Nasir M. Rajpoot is a Professor in the Department of Computer Science at the University of Warwick, UK. His research focuses on computational pathology, medical image analysis, and deep learning applications in histology. He leads interdisciplinary projects integrating artificial intelligence with healthcare, particularly in cancer diagnostics and pathology workflows. Rajpoot’s work emphasizes developing robust algorithms for histology image analysis, including nuclear segmentation, tumor classification, and domain generalization in computational pathology. His contributions include the TIAToolbox, an open-source framework for tissue image analytics, and the CoNIC Challenge to advance nuclear detection and counting in histology images. He collaborates with clinicians and biologists to translate AI models into clinical practice, addressing challenges like tumor heterogeneity and staining variability. Rajpoot’s research spans colorectal, lung, and oral cancers, with a focus on predicting clinical outcomes via histological features and genomic data integration. Notable projects include the development of Handcrafted Histological Transformer (H2T) for unsupervised representations of whole slide images and the SAFRON framework for histology image synthesis. His work addresses domain adaptation, robustness evaluation, and explainability in AI-driven pathology systems.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۶۱-۷۵ از ۶٬۵۳۱ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
- Biophysics
- Cell Mechanics
- Glycobiology
- +۵ مورد دیگر
Jennifer Curtis is a Full Professor in the School of Physics at Georgia Institute of Technology and serves as an ADVANCE Professor for the College of Sciences. Her research focuses on the physics of cell-cell and cell-extracellular matrix interactions, particularly within glycobiology and immunobiology contexts. Dr. Curtis earned her Ph.D. in Physics from the University of Chicago (2002) and her B.A. in Physics from Columbia University (1997). Her research interests span biophysics at interfaces, quantitative modeling of collective cellular interactions, cell mechanics, motility, adhesion, and the role of bulky sugars in tissue organization. Her laboratory investigates collective and single cell migration, immunophage therapy (combining immune cells with phages to combat bacterial infections), and molecular biophysics of hyaluronan synthase. Recent work demonstrates applications in soft materials, biomaterials, tissue engineering, and advanced characterization techniques. Analysis of her publication record reveals consistent focus on glyco-biophysics and cellular mechanics, with increasing emphasis on microbial communities and therapeutic applications. Her work bridges physics, biology, and engineering through interdisciplinary approaches. Honors include the NSF CAREER Award (2010), Georgia Tech College of Sciences Faculty Mentor Award (2015), and Cullen Peck Award (2020). She serves on the Biophysical Journal editorial board. Dr. Curtis actively mentors students through the Georgia Tech Physics REU program (which she directs) and collaborates with biologists, chemists, and materials scientists. Her laboratory maintains strong partnerships with institutions including Emory University and international collaborators. The Curtis Lab operates the Cell Physics Laboratory in the Molecular Science & Engineering Building, utilizing advanced techniques including holographic optical tweezers, thermochemical nanolithography, and single-molecule imaging to study cellular mechanics and polymer physics at biological interfaces.
Ian Wilsonمشاهده پروفایل
پژوهشگر
- Medical Genetics
- Nephrology
- Genomics
- +۳ مورد دیگر
Dr. Ian Wilson is a researcher at Newcastle University with a focus on medical genetics, nephrology, and genomic analysis. His work spans genetic determinants of kidney diseases, mitochondrial disorders, and biomarker development. Notable contributions include studies on uromodulin genetics in African populations, copy-number variations in rare diseases, and kidney ciliopathies. He has collaborated extensively on projects involving genome sequencing, mitochondrial replacement therapy, and muscular dystrophy biomarkers. Wilson's research integrates computational tools like machine learning for predictive modeling in urolithiasis and employs advanced imaging techniques for disease progression monitoring. Key areas: Genetic epidemiology, renal genomics, mitochondrial DNA analysis Focus on translational applications: Biomarker development for kidney stones and muscular dystrophies Interdisciplinary collaborations in ophthalmology and orthopedics His publications reflect a commitment to advancing diagnostic accuracy and understanding complex genetic disorders through multi-omics approaches.
