جست‌وجوی استاد و پژوهشگر

Gabriel Blecherمشاهده پروفایل

مدرس ارشد

• point-of-care ultrasound
• efficient use of diagnostic testing in emergency medicine
• qualitative analysis of the patient experience
• +۳ مورد دیگر

Gabriel Blecher is an Emergency Physician and Clinical Director of Emergency at Peninsula Health, with additional roles at Cabrini Hospital Emergency Department and My Emergency Doctor (telehealth provider). He holds a ORCID and is affiliated with Monash University as a Senior Lecturer in the Faculty of Medicine . Education : Master of Science in Epidemiology from the University of Ottawa (Canada) Research Interests focus on point-of-care ultrasound , diagnostic testing efficiency , and patient experience analysis . His work spans emergency telehealth , implementation science , and critical care protocols , with recent studies on COVID-19 prognosis and multimedia distraction strategies . Scientific Awards : Monash Health Emerging Researcher Fellowship (2014) Projects : Leading two initiatives funded by the Australian Department of Health and Aged Care, including "Just Say No to the Just in Case Cannula" (2023–2029) and a digital health intervention for pathology feedback (2023–2026).

Kai Shimagakiمشاهده پروفایل

پژوهشگر

• HIV research
• virology
• immunology
• +۴ مورد دیگر

Kai Shimagaki is a Postdoctoral Associate at the University of Pittsburgh. His research focuses on HIV-1 evolution, coevolutionary processes between viruses and antibodies, and quantitative analysis of genetic interactions. He holds a Ph.D. from Sorbonne University (formerly Pierre et Marie Curie University), where his work centered on protein structure prediction and pathogen-immune system interactions. Education: Ph.D. in Computational Biology, Sorbonne University Research Interests: Quantitative analysis of viral evolution and immune system dynamics Computational modeling of fitness landscapes and epistasis Development of algorithms for deep mutational scanning and protein sequence analysis His work bridges virology, immunology, and computational methods to understand HIV adaptation mechanisms. Publications Overview: Recent work emphasizes HIV evolution modeling, epistasis detection, and computational tools for genetic fitness prediction. Key methods include Bézier interpolation, Boltzmann machine models, and higher-order covariance analysis. Scientific Awards: None listed. Advising & Funding: Supported by the Honjo International Scholarship Foundation during his Ph.D. No current advising roles noted. Labs/Teams: Affiliation details not specified in text.

• Biophysics
• Microbial Physiology
• Gene Expression Dynamics
• +۳ مورد دیگر

Jing He is a part-time faculty member in the Department of Physics & Astronomy at the University of Pittsburgh's Dietrich School of Arts and Sciences. Their research focuses on interdisciplinary studies at the interface of biophysics, bacterial physiology, and computational modeling. Dr. He's work explores gene expression dynamics in bacterial cells, mechanisms of bacterial motility, and the application of machine learning in biochemical systems analysis. Education: PhD in Physics under the advisement of Dr. Xiao-lun Wu. Research interests include quantitative analysis of gene expression variability, bacterial swimming behavior modulation by chemotactic proteins, and development of predictive models for metabolic and motility systems. Notable findings include the discovery of amino acid starvation-induced growth arrests and the role of CheY protein in Vibrio alginolyticus reorientation dynamics. Research trends in their publications emphasize machine learning applications in drug discovery, enzyme kinetics modeling, and SARS-CoV-2 molecular mechanisms. Techniques employed include in silico screening, molecular dynamics simulations, and advanced data analysis methodologies. Collaborations with Prof. Fu have enabled theoretical modeling of flagellar dynamics in polar bacteria. Key contributions include novel methods for predicting catalytic constants using neural networks, optimization of pharmacokinetic modeling for antimalarial drugs, and analysis of viral spike protein mutations. Current work bridges microbiology, physics, and computational biology to address fundamental questions in cellular behavior and drug development.

