جست‌وجوی استاد و پژوهشگر

Joshua J. Coonمشاهده پروفایل

استاد

• Bioanalytical Chemistry
• Mass Spectrometry
• Proteomics
• +۴ مورد دیگر

Joshua J. Coon is a Professor at the University of Wisconsin-Madison with appointments in the Department of Biomolecular Chemistry and the Department of Chemistry. He leads the Coon Group, focusing on advancing mass spectrometry technologies for proteomics, metabolomics, and lipidomics. His research addresses fundamental questions in cell biology, including stem cell differentiation, epigenetic regulation, and cancer biomarker discovery. Affiliations : Director of the NIGMS National Center for Quantitative Biology of Complex Systems. Research Emphasis : Instrumentation development, data analysis software, ion chemistry, and biological applications of proteomics. Laboratory : Located in the Genome Center of Wisconsin with a dozen hybrid mass spectrometers, including Orbitrap systems. Collaborations : Long-term partnership with Thermo Fisher Scientific and the Wisconsin Alumni Research Foundation (WARF) for technology commercialization. Training : Mentored 27 Ph.D. students since 2009, emphasizing interdisciplinary research and professional development.

Mark W Grinstaffمشاهده پروفایل

استاد

• Biomaterials
• Nanotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Mark W Grinstaff is a Professor at Boston University, leading the Grinstaff Group, which focuses on interdisciplinary biomaterials and biomedical engineering research. His work addresses healthcare challenges through innovations in diagnostics, devices, and therapeutics. He holds a B.A. from Occidental College (1987) and a Ph.D. from the University of Illinois at Urbana-Champaign (1992). Research interests include designing biodendrimers for tissue engineering, interfacial biomaterials, and conducting polymer-based sensors. Key areas span cartilage repair, drug delivery systems (e.g., anticancer, DNA), and biodegradable scaffolds. He explores nanoparticle-based imaging agents for osteoarthritis diagnosis and biomechanical assessments using computed tomography. Recent publications highlight advancements in machine learning-driven osteoarthritis classification, dual-contrast agents for cartilage imaging, and synthetic biolubricants for equine models. His group emphasizes translational research, with a focus on nanotechnology, regenerative medicine, and therapeutic delivery platforms. Grinstaff’s work is supported by grants and collaborations, though specific grants are not detailed in the text. He advises students through the Grinstaff Group, though no student names are listed here. His lab develops novel materials and devices, including polymeric adhesives and biosensors, with applications in orthopedics, oncology, and infectious diseases.

Sai Zhangمشاهده پروفایل

استادیار

• Machine Learning
• Genomics
• Precision Medicine
• +۵ مورد دیگر

Sai Zhang is an Assistant Professor in the Department of Epidemiology at the University of Florida (UF), holding affiliations with the College of Public Health & Health Professions and College of Medicine. He is also an Affiliate Faculty in the J. Crayton Pruitt Family Department of Biomedical Engineering at the Herbert Wertheim College of Engineering. Previously, he was an Instructor at Stanford University School of Medicine and a Research Associate at the VA Palo Alto Epidemiology Research and Information Center (ERIC). Dr. Zhang completed his Ph.D. in Computer Science and Technology at Tsinghua University, followed by postdoctoral training in Dr. Michael Snyder’s lab at Stanford Genetics. His research integrates machine learning, genomics, and precision medicine to uncover genomic bases of complex diseases. Key focuses include developing algorithms for multiomic data analysis, modeling genotype-phenotype relationships, and leveraging deep learning for biological sequence analysis. His work emphasizes cell-type-specific mechanisms in diseases like ALS, coronary artery disease, and neurodegenerative disorders. Notable contributions include frameworks for polygenic risk scoring (e.g., PRS-Net), biomarker discovery for ALS, and tools for time-to-event prediction in neurological diseases. He leads the Zhang Laboratory, advancing computational systems for precision health applications.