Kimberly A. Whitler serves as the Frank M. Sands Sr. Associate Professor of Business Administration at the University of Virginia's Darden School of Business. With nearly 20 years of industry experience in general management, strategy, and marketing roles within CPG and retailing sectors, she brings practical expertise to her academic work. Her career includes significant positions at Procter & Gamble, Aurora Foods, David's Bridal, and PetSmart, where she helped build $1B+ brands including Tide, Bounce, Downy and Zest. Dr. Whitler's educational background includes: B.A. in psychology and business administration from Eureka College MBA from the University of Arizona, Eller School of Business M.S. and Ph.D. from Indiana University, Kelley School of Business Whitler is an authority on marketing strategy, brand management, and marketing performance, with particular expertise in understanding how a firm's marketing performance is affected by its C-suite and board. Her research focuses on C-level marketing management challenges, digital marketing transformation, employer branding, and the emerging field of athlete branding through NIL (Name, Image & Likeness). She has authored over 350 articles as a Forbes senior contributor and published in top journals including Harvard Business Review, Journal of Marketing, and Journal of the Academy of Marketing Science. Her award-winning publications demonstrate a consistent progression from traditional brand management topics toward more strategic considerations of marketing's role at the executive and board levels. Recent work examines digital transformation, brand purpose, and the evolving CMO role, reflecting her deep understanding of how marketing strategy intersects with organizational leadership. Whitler has received numerous professional accolades: Ranked as a Top Influencer of CMOs Named Favorite Professor of Top MBA Students in Poets and Quants Winner of Darden's Morton Award in 2018 and 2021 Finalist for Journal of Marketing's 2018 MSI/Paul H. Root Award Winner of 2017 Robert D. Buzzell Best Paper award Winner of 2020 Sheth Foundation Award As an active consultant and speaker, Whitler has worked with numerous C-level organizations including Coca-Cola, McDonald's, U.S. Department of Defense, and Gartner. She has been cited over 3,600 times in major media outlets including Wall Street Journal, New York Times, and Bloomberg, establishing herself as a leading voice in marketing strategy. Her industry experience informs her teaching and research, creating a valuable bridge between academic theory and practical application. Whitler leads research initiatives focused on marketing leadership and brand strategy, often collaborating with industry partners to ensure practical relevance of her work. Her recent projects include examining the impact of marketers on corporate boards and developing frameworks for effective marketing technology implementation, positioning her at the forefront of strategic marketing research.
Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration
Lawrence Staib is Professor of Radiology and Biomedical Imaging, Biomedical Engineering, and Electrical Engineering at Yale University. He serves as Director of Undergraduate Studies in Biomedical Engineering and is a member of Yale's Bioimaging Sciences division, Image Processing & Analysis Group, Yale Biomedical Imaging Institute, and Yale-BI Biomedical Data Science Fellowship program. Dr. Staib earned his A.B. in Physics from Cornell University (1982), followed by a Ph.D. in Engineering and Applied Science from Yale University (1990), and completed a postdoctoral fellowship at Yale School of Medicine (1991). His research focuses on developing advanced medical image analysis methods using machine learning and model-based approaches. Key research areas include neuroimaging applications for autism spectrum disorder classification, cardiac imaging analysis for strain and motion assessment, prostate cancer diagnosis and risk mapping, and innovative techniques for medical image segmentation with limited labeled data. Dr. Staib's work emphasizes uncertainty estimation in deep learning models, multi-modal image registration, and domain adaptation techniques to improve clinical decision support systems. His recent publications demonstrate a strong trend toward developing interpretable AI models for clinical applications, with particular emphasis on fMRI analysis for neurological conditions, cardiac motion analysis, and prostate cancer diagnosis. His work frequently addresses the challenge of limited labeled data in medical imaging through innovative self-supervised, semi-supervised, and few-shot learning approaches. Fellow of the American Institute for Medical and Biological Engineering (AIMBE) (2015) Distinguished Investigator Award from the Academy for Radiology & Biomedical Imaging Research (2017) MICCAI Fellow (2022) Medical Image Analysis Second Best MICCAI Paper Award (2005) ASNR Cum Laude Scientific Exhibit Award (2003) Dr. Staib serves on the editorial board of Medical Image Analysis and as Associate Editor of IEEE Transactions on Biomedical Engineering. His research is supported by NIH grants including the Autism Center of Excellence program. He leads the Image Processing & Analysis Group within Yale's Bioimaging Sciences division, collaborating extensively with James Duncan, John Onofrey, Xenophon Papademetris, and other Yale researchers on applications spanning neuroimaging, cardiology, and oncology. Current projects focus on developing robust AI models for clinical decision support with emphasis on uncertainty quantification and interpretability.
