her outreach includes lecturing at JKU and reviewing for journals like ACM Journal of Data and Information Quality (JDIQ) and Elsevier Journal of Information Fusion .

• Human Cognitive Evolution
• Decision-Making Under Risk
• Evolutionary Psychology
• +۳ مورد دیگر

Andreas Wilke is a Professor in the Department of Psychology at Clarkson University, affiliated with the Lewis School of Health & Life Sciences. His research focuses on the evolutionary basis of human decision-making, particularly under conditions of risk and uncertainty. He holds a Ph.D. in Psychology from the Free University of Berlin and has conducted postdoctoral research at institutions including UCLA and the Konrad Lorenz Institute. Wilke's work integrates cognitive psychology with evolutionary biology, exploring topics such as foraging behavior, risk perception, and the 'hot hand' fallacy. He has secured grants from the National Science Foundation and Clarkson University, and his research has been presented at conferences like the Human Behavior and Evolution Society meetings. Education: Ph.D. in Psychology (2006) and M.A. in Psychology (2002), Free University of Berlin. Key Research Interests: Evolution of decision-making under uncertainty, foraging strategies, cognitive biases, and cross-cultural studies. Grants: NSF Grant SES-2116145 (2021–2023), multiple Clarkson University awards for research on randomness perception and statistical thinking. Wilke’s research emphasizes interdisciplinary collaboration, linking psychological findings to anthropology and ecology. His lab examines how evolutionary pressures shape cognitive mechanisms, including studies using virtual reality to simulate foraging scenarios. Recent work investigates children’s understanding of randomness and spatial reasoning, highlighting developmental perspectives.

Longin Jan Lateckiمشاهده پروفایل

استاد

• Computer Vision
• Medical Imaging
• Digital Geometry and Topology
• +۶ مورد دیگر

Dr. Longin Jan Latecki is a Professor in the Department of Computer and Information Sciences at Temple University. His research focuses on computer vision, medical imaging, digital geometry, and artificial intelligence. He has held editorial roles, including Associate Editor-in-Chief of Pattern Recognition and roles on the editorial boards of Computer Vision and Image Understanding and Journal of Imaging . He has organized events like the Asian Conference on Pattern Recognition and chaired the PhD Track in Artificial Intelligence. His research spans topics such as shape-based object detection, video mining, and robot mapping. Notable projects include the Shape-Based Image Search Engine and work on Well-Composed 3D Images . He has authored over 300 publications and advised numerous PhD students in areas like medical imaging, computer vision, and data mining. Dr. Latecki has collaborated on projects such as ClimatePub4KG for climate modeling and SciDMT for scientific mention detection. His work emphasizes practical applications, including dental imaging analysis, autonomous robotics, and multimedia transmission optimization. He teaches courses like Mathematical Concepts in Computing and Artificial Intelligence .

Ryan Ellerمشاهده پروفایل

مدرس ارشد

• Genetics
• Genomics
• Computational Biology
• +۶ مورد دیگر

Ryan Eller is a Senior Lecturer in the Department of Biology, Forensic & Investigative Sciences at Indiana University. He holds a Ph.D. in Genetics from Purdue University (IUPUI) and a B.S. in Biology from Butler University. His research focuses on utilizing computational tools to extract and analyze genetic information from human DNA. His primary research interests include Genetics/Genomics, Computational Biology and Bioinformatics, Artificial Intelligence, and Statistics. Eller's work explores how DNA stores information about ancestral histories, disease susceptibility, and human phenotypes, with applications spanning from medical fields to forensics to population genetics. Analysis of his recent publications reveals a strong focus on the genetic architecture of human facial features through genome-wide association studies (GWAS). His research spans multiple populations and examines various aspects of craniofacial morphology, including eyebrow thickness, eyebrow color, cranial vault shape, and the relationship between face and brain shape. His computational approach is evident in his development of analytical pipelines for genomic data. Eller actively seeks students interested in genetics, computational biology, bioinformatics, machine learning, and programming (Python, R) for research opportunities, noting that all his work is computational in nature rather than wet lab research.

