جست‌وجوی استاد و پژوهشگر

• Hematopathology
• Molecular Pathology
• Myeloid Neoplasms
• +۵ مورد دیگر

Sam Sadigh, M.D. is an Assistant Professor of Pathology at Harvard Medical School and works at Brigham and Women's Hospital in the Department of Pathology. His research focuses on hematopathology, molecular pathology, and the study of hematologic malignancies including myeloid neoplasms, lymphomas, and post-transplant complications. Dr. Sadigh received his B.A. in Neuroscience from the University of Virginia, followed by his M.D. from the Medical College of Virginia (VCU School of Medicine). He completed his AP/CP Pathology residency at the University of Pennsylvania and his Hematopathology fellowship at Massachusetts General Hospital. Dr. Sadigh's research interests span several key areas in hematopathology and molecular diagnostics. His work focuses on the molecular characterization of myeloid neoplasms, understanding the tumor microenvironment in lymphomas, particularly those associated with Epstein-Barr virus, and investigating immune responses in vascularized composite allotransplantation (including face transplantation). His recent research has increasingly incorporated spatial multi-omics approaches to understand the spatial organization of tumor microenvironments. Analysis of Dr. Sadigh's recent publications (2023-2025) reveals a strong focus on the intersection of molecular pathology, hematologic malignancies, and transplant immunology. His work often examines the relationship between genetic abnormalities and morphological features in hematologic disorders. Several recent publications address the impact of viral infections (particularly EBV) on lymphoma development and progression. He has also made significant contributions to understanding rejection mechanisms in facial transplantation through detailed pathological analyses. Dr. Sadigh has been actively involved in mentoring and teaching, as evidenced by his numerous collaborative publications with colleagues across multiple institutions. His work spans basic science investigations into disease mechanisms as well as more clinically focused studies on diagnostic approaches and patient outcomes. Dr. Sadigh is part of research teams investigating vascularized composite allotransplantation at Brigham and Women's Hospital, collaborating closely with surgeons, immunologists, and other pathologists. His laboratory work focuses on applying advanced molecular and spatial techniques to understand the pathological processes in hematologic malignancies and transplant rejection.

Rosemary Braunمشاهده پروفایل

دانشیار

• Computational Biology
• Machine Learning
• Graph Theory
• +۳ مورد دیگر

Rosemary Braun is an Associate Professor at Northwestern University with joint appointments in Molecular Biosciences, Applied Mathematics, and Physics. She also serves as an External Professor at the Santa Fe Institute , where she applies her interdisciplinary expertise to complex systems research. Her research focuses on: Computational biology at multiple scales Machine learning for high-dimensional biological data Graph-theoretic modeling of cellular interaction networks Dynamical simulations of biological processes Circadian regulation and its disruption Applications in cancer and developmental biology Recent publications demonstrate expertise in: Single-cell transcriptomics Circadian rhythm analysis Spatial neighborhood reconstruction Network-based disease modeling Statistical methods in biological data Chronobiology and health impacts She leads a computational laboratory that collaborates extensively with experimental teams and serves on leadership committees at: Northwestern Institute on Complex Systems NSF-Simons Center for Quantitative Biology

David M. Tobinمشاهده پروفایل

استاد

• Tuberculosis
• Mycobacterial Pathogenesis
• Host-Pathogen Interactions
• +۹ مورد دیگر

David M. Tobin is a Professor at Duke University School of Medicine with joint appointments in Molecular Genetics and Microbiology, Cell Biology, and Integrative Immunobiology. His research focuses on understanding Tuberculosis pathogenesis through zebrafish models , human genetics , and pharmacological interventions , aiming to identify novel therapeutic targets. Ph.D. in 2002 from University of California San Francisco, School of Medicine Research Interests : Using zebrafish genetics to map host susceptibility genes for TB, studying macrophage biology and granuloma formation , and translating findings to human TB and leprosy through genetic pathway analysis . Collaborations in Vietnam and Guatemala examine disease transmission dynamics. Publication Trends : Recent work emphasizes single-cell transcriptomics , angiogenesis in granulomas , and cross-species immune pathway conservation . His team develops innovative CRISPR tools for zebrafish and explores host-directed therapies for mycobacterial infections. Scientific Recognition : Fellow, American Academy of Microbiology (2024) Fellow, American Association for the Advancement of Science (2019) NIH Director's New Innovator Award (2011) Advising & Funding : Mentors graduate and postdoctoral researchers while directing major NIH grants including the Tri-Institutional Molecular Mycology and Pathogenesis Training Program (2024-2029) and Innate Immune Determinants of Granuloma Formation (2017-2027).