Paul Jenkinsمشاهده پروفایل

استاد

• Monte Carlo methods
• Inference from stochastic processes
• Mathematical population genetics
• +۳ مورد دیگر

Paul Jenkins is a Professor in the Departments of Statistics and Computer Science at the University of Warwick, where he conducts research at the intersection of statistical methodology, computational biology, and population genetics. He is an active member of the Warwick Machine Learning group, focusing on probabilistic AI and computational statistical methods. His research centers on Monte Carlo methods, inference from stochastic processes, mathematical population genetics, and machine learning applications. Professor Jenkins develops sophisticated statistical techniques for analyzing genetic data, with particular emphasis on Wright-Fisher diffusion processes, coalescent theory, Bayesian inference methods, and recombination rate estimation. His work bridges theoretical statistical development with practical applications in evolutionary biology and genomic epidemiology. Professor Jenkins teaches advanced courses including ST341 Statistical Genetics, ST418 Statistical Genetics with Advanced Topics, and ST407 Monte Carlo Methods. He currently supervises undergraduate and Masters projects through modules CS350, ST415, ST421, and ST955, though he notes he cannot accept undergraduate projects or internships from outside Warwick. His publication record demonstrates consistent high-impact research output, with numerous publications in top-tier journals including Annals of Applied Probability , Genetics , PLoS Genetics , and Bioinformatics . Recent work shows increasing interdisciplinary reach, with applications spanning from viral evolution (SARS-CoV-2 recombination) to healthcare analytics (multimorbidity modeling). Warwick Machine Learning Group: Active contributor to probabilistic AI research initiatives Current recruitment: Seeking postdoctoral Research Fellow in Probabilistic AI

Paul J. Hurtadoمشاهده پروفایل

دانشیار

• Population Ecology
• Infectious Disease Ecology
• Dynamical Systems
• +۳ مورد دیگر

Paul J. Hurtado is an Associate Professor in the Department of Mathematics and Statistics at the University of Nevada, Reno (UNR), and a faculty member of the Ecology, Evolution and Conservation Biology (EECB) graduate program. Formerly affiliated with the Mathematical Biosciences Institute (MBI) and Aquatic Ecology Laboratory (AEL) at Ohio State University. Education: PhD in Applied Mathematics (Cornell University, 2012), MS in Applied Mathematics (Cornell University, 2007), and dual BS degrees in Mathematics and Biology/Chemistry from the University of Southern Colorado (2003). Research focuses on applying mathematical models to ecological and epidemiological questions, particularly population ecology, infectious diseases, and immune-pathogen dynamics. Techniques include dynamical systems, stochastic processes, and statistical methods. Key contributions involve generalizing the linear chain trick to model complex biological systems using ODE frameworks. Advises multiple graduate and undergraduate students in interdisciplinary projects across mathematics, statistics, and ecology. Current research spans viral hotspots in caterpillars, feedlot bloat detection in cattle, and amphibian pathogen dynamics.

• Mass Spectrometry
• Molecular Imaging
• Biomedical Engineering
• +۵ مورد دیگر

Professor Ron Heeren is Distinguished Professor and Limburg Chair at Maastricht University, where he serves as Scientific Director of the Maastricht MultiModal Molecular Imaging Institute (M4I) and heads the Imaging Mass Spectrometry division. Appointed as a Hans Fischer Senior Fellow at the Technical University of Munich (TUM-IAS) in 2020, his career spans academic leadership roles at Utrecht University (2001) and research group leadership at FOM-AMOLF (1995-2015). Education: PhD in Technical Physics (1992, University of Amsterdam) Professional Roles: Founding member of international mass spectrometry societies, editorial board member for peer-reviewed journals Research Interests: Center on mass spectrometry-based molecular imaging for biomedical applications. His work bridges fundamental physics, chemistry, and biology with clinical translation, developing hyperspectral imaging technologies for tissue analysis in diseases like cancer, osteoarthritis, and metabolic disorders. Key areas include local immune-metabolism, non-covalent protein complexes, and 3D host-pathogen interface mapping. Publications & Impact: Over 300 peer-reviewed works, H-index 57. His articles demonstrate technological innovations in MALDI-MSI, lipidomics, and clinical applications across oncology, immunology, and food science. Scientific Awards: Recognized with the Thomson Medal (2020) for international MS contributions, NWO Valorization Prize (2019), Brightlands Convention Award (2019), and multiple early-career recognitions.