Martin Frommمشاهده پروفایل

استاد

• Biomarkers for transporter-mediated drug-drug interactions
• Medication safety (oncology, geriatrics)
• Mass spectrometry and metabolomics
• +۲ مورد دیگر

Martin Fromm is a Professor of Clinical Pharmacology and Toxicology at Friedrich-Alexander University Erlangen-Nürnberg, where he has served as Director of the Institute of Experimental and Clinical Pharmacology and Toxicology since 2004. His career includes prior roles as Acting Professor (2002–2004), Group Leader (1999–2002), and postdoctoral fellowships at the Dr. Margarete-Fischer-Bosch Institute (1992–1996) and Vanderbilt University (1997–1999). Research Focus: Mechanisms of variable drug effects, drug transporters, medication safety, and biomarker development for transporter-mediated drug interactions. Publications: Over 170 original articles and 49 reviews with an h-index of 76 (24,000+ citations). Leadership: Chair of the University Hospital Erlangen's drug utilization committee and steering board of the Center of Clinical Studies. Scientific Awards: Top 3% Highly Cited Researcher (AD Scientific Index 2022–2024) Top 2% Highly Cited Researcher (Stanford List 2023) MSD Health Award (2021) Paul-Martini-Award (2001) Presidential Trainee Award (1998) Research Trends: His recent work integrates metabolomics, machine learning (LC-MS methods), and clinical studies to enhance medication safety in oncology and geriatrics. Earlier studies focus on transporter proteins (e.g., OCT2, MATE1, P-glycoprotein) and their role in drug absorption, metabolism, and interactions. Grants & Collaborations: Funded by DFG, BMBF, BMG, and Deutsche Krebshilfe. Active in ethics committees and clinical pharmacology societies.

Arthur Bousquetمشاهده پروفایل

دانشیار

• Applied Mathematics
• Numerical Analysis
• Computational Fluid Dynamics
• +۳ مورد دیگر

Arthur Bousquet is an Associate Professor of Mathematics at Lake Forest College, affiliated with the Math and Computer Science department. He holds a PhD in Applied Mathematics from Indiana University (Bloomington, IN) and a MS in Engineering in applied mathematics and scientific computing from SuP Galilee Engineering School (Paris, France). His research focuses on numerical methods for partial differential equations, including finite volume and finite element techniques, with applications to geophysical fluid dynamics, climate modeling, and biomedical problems like viral shell mechanics. Notable areas include shallow water equations, phase field modeling, and computational methods for atmospheric dynamics. Bousquet has published extensively on topics such as numerical weather prediction, electrokinetic equations, and virus nanoindentation modeling. His work often combines theoretical analysis with computational simulations to address complex systems in fluid dynamics and materials science. He has received the Rothrock Award for teaching excellence (2014) and held research fellowships including an NSF Graduate Fellowship (2009-2013). His teaching includes courses like Computational Mathematics, Multivariable Calculus, and Real Analysis.