Nian Wangمشاهده پروفایل

دانشیار

• Neuroimaging
• Biomedical Engineering
• MRI Techniques
• +۳ مورد دیگر

Dr. Nian Wang, Ph.D., is an Associate Professor in the Department of Biomedical Engineering at UT Southwestern Medical Center and Principal Investigator at the Advanced Imaging Research Center. He leads the Multimodality Imaging and Analysis (MUDIA) Laboratory, focusing on developing novel MRI acquisition and reconstruction methods for studying central nervous system and musculoskeletal disorders. Education: B.S. from Wuhan University, Ph.D. from Chinese Academy of Sciences Prior Appointments: Research Associate and Assistant Professor at Duke University (2018), Tenure-Track Assistant Professor at Indiana University School of Medicine (2020) Dr. Wang's research specializes in quantitative MRI techniques, including UTE, multi-component T2*, QSM, and compressed sensing for high-resolution diffusion MRI. His work addresses early detection of neurological diseases (Multiple Sclerosis, Alzheimer’s disease, ASD) and musculoskeletal disorders through advanced imaging and computational analysis. The MUDIA Lab's recent publications demonstrate expertise in: High-resolution neuroimaging and connectomics Quantitative susceptibility mapping (QSM) Diffusion MRI for tissue microstructure Machine learning applications in medical imaging Translational studies from rodents to humans Collagen fiber architecture analysis His team integrates multimodal imaging with histological validation and collaborates on preclinical and clinical applications of MRI for neurodegenerative and musculoskeletal conditions.

• Biomarker Discovery
• Medical Informatics
• Statistical Learning
• +۵ مورد دیگر

Yang Xie is a Professor at UT Southwestern Medical Center , where she serves as the Associate Dean for Data Sciences . She is the founding director of the Quantitative Biomedical Research Center (QBRC) , Pediatric Cancer Data Commons (PCDC) , and Cancer Center Data Science Shared Resources (DSSR) within the Harold C. Simmons Comprehensive Cancer Center . Her research integrates biostatistics , bioinformatics , and machine learning to develop predictive biomarkers and precision medicine approaches for cancer patients. Her PhD in Biostatistics (2006) and MS in Biostatistics (2002) and Epidemiology (2000) from University of Minnesota-Twin Cities and Peking University Health Science Center (1997) form the foundation of her interdisciplinary expertise. Research focuses include RNA regulation , high-dimensional data analysis , and computational oncology . Recent projects leverage deep learning for pathology image analysis and tumor microenvironment modeling , with applications in lung cancer survival prediction , Germ Cell Tumor data commons , and immune-related adverse event forecasting . She has developed open-source tools like MetaPrism and PIPE-CLIP for microbiome and CLIP-seq analysis. Scientific recognitions include NIH MIRA grant leadership and multiple DREAM Challenge awards for computational modeling. Her work bridges biostatistics , machine learning , and translational oncology through collaborations with institutions like MD Anderson and Northwestern University .

Lin Xuمشاهده پروفایل

استادیار

• Bioinformatics
• Deep Learning
• Integrated Genomics
• +۷ مورد دیگر

Dr. Lin Xu is an Assistant Professor at the Department of Health Data Science & Biostatistics, UT Southwestern Medical Center. His research integrates deep learning and bioinformatics to identify disease genes and therapeutic targets in human diseases through single-cell/spatial multi-omics analysis. Grants: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), National Human Genome Research Institute (NHGRI), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), Cancer Prevention and Research Institute of Texas (CPRIT), U.S. Department of Defense (DoD), Hyundai Foundation, Children’s Cancer Fund, Sam Day Foundation, Rally Foundation, Andrew McDonough B+ Foundation. Research focuses on integrated genomics , deep learning algorithms , and NGS-based analysis to uncover molecular mechanisms in cardiovascular diseases and cancer (particularly rhabdomyosarcoma and germ cell tumors ). Key methods include Bayesian modeling , predictive models for drug response, and multi-omics integration for tumor/immune microenvironment characterization. Recent publications span Nature , Science , Cell , and Nature Communications , covering topics like transcriptional regulators , spatial transcriptomics , kinase networks , and telomere-targeting therapies . Software tools developed include COSMOS , SpaSNE , iExCN , and AI-enhancer .