Matthew Sherman Brownمشاهده پروفایل

استاد

• Medical Imaging
• Artificial Intelligence in Radiology
• Quantitative CT Analysis
• +۶ مورد دیگر

Matthew Sherman Brown is a Professor in the Department of Radiological Sciences at the David Geffen School of Medicine, UCLA . His work bridges medical imaging , artificial intelligence , and clinical translation to advance diagnostic and therapeutic strategies in pulmonary diseases, oncology , and radiology . Research Focus : Quantitative CT analysis for lung diseases (e.g., IPF, emphysema), AI-driven medical imaging, image harmonization, and radiomics. Grants : NIH R01HL153964 (COPD treatment planning), NIH U01CA181156 (CT response assessment), and NIH R01CA088973 (lung cancer screening). Recent publications highlight his leadership in integrating deep learning and domain knowledge to develop tools like SimpleMind for explainable AI and CT-Norm for image harmonization. His work on quantitative fissure integrity scores and lung fibrosis progression models has transformed treatment planning in pulmonary conditions. Clinical Impact : Key contributions to AI adoption in radiology workflows, improving emphysema valve response prediction, and standardizing CT protocols for reproducibility.

Eleazar Eskinمشاهده پروفایل

استاد

• Computational Genomics
• Bioinformatics
• Genetics
• +۵ مورد دیگر

Eleazar Eskin is a Professor at the University of California Los Angeles (UCLA) with appointments in Computer Science , Human Genetics , and Computational Medicine . He is affiliated with the Henry Samueli School of Engineering and Applied Science and contributes to interdisciplinary research bridging computational methods with biomedical applications. PhD in Computer Science, Stanford University Postdoctoral Fellowship, University of Southern California Eskin’s research focuses on computational genomics , statistical genetics , and machine learning applications in medicine . He develops algorithms for genome-wide association studies (GWAS) , structural variant detection , and multi-omics data integration , addressing challenges in population stratification , pleiotropy , and epigenetic regulation . His recent publications span 2023–2025 , emphasizing machine learning in clinical diagnostics , computational reproducibility , and genetic mechanisms in complex traits . Collaborative projects include the GTEx Consortium and UCLA’s Computational Pan-Genomics initiatives. Scientific awards include the NSF CAREER Award , Alfred P. Sloan Fellowship , and NIH Director’s Pioneer Award . He leads NIH-funded programs like R25GM135043 (Computational Genomics Summer Institute) and R25NS115554 (Undergraduate Neurogenomics Training). Eskin mentors trainees through NIH T32 grants and co-developed methods like MARS (allelic heterogeneity), PLEIO (pleiotropy analysis), and BayesCCE (epigenetic modeling). His work impacts SARS-CoV-2 testing , neurodevelopmental disorders , and precision medicine .

Blair Strangمشاهده پروفایل

مدرس

• Virology
• Antiviral Therapeutics
• Human Cytomegalovirus (HCMV)
• +۶ مورد دیگر

Dr. Blair Strang is a Lecturer in Virology at St George's, University of London, where he has worked since 2013. His research focuses on human cytomegalovirus (HCMV) replication and pathogenesis, with an emphasis on developing antiviral therapeutics. University of Glasgow (BSc, 1995-1999) University College London (PhD, 1999-2003) MRC Virology Unit (Postdoc, 2003-2006) Harvard Medical School (Postdoc, 2006-2013) Dr. Strang's research includes high-throughput screening for antiviral compounds, machine learning applications in drug discovery, and investigating host cell proteins as HCMV drug targets. His work extends to DNA virus infections in placental tissue and clinical studies on HCMV shedding during pregnancy. He collaborates with researchers from institutions including Harvard Medical School, University College London, King's College London, and biotech companies like Merck and LifeArc. Funding sources include Medical Research Council (MRC), National Institutes of Health (NIH), Wellcome Trust, and industry partners. Supervises PhD, MRes, MSci, and BSc/iBSc students Teaches virology to MPharm and other advanced students Administers Infection & Immunity research projects Lectures at SGUL Summer School since 2018

Chongle Panمشاهده پروفایل

دانشیار

• Bioinformatics
• Machine Learning
• Proteomics
• +۵ مورد دیگر

Chongle Pan is an Associate Professor of Microbiology and Computer Science at The University of Oklahoma. He holds a Ph.D. from the University of Tennessee (2006) and a B.S. from East China Normal University (2001). His research bridges computational and biological sciences, focusing on explainable machine learning, parallel computing for biomedical informatics, human microbiome dynamics, and environmental microbiome modeling. Key projects include studying probiotic/prebiotic impacts on human health and developing mechanistic models for wetland sediment communities' greenhouse gas emissions. His lab employs proteomic stable isotope probing, integrated -omics, and synthetic microbiome approaches. Research interests include computational biology, proteomics, and environmental microbiology. Notable contributions include genome-resolved proteomic studies of soil microbial communities and cloud computing-based proteomics analysis tools like CloudProteoAnalyzer. Collaborations involve institutions like Lawrence Berkeley National Lab and Pacific Northwest National Lab. Publications highlight advancements in metaproteomics, microbial community modeling, and biomedical imaging technologies. His work addresses environmental bioremediation challenges and computational solutions for genomic data analysis. The Pan Lab's research emphasizes interdisciplinary innovation at the interface of computer science and life sciences. Grants and funding sources support his work in computational biology and microbial ecology. No specific awards are listed, but his extensive publication record reflects sustained academic impact. Students are advised through collaborative interdisciplinary programs combining computer science and microbiology disciplines.