Matloob Khushiمشاهده پروفایل
مدرس ارشد
Dr. Matloob Khushi serves as a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 25 years of combined academic and industry experience, his work bridges theoretical AI advancements with practical applications in finance, healthcare, and public health domains. His research has established significant collaborations with international banks, healthcare institutions, and technology startups. Dr. Khushi earned his PhD in AI and Data Science from the University of Sydney, developing novel algorithms for genomic data analysis. His postdoctoral research at the Children's Medical Research Institute (2014-2017) pioneered AI-based diagnostic tools for medical condition detection. More recently, he developed bioinformatics tools for environmental assessment under a UKRI NEC grant. Research Focus FinTech Innovation : Creator of the SS Ratio (incorporating volatility and drawdown sensitivities), advanced portfolio optimization models, and synthetic data generation techniques for fraud detection and credit risk assessment Bioinformatics Leadership : Developer of AI tools for genomic analysis and early cancer detection, featured in SBS News and The Daily Telegraph Public Health NLP : Architect of systems for vaccine misinformation detection, mental health monitoring, and health surveillance on social media His publication portfolio shows consistent growth from foundational bioinformatics work to current multimodal AI applications, with increasing interdisciplinary collaboration across finance and healthcare sectors. Awards and Recognition Ranked among Stanford/Elsevier's top 2% of global AI scientists Recipient of Best Paper Awards from IEEE Transactions on Computational Social Systems and PeerJ Media recognition for cancer detection research by major news outlets Mentorship and Teaching Dr. Khushi has supervised six PhD candidates to completion and over 100 postgraduate dissertations. He teaches CS3002 Artificial Intelligence and mentors students in Final Year Projects. His supervision focuses on Deep Learning/NLP for FinTech prediction and Public Health Surveillance applications, emphasizing practical implementation of theoretical concepts.
Jonas Anderegg is a Lecturer at the Department of Environmental Systems Science, ETH Zurich. He holds a PhD and MSc from ETH Zurich in Agricultural Sciences. His research focuses on crop disease phenotyping, precision agriculture, and host-pathogen interactions. Current projects include automated image analysis for disease detection and quantification of Zymoseptoria tritici under field conditions. He has held postdoc positions in Plant Pathology (Institute of Integrative Biology) and Crop Science (Institute of Agricultural Sciences) at ETH Zurich. His work involves developing scalable imaging and deep learning methods for field phenotyping, with applications in quantitative resistance assessment and crop disease management. Education: PhD, Group of Crop Science, ETH Zurich (2016-2020) MSc in Agricultural Sciences, ETH Zurich (2015) Research interests emphasize high-throughput phenotyping, automated disease detection, and integrating imaging technologies into agricultural practices. Key contributions include datasets like SYMPATHIQUE and FIP 1.0, which provide foundational resources for crop disease research. Grants and advising: While no formal student advisees are listed, his postdoc roles and collaborative projects likely involve mentoring junior researchers. His work aligns with ETH Zurich's focus on sustainable agriculture and technological innovation in plant sciences. Labs and teams: Active member of the Crop Disease Phenotyping group, leveraging UAVs, thermal imaging, and deep learning for field-scale monitoring of crop health and senescence dynamics.