Omar Ahmedمشاهده پروفایل

دانشیار

• Spatial Navigation
• Memory Circuits
• Alzheimer's Disease
• +۵ مورد دیگر

Associate Professor Omar Ahmed is a faculty member in the Biopsychology Department within the College of Literature, Science, and the Arts at the University of Michigan. His research focuses on neural circuit mechanisms of spatial navigation, memory consolidation, and their dysfunction in neurological disorders. Dr. Ahmed's primary research interests include spatial navigation circuits , memory consolidation during sleep , Alzheimer's disease mechanisms , epilepsy pathophysiology , and therapeutic applications of psychedelic compounds . His lab employs transgenic rodent models, human patient studies, and AI-driven data analysis to investigate how neural circuits encode space, time, and speed. Analysis of his recent publications reveals a strong focus on retrosplenial cortex function, theta oscillation dynamics, and the long-term cognitive effects of psychedelic compounds. His work bridges basic neuroscience with translational applications for neurological and psychiatric disorders. Scientific recognition includes: Altmetric Top 5% of all research output (2025) for psychedelic cognition study Dr. Ahmed leads the Ahmed Lab, which investigates neural circuit repair strategies for neurological disorders. His research involves collaborative projects with U-M Psychology faculty and receives coverage in major scientific outlets including Discover Magazine and Inside Precision Medicine. The lab utilizes engineered mouse models and advanced physiological techniques to validate mechanisms of psychedelic medicine. The Ahmed Lab maintains active research programs in: Neural circuit mapping of spatial navigation systems Theta oscillation dynamics across behavioral states Psychedelic compound effects on cognitive flexibility Seizure mechanisms in human neural tissue

Jifan Fengمشاهده پروفایل

پژوهشگر

• Developmental Biology
• Cell Biology
• Regenerative Medicine
• +۳ مورد دیگر

Jifan Feng is a Research Scientist and Team Lead at the Center for Craniofacial Molecular Biology, affiliated with the Herman Ostrow School of Dentistry at the University of Southern California. Holding a Ph.D. in Pre-clinical Dentistry (Cell Biology) from King’s College London, along with an MRes in Regenerative Medicine from the University of Bath and an MB in Stomatology from Nanchang University, Feng has dedicated his career to understanding craniofacial development and stem cell regulation. Education: M.B., Stomatology, Nanchang University, China (2006) MRes, Regenerative Medicine, University of Bath, UK (2007) Ph.D., Pre-clinical Dentistry (Cell Biology), King’s College London, UK (2012) Research Focus: Feng’s work examines spatiotemporal cellular dynamics, signaling pathways (e.g., Wnt, FGF, Hedgehog), and stem cell niches during craniofacial development. His studies include mechanotransduction, neural-epithelial interactions, and epigenetic regulation in tooth root morphogenesis and soft palate development. Publication Trends: Recent articles emphasize spatial transcriptomics, sensory nerve-stem cell crosstalk, and signaling network interactions. Key subfields include craniofacial morphogenesis, gene regulatory networks, and niche-mediated stem cell homeostasis. Awards: 3rd Place, FaceBase Community Forum poster competition (2022) Collaborations and Grants: Feng collaborates extensively with researchers like Yang Chai and Ting-Hsiao Emilie Ho. While specific grants are not listed in the text, his work is supported by high-impact publications in journals such as Nature Communications , PNAS , and eLife .

Haesun Parkمشاهده پروفایل

استاد

• Data analysis
• Visual analytics
• Numerical computing
• +۴ مورد دیگر

Dr. Haesun Park is a Regents' Professor and Chair in the School of Computational Science and Engineering at Georgia Institute of Technology, Atlanta, Georgia. She has held this position since August 2020, after becoming a Regents' Professor in July 2019 and a Professor since July 2005. Prior to joining Georgia Tech, she served as a Professor in the Department of Computer Science and Engineering at the University of Minnesota from 1987 to 2005 (Assistant Professor 1987-1993, Associate Professor 1993-1998, Professor 1998-2005) and as a Program Director at the National Science Foundation from 2003-2005. Education: Ph.D. in Computer Science (minor: Mathematics), Cornell University, 1987 M.S. in Computer Science, Cornell University, 1985 B.S. (Summa Cum Laude) in Mathematics, Seoul National University, 1981 (with Presidential Medal for top graduate) Dr. Park's research spans multiple domains within computational science, with particular focus on data analysis, visual analytics, numerical computing, text mining, social media mining, parallel computing, and bioinformatics. Her work integrates mathematical foundations with practical applications across various fields, developing innovative algorithms for large-scale data analysis. She has made significant contributions to nonnegative matrix factorization techniques and their applications in diverse domains including healthcare, social media analysis, and scientific computing. Her recent publication trends show a strong focus on parallel and distributed implementations of matrix factorization algorithms, applications in healthcare data analysis (particularly patient profiling and clustering), and development of scalable frameworks for handling large-scale datasets. The work demonstrates increasing interdisciplinary collaboration, especially with medical researchers, and a growing emphasis on practical implementations that can handle real-world data challenges. Scientific Awards: SIAM Fellow (2013) IEEE Fellow (2016) ACM Fellow (2020) Dr. Park has held significant leadership roles including Executive Director of the Center for Data Analytics (2013-2015) and Director of the NSF/DHS FODAVA-Lead Center (2008-2014). She has served as conference co-chair for the SIAM International Conference on Data Mining in 2008 and 2009, and as an editorial board member for leading journals including IEEE Transactions on Pattern Analysis and Machine Intelligence, SIAM Journal on Matrix Analysis and Applications, and SIAM Journal on Scientific Computing. She has been a plenary keynote speaker at major international conferences including SIAM Conference on Applied Linear Algebra in 1997 and 2015, and SIAM International Conference on Data Mining in 2011. Dr. Park is affiliated with multiple research centers at Georgia Tech including the Algorithms and Randomness Center (ARC) and the Institute for Data Engineering and Science (IDEaS). She has maintained a long-term collaboration with the Korea Institute for Advanced Study (KIAS) as a KIAS Scholar from 2008-2018, demonstrating her international research impact.