Eyal Bigalمشاهده پروفایل

پژوهشگر

• Marine Biology
• Conservation Biology
• Ecology
• +۳ مورد دیگر

Eyal Bigal is a Postdoctoral Scholar at Stanford University's Hopkins Marine Station, focusing on marine biology and conservation. His research integrates ecological, behavioral, and technological approaches to understand marine ecosystems and address conservation challenges. He specializes in studying sharks, rays, and marine mammals, particularly their habitat use, population dynamics, and health. Research interests include shark behavior and thermoregulation, dolphin population monitoring, viral and bacterial pathogens in marine mammals, and the application of technologies like UAVs and acoustic tracking for ecological surveys. His work emphasizes conservation solutions for coastal and open-ocean ecosystems. Key projects involve analyzing shark aggregations, characterizing nursery habitats for elasmobranchs, and investigating human impacts on marine species. Collaborative efforts with interdisciplinary teams advance methodologies for species identification, habitat management, and disease surveillance in marine environments. Publications highlight innovations in acoustic tracking, microbiome studies of sharks, and long-term dolphin population assessments. His research contributes to evidence-based policies for marine spatial planning and biodiversity protection in the Eastern Mediterranean and beyond.

Michael Brownمشاهده پروفایل

پژوهشگر ارشد

• Prostate Cancer Metastasis
• Bone Metastasis Mechanisms
• Cancer Stem Cell Biology
• +۴ مورد دیگر

Dr. Michael Brown is a Research Fellow at the Division of Cancer Sciences, University of Manchester, leading the scientific research arm of the Genito Urinary Cancer Research Group. His primary focus is prostate cancer metastasis mechanisms, particularly bone-directed metastasis and the role of polyunsaturated fatty acids. He collaborates with the Manchester Institute of Biotechnology and School of Chemical Engineering. Key areas include cancer stem cell biology, biomarker development, and molecular diagnostics. Education: Ph.D. in Molecular Virology, University of Reading (1995) B.Sc. Microbiology, University of Leeds (1991) Research Interests: Prostate cancer metastasis, lipid signaling in cancer, biomarker discovery, renal/bladder cancer stem cells. His work contributes to UN Sustainable Development Goals related to health and innovation. Advising & Grants: Supervised 13+ theses on topics like EphA2 biomarker validation, lipid effects on prostate cancer, and MALAT1 in cancer metabolism. Active in collaborative projects funded by Cancer Manchester Research Centre. Labs/Teams: GenitoUrinary Cancer Research Group (led by Prof. Noel Clarke), collaborations with analytical spectroscopy teams at MIB.

Shibu Yoosephمشاهده پروفایل

استاد

• Computational Biology
• Genomics
• Bioinformatics
• +۵ مورد دیگر

Shibu Yooseph is the Kravis Professor of Integrated Sciences in the Kravis Department of Integrated Sciences , specializing in computational biology, bioinformatics, and microbiome research. His career includes roles as Professor of Computer Science at the University of Central Florida (2016–2023), Senior Director of Bioinformatics at Human Longevity Inc., and leadership positions at the J. Craig Venter Institute, where he contributed to major genome projects like the Human Genome and Sorcerer II expeditions. Education: Ph.D. in Computer and Information Science (1997), University of Pennsylvania; B.Tech. in Computer Science (1992), Indian Institute of Technology, Banaras Hindu University. Research Focus: Algorithm design, machine learning, computational genomics, and microbiome analysis. Key projects include microbial network modeling, host-microbiome interactions, and applications in disease (e.g., inflammatory bowel disease, colorectal cancer). His work leverages computational tools like GRASP2 and SFA-SPA for metagenomic data analysis. Publications Trends: Recent work emphasizes oral and gut microbiome dynamics in clinical settings, microbial network inference , and computational methods for genomic assembly . Contributions span biotechnology, environmental microbiology, and translational medicine. Awards: Not explicitly listed in available texts. Leadership & Grants: Directed informatics teams at multiple institutions, led the Genomics and Bioinformatics Cluster at UCF, and contributed to major NIH-funded projects. Grants and funding details are not detailed in the provided text. Labs & Teams: Affiliated with the Kravis Department’s integrated sciences team and previously with the J. Craig Venter Institute’s informatics group.