Darryl Dickersonمشاهده پروفایل
استادیار
- Biomedical Engineering
- Mechanical Characterization of Biological Interfaces
- Bioinspired Materials Design
- +۴ مورد دیگر
Dr. Darryl Dickerson is an Assistant Professor in the Department of Mechanical and Materials Engineering at Florida International University (FIU), part of the College of Engineering. His research focuses on mechanical characterization of biological interfaces, design of bioinspired materials, and advancing inclusive engineering education practices. He holds a Ph.D. (details not explicitly provided in text). Research Interests: Dr. Dickerson’s work bridges biomechanics and biomaterials engineering with social equity in education. Key areas include: Mechanical properties of biological interfaces (e.g., bone-cartilage junctions) Development of biomaterials for tissue repair using 3D printing and electrospinning Anti-marginalization strategies in engineering education, particularly for Black and Brown students Publications Trends: Recent work emphasizes dual themes: (1) Biomedical innovation through advanced material fabrication and (2) Inclusive pedagogy addressing systemic inequities in STEM education. Notable contributions include scaffold designs for osteochondral repair and frameworks for reducing microaggressions in team-based learning. Grants and Advising: No specific grants or advisees listed in the provided text. His work appears to be grant-funded through NIH/National Science Foundation pathways common in biomaterials and education research. Labs and Teams: While not explicitly stated, his research likely involves collaborations with FIU’s Center for Engineering and Computing’s diversity initiatives and biomaterials labs focusing on tissue engineering applications.
- Complex Dynamics
- Biophysics
- Statistical Physics
- +۲ مورد دیگر
Jeff Urbach is a Professor in the Department of Physics at Georgetown University and Vice Provost for Research. He earned a B.A. in Physics from Amherst College (1985), a Ph.D. from Stanford University (1993), and completed a postdoctoral fellowship at the University of Texas at Austin (1993-1996). He joined Georgetown in 1996, advancing to Professor in 2006, and held leadership roles including Department Chair (2000-01, 2004-07, 2016-20) and Director of the Institute for Soft Matter Synthesis and Metrology (2011-15). Education: B.A. in Physics (Amherst College, 1985); Ph.D. in Physics (Stanford University, 1993) His research focuses on complex dynamics and biophysics , applying statistical physics, nonlinear dynamics, and advanced imaging to systems like granular materials, cytoskeletal proteins, and neuronal migration. Current work emphasizes quantitative modeling of multifaceted, interacting systems through computer simulations and experimental analysis. Scientific awards include the Sloan Foundation Fellowship and the Presidential Early Career Award for Scientists and Engineers . Research funding has been secured from the National Science Foundation, National Institutes of Health, NASA, Air Force Office of Scientific Research, NIST, and other foundations.
- Theoretical Computer Science
- Automata Theory
- Logic
- +۶ مورد دیگر
Manfred Droste is a Professor at the Institute of Computer Science of the University of Leipzig, where he leads the Research Group on Automata and Formal Languages. He serves as Director of the Graduate Centre Mathematics, Computer Science and Natural Sciences and is Vice-speaker of the DFG-Research Training Group Quantitative Logics and Automata. His academic career spans decades of research and leadership in theoretical computer science and algebra. Prof. Droste's research focuses on theoretical computer science, particularly automata theory, logic, algebraic models for concurrent systems, and domain theory. In algebra, his interests include model theory, automorphism groups, and ordered algebraic structures. His work bridges theoretical foundations with practical applications in formal language theory and quantitative systems. His extensive publication record demonstrates a consistent focus on weighted automata, formal languages, and their logical characterizations. Over the years, his research has evolved to address increasingly complex quantitative models, with recent work focusing on weighted complexity classes, weighted linear dynamic logic, and decidability boundaries for weighted automata. Prof. Droste has received significant recognition including election to Academia Europaea, an honorary doctorate from Immanuel Kant Baltic Federal University, and fellowship in the Asia-Pacific Artificial Intelligence Association. These honors reflect his substantial contributions to theoretical computer science. He has supervised numerous PhD students including Dietrich Kuske, Paolo Boldi, and Karin Quaas, many of whom have become prominent researchers. His extensive grant portfolio includes multiple DFG projects on weighted automata and international collaborations through DAAD funding. Prof. Droste leads a vibrant research team including Andrea Hesse, Karin Quaas, Erik Paul, and others. He has organized the international workshop series "Weighted Automata: Theory and Applications" since 2002, fostering global collaboration in this specialized field.