Greg Aloupisمشاهده پروفایل

استاد

• Computational Geometry
• Algorithms
• Robotics
• +۴ مورد دیگر

Greg Aloupis is an Industry Professor in the Department of Computer Science and Engineering at New York University's Tandon School of Engineering. He holds a Ph.D. from McGill University (2005), with postdoctoral research at Carleton University (Canada), Université Libre de Bruxelles (Belgium), and Academia Sinica (Taiwan). He served as a Visiting Assistant/Associate Professor at Tufts University from 2013 to 2017. His research focuses on computational geometry, algorithms, robotics, and theoretical computer science, with notable contributions to reconfigurable robotics, geometric algorithms, and data depth analysis. Education: Ph.D. in Computer Science, McGill University, 2005 Postdoctoral research at Carleton University, ULB, and Academia Sinica His research interests include computational geometry applications in robotics, modular robot reconfiguration, geometric transformations, and algorithmic game theory. Over 50 publications in top venues such as Computational Geometry: Theory and Applications, Discrete & Computational Geometry, and Theoretical Computer Science. Courses taught include undergraduate and graduate algorithms courses (CS-2413, CS-6033) and discrete mathematics.

• Computer Vision
• Control Theory
• Biomedical Image Analysis
• +۵ مورد دیگر

Zhen Tang is an active researcher with a prolific publication record spanning from 2007 to 2025, primarily in computer science and engineering disciplines. Their work appears consistently in high-impact venues including IEEE Access, IEEE Transactions, and major conferences in computer vision and systems engineering. Research interests span computer vision, control theory, biomedical image analysis, machine learning, and multi-agent systems. Tang's work demonstrates a strong interdisciplinary approach, connecting theoretical control systems with practical applications in medical imaging, distributed computing, and emerging technologies like DNA computing. Recent publications show a growing interest in large language models, blockchain applications, and ethical considerations in technology design. The publication trends reveal an evolution from foundational work in image processing and pattern recognition (2010-2015) to more complex systems involving multi-agent control and deep learning (2016-2020), and most recently expanding into large language models, blockchain healthcare applications, and technology ethics. The research shows strong connections between theoretical control systems and practical applications across multiple domains. Zhen Tang has established long-term collaborations with researchers including Yanli Wan, Zhenjiang Miao, Wei Wang, and others, suggesting stable research group affiliations. The consistent publication output across 18 years indicates an established academic career with significant contributions to multiple subfields within computer science and engineering.

Russell C. Hardieمشاهده پروفایل

استاد

• Digital Signal Processing
• Image Processing
• Machine Learning
• +۳ مورد دیگر

Russell C. Hardie is a full-time Professor at the University of Dayton , holding positions in the Department of Electrical and Computer Engineering with joint appointments in Electro-Optics and Photonics and Bioengineering . His academic journey began with a B.S. in Engineering Science from Loyola College (1988), followed by M.S. and Ph.D. in Electrical Engineering from the University of Delaware (1990, 1992). Prior to joining the University of Dayton in 1993, he served as a Senior Scientist at Earth Satellite Corporation (now MDA Federal). Research Interests : Digital signal/image processing, medical imaging, super-resolution techniques, hyperspectral/infrared imaging, pattern recognition Key Awards : 2006 Alumni Award in Teaching (University of Dayton) 1998 Rudolf Kingslake Medal (SPIE) 1999 School of Engineering Excellence in Teaching 2002 IEEE Professor of the Year 1997 Epsilon Delta Tau Engineering Professor of the Year Recent Work : Focuses on machine learning applications for medical imaging (lung segmentation, nodule detection), atmospheric turbulence mitigation, and hyperspectral data analysis. His 15 most recent publications span topics from zero-shot chest X-ray analysis to methane plume detection and turbulence-corrected imaging systems. Contact: rhardie1@udayton.edu

Ravi Dhingraمشاهده پروفایل

استاد

• Advanced Heart Failure
• Cardiac Transplantation
• Heart Failure Treatment
• +۳ مورد دیگر

Ravi Dhingra, MD, MPH, is a Professor of Medicine and serves as the Section Head and Medical Director of the Advanced Heart Failure and Transplant Cardiology Program at Froedtert & Medical College of Wisconsin (MCW). His clinical expertise focuses on advanced heart failure, cardiac amyloidosis, and cardiac transplantation. He is affiliated with Froedtert Hospital and the Transplant Center, specializing in heart failure and transplant cardiology. Dr. Dhingra completed his M.B.B.S. from Armed Forces Medical College (1995), followed by residencies in Internal Medicine and ENT in New Delhi. He later pursued advanced training in preventive cardiology and research at Harvard Medical School, earning an MPH from the Harvard School of Public Health (2010). His cardiology fellowship was at Dartmouth-Hitchcock Medical Center, with specialization in Advanced Heart Failure and Transplant Cardiology at Tufts Medical Center. His research emphasizes optimizing donor-recipient matching for heart and dual-organ transplants, contributing to advancements in transplantation science. He holds leadership roles in national committees shaping heart failure and transplant guidelines. Awarded fellowships from the American College of Cardiology and American Heart Association, Dr. Dhingra is board-certified in Advanced Heart Failure, Transplant Cardiology, and Cardiovascular Disease. He speaks English, Hindi, and Punjabi and treats adult and senior patients.