Francesco Ferraroمشاهده پروفایل

مدرس

• Respiratory Physiology
• Geriatric Rehabilitation
• Public Health
• +۵ مورد دیگر

Francesco Ferraro is a Lecturer in Sport Therapy and Rehabilitation affiliated with the College of Science and Engineering. His research focuses on respiratory muscle training interventions, long-term post-viral syndromes (particularly Long-COVID), geriatric rehabilitation, and educational strategies during pandemics. He has published extensively on topics such as the efficacy of inspiratory muscle training in older adults, the impact of Long-COVID on quality of life, and the role of artistic sports in improving academic outcomes among vulnerable youth. His work integrates clinical practice with technological innovation, as seen in studies exploring AI applications in clinical vision and embodied cognition frameworks. Ferraro has conducted randomized controlled trials evaluating interventions like Tai Chi for respiratory health and Latino dance for child self-efficacy. He collaborates internationally, with studies in Pakistan, China, and across European countries. Key areas of contribution include: Developing rehabilitation protocols for orthopedic recovery through respiratory training Advocating for redefined biomarker standards in post-COVID patient assessment Designing pedagogical interventions to address pandemic-related educational gaps Ferraro’s research often bridges clinical, educational, and social domains, emphasizing holistic health strategies for marginalized groups such as left-behind children and individuals with chronic conditions.

• Computational Chemistry
• Medicinal Chemistry
• Computer-Aided Drug Design
• +۴ مورد دیگر

Donald B. Boyd, Ph.D., serves as Research Professor of Chemistry at Indiana University - Purdue University Indianapolis (IUPUI) within the School of Science. His academic journey began in 1982 when he joined as Adjunct Professor while concurrently working as a Senior Research Scientist at Eli Lilly and Company, where he spent 25 years in computer-aided drug design. He was promoted to Research Professor in 1994, establishing himself as a leading figure in computational chemistry with over 100 refereed publications and significant editorial contributions. Dr. Boyd earned his B.S. from The Pennsylvania State University (1963), followed by an A.M. (1965) and Ph.D. (1968) from Harvard University, with NIH Postdoctoral training at Cornell University (1967-68). His research focuses on computational chemistry and medicinal chemistry, particularly the relationship between molecular structure and properties, with applications in pharmaceutical development. He pioneered computer-aided drug design methodologies that address the economic challenges of modern drug discovery, leveraging genomic insights for targeted therapeutic development. His publication record reveals consistent contributions to computational drug design, molecular modeling, and the historical evolution of computational chemistry. Early work centered on molecular simulations of drug-receptor interactions (1990s), evolving toward Alzheimer's disease therapeutics, HIV inhibitors, and pharmaceutical stress testing in recent years. The research demonstrates increasing integration of cheminformatics, machine learning, and industrial applications throughout his career. Spirit of Philanthropy Award from IUPUI (1996) Woodward Lecturer, Pennsylvania State University College of Medicine (2013) Sloan-C Award for Online Education (2012) Stanley C. Israel Regional Award (2011) James Flack Norris Award for Teaching Chemistry (2008) Multiple Prestigious External Award Recognition (PEAR) honors Dr. Boyd has advised numerous graduate students who now hold positions at major pharmaceutical companies and research institutions worldwide. His editorial leadership includes founding the Reviews in Computational Chemistry book series (18 volumes, 1990-2002) and serving as Editor of the Journal of Molecular Graphics and Modelling (1998-2001), where he increased submissions from 5 to 90 annually. He conceived the biennial Gordon Research Conferences on Computational Chemistry (1986-present) and the ACS Symposium on Emerging Technologies in Computational Chemistry. Through his Central Indiana Computational Chemistry Christmas Luncheons and leadership in professional organizations including the American Chemical Society's Division of Computers in Chemistry, Dr. Boyd has fostered collaborative research communities while maintaining active industry consultation roles with pharmaceutical and chemical companies.