Jana Shenمشاهده پروفایل

استاد

• Molecular Simulation
• Data Science
• Kinases
• +۱۲ مورد دیگر

Jana Shen is a Professor in the Department of Pharmaceutical Sciences at the University of Maryland School of Pharmacy, where she leads an interdisciplinary research group at the intersection of chemistry, biology, physics, and computer science. Her lab develops and applies advanced simulation and data science tools to understand biomolecular mechanisms and accelerate drug discovery. Education: Postdoc, The Scripps Research Institute (2003–2007) PhD, University of Minnesota at Twin Cities (1999–2003) MS, University of Calgary, Canada (1996–1999) Diplom-Chemie, Bergische Universität Wuppertal, Germany (1991–1995) Her research focuses on molecular simulation , data science , and computational biophysics , with applications in kinases , GPCRs , transmembrane transporters , and pH-responsive materials . She has pioneered the development of continuous constant pH molecular dynamics (CpHMD) methods and their applications in drug design and biomolecular mechanisms. The recent publications highlight a strong trend in computational drug discovery , particularly in covalent inhibitors , opioid receptor mechanisms , antiviral design , and the integration of machine learning with molecular dynamics . These works span high-impact journals such as eLife , JACS , Nature Communications , and ACS journals. Scientific Awards: National Science Foundation CAREER Award American Chemical Society HP Outstanding Junior Faculty Award Junior Faculty Research Award (University of Oklahoma, 2008, 2009) Phi Kappa Phi, University of Minnesota Louise T. Dosdall Graduate Fellowship Nova Graduate Fellowship Dr. Shen has mentored numerous PhD students and postdoctoral fellows, many of whom have gone on to successful careers in academia and industry. Her research is supported by major agencies including the National Institutes of Health , National Science Foundation , and FDA . She leads the Shen Lab, which actively develops open-source tools such as DeepCys , CpHMD , and PKAD-3 , and maintains databases for covalent ligandability and pKa predictions.

• Virology
• Molecular Pathology
• Host-Pathogen Interactions
• +۵ مورد دیگر

Dr. Richard Y. Zhao is a tenured Professor in the Department of Pathology and Microbiology-Immunology at the University of Maryland School of Medicine. His research combines molecular biology, fission yeast genetics, mammalian biology, and virology to study virus-host interactions, particularly for HIV and Zika virus. He previously held academic positions at Northwestern University and Columbia University and has contributed to over 120 peer-reviewed articles. B.S., China Oceanography University (1981) M.S., Oregon State University (1995) Ph.D., Oregon State University (1991) Postdoctoral Training, Columbia University (1991-1992) Dr. Zhao's research focuses on: Virus-host interactions and pathogenicity High-throughput drug screening for antivirals Role of viral proteins in neuroinflammation and cancer Translational genomics in precision medicine His recent publications highlight SARS-CoV-2 ORF3a, Zika envelope proteins, and HIV protease inhibitors, emphasizing host-pathogen mechanisms across species. He has served on NIH panels and editorial boards for journals like Cell Research and Retrovirology . Scientific awards include: Fellow, American Academy of Microbiology (2019) Bernard L Mirkin Endowed Chair (2001-2004) Honorary Director, Shandong Gallo Institute (2009) Distinguished Service from SCBA (2015) Outstanding Service from CBA-USA (2016) Dr. Zhao also contributes to clinical diagnostics and personalized medicine through molecular testing and pharmacogenetics programs.

Karen S. Andersonمشاهده پروفایل

استاد

• Cancer Immunology
• Breast Cancer
• HPV-related Cancers
• +۵ مورد دیگر

Karen S. Anderson, M.D., Ph.D. is a Professor of Medicine at Mayo Clinic in Phoenix, Arizona, where she serves as a Contract Physician in the Division of Hematology/Oncology within the Department of Internal Medicine. Her clinical practice focuses on breast cancer, and she is affiliated with the Mayo Clinic Comprehensive Cancer Center and the Breast Clinic. As an active researcher, Dr. Anderson leads clinical trials in breast cancer immunotherapy and biomarker development. Dr. Anderson's educational background includes: Medical Scientist Training Program (MD), Duke University School of Medicine (1994) Ph.D. in Microbiology and Immunology, Duke University (1994) BA in Chemistry, University of Virginia (1986) Internship and Residency in Internal Medicine, Brigham and Women's Hospital, Boston Fellowship in Adult Hematology and Oncology, Dana Farber Cancer Institute Dr. Anderson's research focuses on cancer immunology with particular emphasis on breast cancer biomarkers, ovarian cancer biomarkers, pancreatic cancer biomarkers, cancer vaccines, and HPV-related cancers. Her work spans from basic immunology to clinical applications, with a strong focus on translating laboratory findings into clinical practice. She has developed innovative approaches for early cancer detection and has been instrumental in advancing breast cancer immunotherapy through clinical trials. Analysis of Dr. Anderson's recent publications reveals a consistent focus on breast cancer immunology, biomarker discovery, and HPV-related cancers. Her work integrates molecular biology, immunology, and clinical oncology to develop novel diagnostic and therapeutic approaches. Notably, her research has expanded to include computational approaches for neoantigen prediction and has addressed public health challenges including HPV-related cancer screening and even COVID-19 vaccine strategies. Dr. Anderson has received several prestigious awards: Outstanding Faculty Mentor Arizona State University Faculty Women's Association (2020) Chief Resident West Roxbury VA Hospital (1996) Phi Beta Kappa University of Virginia (1986) Merck Scholar (1986) Alpha Omega Alpha Honor Medical Society (1986) Echols Scholar University of Virginia (1982) Dr. Anderson has been actively involved in mentoring students and early-career researchers, serving on numerous thesis committees at Arizona State University across multiple departments including Molecular and Cellular Biology, Chemistry, and the Barrett Honors College. Her research is supported by multiple grants from the National Cancer Institute, including her role as Co-Chair of the Breast and Gynecologic Cancers Collaborative Group within the Early Detection Research Network. Dr. Anderson is a key member of the Arizona Biomarker Alliance Executive Committee and has established collaborative research teams focused on cancer biomarker discovery and validation. Her laboratory work integrates protein microarray technology, immunology, and cancer genomics to develop novel diagnostic and therapeutic approaches for breast and HPV-related cancers.