• Spiking Neural Networks
• Brain-Computer Interfaces
• EEG Analysis
• +۴ مورد دیگر

Gang Pan is a Professor at Zhejiang University's College of Computer Science and Technology, where he leads research in neural networks, brain-computer interfaces, and neuromorphic computing. His work bridges computer science, neuroscience, and biomedical engineering, focusing on developing novel AI approaches inspired by biological neural systems. He maintains extensive collaborations with researchers including Shijian Li, Qian Zheng, and Huajin Tang. Professor Pan's research centers on spiking neural networks (SNNs) and their applications in brain-computer interfaces, medical diagnostics, and efficient neuromorphic computing. His work explores how SNNs can model biological neural processes while offering energy-efficient alternatives to traditional deep learning. Recent projects include EEG-based mental health diagnostics, neural decoding of visual perception, and battery-free neural recording systems. His approach integrates computational neuroscience with practical AI applications, particularly in healthcare contexts. Analysis of his 15 most recent publications reveals strong trends in neuromorphic computing, with particular emphasis on spiking neural networks for medical applications. His work spans from theoretical advances in SNN architectures to practical implementations in EEG analysis, mental health diagnostics, and neural interface hardware. The interdisciplinary nature of his research connects computer science, neuroscience, and biomedical engineering, with increasing focus on clinical applications of neural decoding technologies. Professor Pan actively mentors students and researchers, as evidenced by his numerous collaborative publications across multiple labs. His research is supported by significant grants enabling work on neuromorphic hardware, brain-computer interfaces, and medical AI applications. The consistent high-impact output demonstrates sustained funding support for his innovative research directions. His laboratory focuses on neuromorphic computing systems, brain-computer interface development, and neural signal processing. The research environment integrates theoretical AI development with practical hardware implementation, creating a pipeline from algorithm design to clinical application. The lab maintains strong connections with neuroscience researchers and medical professionals to ensure clinical relevance of their technological innovations.

Eraldo Ribeiroمشاهده پروفایل

دانشیار

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۹ مورد دیگر

Eraldo Ribeiro is an Associate Professor of Computer Science at Florida Institute of Technology (FIT), situated in the College of Engineering and Science's Department of Electrical Engineering and Computer Science. He holds a Ph.D. in Computer Vision from the University of York (2001), an M.Sc. in Computer Science from the Federal University of São Carlos (1995), and a B.Sc. in Mathematics from the Catholic University of Salvador (1992). His research focuses on computer vision, pattern recognition, and machine learning, with emphasis on 3-D shape modeling, image registration, human-motion recognition, and non-rigid deformation analysis. Current projects include underwater video mosaicing techniques and spatio-temporal crime pattern modeling. He serves as an associate editor for Machine Vision and Applications and Journal of Signal, Image, and Video Processing . Ribeiro’s recent work spans diverse applications including automated anuran call classification, pollen grain recognition via CNN-RNN hybrid models, and network-centric approaches to image annotation. His lab’s projects address challenges in medical imaging registration, social media analytics, and biofilm adhesion studies. He collaborates on interdisciplinary initiatives such as coral reef texture classification (using SVMs) and data science for urban crime analysis. Ribeiro’s contributions to computer vision education include teaching CSE4001 and CSE5683 courses at FIT.

Klara Kedemمشاهده پروفایل

استاد

• Computational Geometry
• Computer Vision
• Bioinformatics
• +۳ مورد دیگر

Klara Kedem is a Professor and former Chair of the Computer Science Department at Ben-Gurion University of the Negev, Israel. She holds a Ph.D. in Computer Science from Tel-Aviv University (1989). Her research focuses on computational geometry, bioinformatics, and computer vision, particularly in historical document analysis. Key contributions include the URMS method for robust shape matching and algorithms for degraded document processing. Professional roles include editorial board memberships at PeerJ Computer Science and Frontiers in Digital Humanities . She has led projects on historical Hebrew and Arabic manuscript analysis, collaborating with institutions like Cornell University. Notable achievements include winning the H-DIBCO 2010 competition for document binarization. Her work spans theoretical advancements (e.g., Voronoi diagrams, 3D structure comparisons) and practical applications (e.g., robot motion planning, protein structure alignment). Current projects involve cultural heritage digitization and pattern matching in ancient texts.