Xian Wuمشاهده پروفایل
استادیار
Xian Wu, Ph.D., serves as a Research Assistant Professor in the Department of Pharmacology & Toxicology at East Carolina University's Brody School of Medicine. Her research leverages human stem cell models to investigate developmental vulnerabilities to environmental contaminants in cardiovascular and neural systems, with emphasis on epigenetic mechanisms and disease modeling. Dr. Wu's academic credentials include: Ph.D. in Toxicology from the University of Georgia M.S. in Biomedicine from East China Normal University B.S. in Biotechnology from Anhui University Her postdoctoral training comprised a Fellowship at the National Institute of Environmental Health Sciences and an ORISE Fellowship at the U.S. Food and Drug Administration. Research focuses on creating human stem cell-derived organoid systems to model developmental toxicology, particularly examining cardiac and neural development under chemical exposure. The laboratory employs fluorescence reporter systems and RNA-seq to identify critical vulnerability windows during early development, with recent work targeting Parkinson's disease mechanisms through dopaminergic neuron models and cardiac fibrosis via advanced organoids. Methodological innovations include high-content imaging for neurogenesis quantification and epigenetic pathway analysis. Publication trends (2016-2025) demonstrate consistent advancement in stem cell-based toxicology testing, with increasing emphasis on micro/nanoplastics risk assessment, arsenic neurotoxicity mechanisms, and doxorubicin cardiotoxicity modeling. The work bridges environmental health, epigenetics, and regenerative medicine through interdisciplinary approaches. Scientific recognition includes: 2025 SPARC Award (ECU) 2024 Top Abstract Award (Developmental Origins of Health and Disease Society) 2024 NIEHS P30 Center Travel Award 2023 ECU Research and Creative Activity Award Dr. Wu actively mentors graduate researchers including Ph.D. candidate Cate Duncan and M.S. students Kamilah Muhammad and Bailey Skeen, alongside undergraduate Bryce Tilghman. Former trainees McKyrah Brown and Monica Cross completed honors theses in the laboratory. Current grants include ECU's SPARC Award funding stem cell model development for environmental contaminant testing. The BSOM 6S-11 laboratory maintains specialized capabilities in cardiac and cerebral organoid generation, fluorescence-based toxicity screening, and RNA-seq epigenetic analysis. Collaborative networks include the National Institute of Environmental Health Sciences and ECU's Center for Human Health and the Environment, supporting translational research on developmental vulnerability periods.
Yize Zhaoمشاهده پروفایل
دانشیار
- Biostatistics
- Data Science
- Neuroimaging Analysis
- +۷ مورد دیگر
Yize Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health and an Associate Professor in the Department of Biomedical Informatics & Data Science at Yale University. She holds affiliations with multiple Yale research centers including the Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute, Yale Center for Brain and Mind Health, and Yale Computational Biology and Bioinformatics. Dr. Zhao's research focuses on developing statistical and AI methods to analyze large-scale complex biomedical data including medical imaging, genomics, and electronic health records. Her methodological expertise spans Bayesian statistics, feature selection, predictive modeling, data integration, missing data analysis, and network analysis. Her research interests span multiple biomedical domains with a strong focus on mental health, psychiatry, neurodegenerative diseases, and aging. Her recent work includes brain-to-behavior modeling, multi-layer biomedical networks, imaging genetics and genomics, and the integration of multi-modal biomedical data with real-world data. Dr. Zhao's work has resulted in numerous high-impact publications, with recent research focusing on Alzheimer's disease, brain network analysis, and advanced statistical methods for neuroimaging. Her publications show a strong trend toward integrating multi-modal data sources and developing sophisticated statistical approaches to address complex biomedical questions. Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS) COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS) YSPH Investigator Research Award Yale Alzheimer's Disease Research Center Research Scholar Award Elected member of the International Statistical Institute Dr. Zhao serves as an Associate Editor for Biometrics and is a standing member of the NIH Biodata Management and Analysis (BDMA) study section. Her research is supported by multiple NIH grants, highlighting the significance and impact of her work in biostatistics and biomedical data science.