Sebastian Hillerمشاهده پروفایل

استاد

• Structural Biology
• NMR Spectroscopy
• Protein Folding
• +۴ مورد دیگر

Professor Sebastian Hiller is a Full Professor at the Biozentrum of the University of Basel, Switzerland, where he leads a research group focused on structural biology and biophysics. His laboratory specializes in using nuclear magnetic resonance (NMR) spectroscopy to elucidate the structures and functions of proteins and their interactions at the atomic level. His research spans several key areas including molecular chaperones and protein folding mechanisms, outer membrane protein biogenesis in bacteria, and kinase signaling pathways. Notably, his group has made significant contributions to understanding how chaperones like trigger factor function, the mechanisms of outer membrane protein assembly through the Bam complex, and dynamic kinase interactions. Their work has direct implications for neurodegenerative diseases and antibiotic development. The Hiller lab's recent publications demonstrate a strong focus on NMR methodology development, protein folding dynamics, and structural mechanisms of antibiotic action. Their research on darobactin's mechanism of action against Gram-negative bacteria represents a significant advance in antibiotic discovery. The group frequently publishes in high-impact journals including Nature, Science, and Nature Communications. ICMRBS Founder's Medal (2018) EMBO Young Investigator (2014) ERC starting grant (2011) SNSF professorship (2010) SNSF scholarship for young researchers (2008) Professor Hiller supervises numerous PhD students and postdoctoral researchers, with many alumni having secured prestigious positions in academia and industry. His laboratory maintains strong collaborations across multiple institutions and has received significant funding through ERC grants and other competitive mechanisms. The Hiller group also operates advanced NMR facilities that serve the broader research community at the University of Basel.

• Statistical Modeling
• Biostatistics
• Biomedicine
• +۷ مورد دیگر

Dae-Jin Lee is an Assistant Professor at IE University’s School of Science and Technology, specializing in statistical modeling and data science. Previously, he served as a Research Line Leader at the Basque Centre for Applied Mathematics (BCAM) and coordinated the Knowledge Transfer Unit in Data Science/AI. His academic background includes a Ph.D. in Mathematical Engineering (2010) from Universidad Carlos III de Madrid and postdoctoral research at CSIRO (Australia). His research focuses on statistical methods for complex data, including penalized splines, tensor product smooths, and applications in biomedicine, epidemiology, environmental science, and sports analytics. He has led multidisciplinary projects funded by public and industry grants, collaborating globally with experts across fields like engineering, medicine, and biology. Key research themes include predictive modeling for health outcomes (e.g., SARS-CoV-2 pneumonia severity), sports injury prevention, and AI in healthcare. His work integrates machine learning with traditional statistical techniques, addressing real-world challenges like pedestrian dynamics simulations and automated medical diagnostics. He is actively involved in scientific organizations, including the Spanish Biostatistics Society and the Statistical Modelling Society. His recent publications highlight innovations in growth curve modeling, AI ethics, and spatiotemporal data analysis, reflecting his commitment to advancing both theoretical and applied statistics.