Bernd Bickelمشاهده پروفایل

استاد

• Computational Design
• Digital Fabrication
• Computer Graphics
• +۷ مورد دیگر

Bernd Bickel is a Full Professor for Computational Design at ETH Zurich, embedded in the Design++ research center. He holds a Master's degree from ETH Zurich and a PhD from ETH Zurich under Markus Gross. Previously, he was at IST Austria (2015–2023), Disney Research, and TU Berlin as a visiting professor. His research focuses on computational design, digital fabrication, and simulation, with applications in robotics, computer vision, and material science. Key interests include physics-based simulation, geometry processing, and interdisciplinary engineering. Notable awards include the Academy of Motion Picture Technical Achievement Award (2019), SIGGRAPH's Significant New Researcher Award (2017), and the EUROGRAPHICS Best PhD Thesis (2012). He leads the Computational Design Lab at ETH Zurich and collaborates with institutions like Inria Nancy on projects such as MFX team collaborations. His work spans academic contributions (over 50 publications) and industrial applications, including the FlexMaps Pavilion (First Prize at IASS 2019) and computational tools for 3D printing. He actively mentors PhD students and oversees grants like ERC Starting Grant 'Materializable'.

Kenneth Schaferمشاهده پروفایل

استاد

• Atomic, Molecular and Optical Physics
• Strong Field Physics
• Attosecond Science
• +۳ مورد دیگر

Kenneth Schafer is the Ball Family Distinguished Professor of Physics & Astronomy at Louisiana State University (LSU), where he leads theoretical research in strong-field and attosecond physics. His work focuses on ultrafast laser-matter interactions, particularly attosecond pulse generation and their application in imaging electron dynamics. He co-leads a research group with Mette Gaarde, combining atomic/molecular physics with high-performance computing to model processes like high-harmonic generation and ionization dynamics. Dr. Schafer earned his Ph.D. in Physics from the University of Arizona (1989). His research integrates time-dependent Schrödinger and Maxwell equations, emphasizing non-perturbative approaches and collaborations with leading experimental groups. Key areas include attosecond waveform control, charge migration in molecules, and developing computational tools like time-dependent density functional theory (TDDFT). His scientific contributions span over 150 publications, with recent work advancing attosecond transient absorption spectroscopy and the study of electron dynamics in complex molecules. He has pioneered methods to track charge migration using frequency-matched strobo-spectroscopy and contributed to attosecond pulse shaping at free-electron lasers (FERMI). Collaborations include experimental groups at JILA, FERMI, and international institutions, focusing on applications such as imaging core excitons in solids and controlling quantum trajectories. His research bridges theory and experiment, addressing fundamental questions in ultrafast physics while advancing technological tools for attoscience.

Zahra Montazeriمشاهده پروفایل

مدرس

• Computer Graphics
• Physics-based Rendering
• Material Modeling
• +۳ مورد دیگر

Zahra Montazeri is a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Manchester. Her research focuses on physics-based computer graphics, particularly photorealistic rendering and appearance modeling for complex materials like cloth, hair, and fur. She holds a PhD in Computer Science from the University of California, Irvine (UCI), and has industry experience at Disney Research, WetaDigital, Industrial Light & Magic (ILM), Pixar, and Luxion. **Education:** PhD in Computer Science (UCI, 2015–2021) M.Sc. in Computer Science (UCI, 2015–2017) B.Sc. in Computer Engineering (Sharif University of Technology, Iran, 2010–2014) **Research Interests:** Zahra’s work bridges academic and industrial applications, emphasizing practical and efficient rendering techniques. Her key areas include physics-based rendering, material modeling for fabrics, and virtual reality optimizations like foveated rendering. She collaborates with industry leaders such as WetaDigital and has contributed to movies like The Mandalorian and Avatar: The Way of Water . **Articles Trends:** Recent work focuses on texture-free cloth rendering, dynamic BTF synthesis, and neural-based material models. Her research often addresses computational efficiency while maintaining photorealism, with applications in film, gaming, and VR. **Awards:** Best Paper Award at EGSR (2023) Best Visuals Award at EGSR (2023) UCI Doctral Fellowship (2015) LightSpeed Venture Partners Summer Fellowship (2016) **Advising & Grants:** Advises four PhD students and has one alumni (David Petrescu). Her group actively collaborates with industry and explores applied research in rendering and virtual environments. She serves on program committees for PG, EGSR, and I3D. **Labs/Teams:** Leads a research group at Manchester focused on graphics and virtual environments, with interdisciplinary projects in computer vision, AI, and material science.