Dr. Vadim Backman is the Sachs Family Professor of Biomedical Engineering and Medicine at Northwestern University's McCormick School of Engineering and Applied Sciences and Feinberg School of Medicine. He holds additional roles as Professor of Medicine (Hematology/Oncology) and Biochemistry and Molecular Genetics, Associate Director of Research Technology and Infrastructure at the Robert H. Lurie Comprehensive Cancer Center, and Director of the Center for Physical Genomics and Engineering. He earned his Ph.D. in Medical Engineering from Harvard-MIT and M.S./B.S. in Physics from St. Petersburg Polytechnic Institute. His research focuses on physical and biological science intersections, developing nanoscale imaging and computational technologies to study chromatin dynamics and their role in disease. Key areas include cancer diagnostics/therapeutics, chromatin engineering, and genome nanoimaging. Dr. Backman has published over 230 papers, holds 20+ patents, and leads large-scale projects like NCI Bioengineering Research Partnerships. Education: Ph.D. (Harvard-MIT), M.S. (MIT), M.S./B.S. (St. Petersburg Polytechnic Institute) Affiliations: PhD Programs in Applied Physics and Interdisciplinary Biological Sciences Research emphasizes chromatin's role in disease, with clinical translation for diagnostics and therapy. His lab develops technologies like nano-CHIA and ChromSTEM, advancing understanding of genomic organization and epigenetic regulation. Awards include the Cozzarelli Prize and MIT Technology Review's Top 100 Innovators. Awards: Cozzarelli Prize (2017), AIMBE Fellowship (2009), NSF CAREER Award (2003) Grants and collaborations include managing multi-investigator projects and co-founding biotech companies. Courses taught: BME 302 (Quantitative Systems Physiology), BME 429 (Advanced Physical and Applied Optics).
Jianhua Xingمشاهده پروفایل
دانشیار
- Biophysics
- Systems Biology
- Cell Biology
- +۷ مورد دیگر
Jianhua Xing is an Associate Professor in the Department of Physics & Astronomy at the University of Pittsburgh , affiliated with the Dietrich School of Arts and Sciences . His research focuses on applying physics-based approaches to study biological systems, particularly cell phenotypic transitions (CPTs) and their underlying dynamics. He integrates quantitative single-cell measurements with computational and theoretical analyses to understand how cells transition between stable states. Key research areas include: Nonequilibrium systems and rate theories for biological transitions Single-cell trajectory analysis and live-cell imaging Epithelial-mesenchymal transition (EMT) dynamics Gene regulatory networks and stochastic processes Biological applications of dynamical systems theory Recent work highlights the coupling between EMT and cell cycle arrest, leveraging machine learning frameworks (e.g., LivecellX ) for high-resolution imaging analysis. His lab also explores chromosomal dynamics and mechanotransduction in stem cell aging. Publications emphasize data-driven modeling and theoretical insights, with contributions to frameworks like GraphVelo and Graph-Dynamo for inferring cellular state transitions. Collaborative efforts bridge physics, biology, and computational science to address fundamental biological questions. No awards or grants are explicitly listed in the provided texts. His research group focuses on advancing systems biology through interdisciplinary methods, with a lab dedicated to quantitative analysis of cellular processes.