Shabaz Mohammedمشاهده پروفایل

دانشیار

• Proteomics
• Mass Spectrometry
• Post-translational Modifications
• +۴ مورد دیگر

Shabaz Mohammed is an Associate Professor of Proteomics at the University of Oxford, holding joint appointments in the Departments of Chemistry and Biochemistry. Since 2020, he has served as Head of the Mechanistic Proteomics research programme at the Rosalind Franklin Institute. His research focuses on advancing proteomics technologies to study protein post-translational modifications and their roles in cellular processes, with applications in viral infections and disease mechanisms. Education: BSc in Chemistry, UMIST (now The University of Manchester), 1999 PhD in Biological Mass Spectrometry, University of Manchester, 2003 Postdoctoral Research, University of Southern Denmark (with Ole Jensen), 2005-2008 Postdoctoral Research, Utrecht University (with Albert Heck), 2008 Professor Mohammed's research centers on developing novel mass spectrometry approaches for large-scale characterization of protein post-translational modifications (PTMs). His group innovates in chromatographic techniques for single-cell proteomics, creates materials for PTM enrichment (glycosylation/phosphorylation), and applies these tools to study viral infections (SARS-CoV-2), cell cycle regulation, and signaling pathways. His work bridges chemistry, biochemistry, and cell biology to understand dynamic protein functions in health and disease. His recent publications (2023-2025) demonstrate strong emphasis on viral proteomics, particularly virus-host RNA-binding protein interactions, and innovations in mass spectrometry fragmentation techniques and chromatography. Key themes include viral remodeling of host cells, new labeling strategies for PTMs, and advancements in single-cell proteomics, with significant implications for understanding viral pathogenesis. Scientific Awards: No specific awards or fellowships were detailed in the source material. Advising and Grants: Information regarding graduate students supervised or specific research grants was not provided in the available text. As an active research group leader, Professor Mohammed likely mentors PhD students and secures competitive funding for proteomics research. Laboratories and Collaborations: Professor Mohammed leads a research group at Oxford focused on proteomics technology development. He collaborates extensively with the Ben Davis group on PTM detection materials and across the university on biochemical applications. At the Rosalind Franklin Institute, he heads the Mechanistic Proteomics programme to unravel protein functions through advanced proteomic methods.

Tim Conradمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Computational Biology
• Machine Learning
• +۵ مورد دیگر

Dr. Tim Conrad is a researcher at the Zuse Institute Berlin in the Visual and data-centric computing department under the Mathematics of Complex Systems division. He leads projects at the intersection of computational biology, AI, and medical data analysis. Projects: Geometric Learning for Single-Cell RNA Velocity Modeling, MODAL MedLab, Sparse Compressed Sensing in -Omics Data, BIFOLD (Big Data and Machine Learning) Research Networks: Affiliated with MATH+ and MODAL Research Campus His research focuses on applying machine learning , network optimization , and sparse data analysis to biological and medical challenges including disease modeling, microbiome dynamics, and ECG classification. Recent work explores hybrid PDE-ODE epidemic models and federated learning in healthcare. 2023-2025 publications highlight trends in AI for biological networks , temporal community detection , and medical signal processing . He co-authored studies on SARS-CoV-2 simulations, proteomics feature selection, and multi-label ECG analysis. His 2004 doctoral thesis at Monash University laid foundations for later work in metabolic pathway analysis. Awarded as a Zuse Fellow , he contributes to open science initiatives like FAIR data sharing . Collaborations span institutions including Freie Universität Berlin and Charité in medical informatics and clinical applications.

April Weiمشاهده پروفایل

استادیار

• Computational Genetics
• Population Genetics
• Statistical Genetics
• +۱۰ مورد دیگر

April Wei is an Assistant Professor in the Department of Computational Biology at Cornell University, where she leads the Wei Lab in Computational Genetics. Her research focuses on developing scalable computational methods to analyze massive genomic datasets, addressing fundamental questions in evolutionary processes and human genetics. B.Sc. in Biology, Fudan University (2013) Ph.D. in Computational Biology, University of Michigan (2018) Postdoctoral Research at UC Berkeley and UCLA Joined Cornell in January 2022 The Wei Lab explores diverse areas such as population genetics , computational genetics , and natural selection , with applications in human evolution , gene conversion , and complex traits . Their work leverages graph-based data structures and deep learning to improve genomic analysis scalability. April's research trajectory, as reflected in her publications, emphasizes genomic data compression , selective sweep detection , and ancestral recombination graph (ARG) analysis . Her lab's outputs span algorithm development for biobank-scale data, evolutionary modeling of overlapping genes, and statistical frameworks for gene conversion landscapes. April mentors a team of Ph.D. students and postdoctoral researchers, including current advisees Ziqing Pan, Meera Chotai, Jinmin Li, Aditya Girish, and Lin Yuan, with notable alumni such as Siddharth Avadhanam (2023). The lab is supported by NIH and NSF grants. Lab culture prioritizes collaboration , inclusivity , and scientific curiosity , with social activities like lab barbecues, game nights, and group hikes. April is also a passionate fan of Star Wars and water sports.

• Machine Learning
• Computer Vision
• Signal Processing
• +۶ مورد دیگر

Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.

Fengzhu Sunمشاهده پروفایل

استاد

• Computational Biology
• Bioinformatics
• Statistical Genetics
• +۶ مورد دیگر

Dr. Fengzhu Sun is a Professor of Quantitative and Computational Biology and Mathematics at the University of Southern California. His research spans computational biology, bioinformatics, statistical genetics, and mathematical modeling, with a focus on metagenomics, protein interaction networks, and genome sequence analysis. Dr. Sun earned his Bachelors in Mathematics from Shandong University, Masters in Probability and Statistics from Peking University, and PhD in Applied Mathematics from USC. He returned to USC in 2000 as an associate professor after serving at Emory University (1995-2000), becoming a full professor in 2006. His research interests encompass protein interaction networks, gene expression, SNPs, linkage disequilibrium, and their applications in predicting protein functions, gene regulation networks, and disease gene identification. He pioneered alignment-free methods for genome and metagenome sequence comparison, with recent work focusing on virus-host interactions in metagenomic data. His publication record shows consistent innovation, with recent work (2023-2025) emphasizing deep learning approaches (DeepMicroClass, DeepDecon, DeepLINK) and novel statistical methods. His research demonstrates strong interdisciplinary integration of computational methods with biological applications. Fellow of American Association for the Advancement of Sciences (AAAS, 2012) Fellow of American Statistical Association (ASA, 2015) Fellow of Institute of Mathematical Statistics (IMS, 2023) Fellow of International Society for Computational Biology (ISCB, 2024) Fellow of Asia-Pacific Artificial Intelligence Association (AAIA, 2025) Member of International Statistical Institute (ISI, 2012) USC Mellon Mentoring award for faculty mentoring (2012) USC Dornsife College senior Raubenheimer Outstanding Faculty Award (2017) Dr. Sun has mentored numerous successful students and postdocs, many now in academic positions or at leading tech and biotech companies. His research group develops computational methods for complex biological data analysis, with current focus on advanced deep learning for metagenomic classification, cancer cell fraction estimation, and virus-host interaction analysis. He has created influential software tools including DeepMicroClass, ImputeCC, DeepDecon, and ViralCC that have become standard resources in computational biology.