Tamara Allistonمشاهده پروفایل

استاد

• Mechanobiology
• Bone Biology
• Cartilage Research
• +۵ مورد دیگر

Tamara Alliston, PhD is a Professor in the Department of Orthopaedic Surgery at the University of California, San Francisco (UCSF). She holds adjunct positions in the Department of Otolaryngology-Head and Neck Surgery and the Department of Bioengineering and Therapeutic Sciences at UCSF, and is a faculty member in the UC Berkeley/UCSF Graduate Program in Bioengineering , UCSF Graduate Programs in Biomedical Sciences , Oral and Craniofacial Sciences , and Developmental and Stem Cell Biology . Dr. Alliston co-directs the Skeletal Biology Core at the NIH P30-supported UCSF Core Center in Musculoskeletal Biology and Medicine. PhD in Cell Biology, Baylor College of Medicine (1998) Postdoctoral Fellow, UCSF Research Interests: Dr. Alliston investigates how mechanobiologic pathways regulate bone and cartilage homeostasis, focusing on TGFβ signaling in osteocytes and chondrocytes. Her work examines the molecular mechanisms linking bone quality, joint degeneration, and aging, with interdisciplinary approaches combining molecular biology, bioengineering, and materials science. Key areas include: Role of osteocytes in bone fragility and osteoarthritis TGFβ/Wnt signaling cross-talk during mechanical stress Bone-brain crosstalk in aging and Alzheimer’s disease Metabolic regulation of bone remodeling via diet and diabetes Development of regenerative therapies for skeletal tissues Recent Publications (selected trends) explore: Integrating mouse transcriptomics with human GWAS to identify bone fragility genes Impact of aging on osteocyte collagen regulation 3D imaging of osteocyte networks Therapeutic targeting of TGFβ in fibrous dysplasia Fluid shear stress signaling in bone matrix remodeling Honors and Leadership: Co-Director, NIH P30 Skeletal Biology Core Editorial Board, Journal of Bone and Mineral Research Chair, UC Berkeley/UCSF Bioengineering Executive Committee AIMBE College of Fellows (2021) Recipient of Arthritis Investigator, ASBMR Frost, and Boskey Awards Training and Collaboration: Dr. Alliston mentors graduate students and postdoctoral scholars in her lab, with trainees presenting at major conferences like ASBMR and ORS. Current and former lab members include Neha Dole, Charlie Schurman, Dave Monteiro, and Serra Kaya. Her NIH R01-funded research spans projects on osteocyte mechanobiology, bone-cartilage crosstalk, and diabetes-related skeletal dysfunction.

• HIV-1 Persistence
• Cell, Gene and Immunotherapies for HIV-1
• Chronic Viral Persistence
• +۵ مورد دیگر

Timothy Scott Henrich is a Professor of Medicine at the University of California, San Francisco (UCSF) School of Medicine, where he leads the Henrich Lab focused on viral persistence and novel therapeutic approaches for chronic viral infections. His research spans HIV-1, SARS-CoV-2, and other persistent viral pathogens, with particular emphasis on understanding viral reservoirs and developing strategies for viral eradication or mitigation of long-term health consequences. Dr. Henrich received his B.A. from Oberlin College (1996), M.D. from Yale University School of Medicine (2004), and M.M.Sc. from Harvard University School of Medicine (2013). He completed his Internal Medicine Residency at Brigham and Women's Hospital (2007) and Infectious Disease Fellowship at Massachusetts General Hospital and Brigham and Women's Hospital (2009). His research interests encompass HIV-1 persistence mechanisms, cell and gene immunotherapies for HIV-1, chronic viral persistence, mechanisms of Long COVID and persistent SARS-CoV-2 infection, PET imaging of infectious pathogens, multi-omic spatial profiling of viral-host responses in tissues, and HIV-1 cure strategies. The Henrich Lab employs interdisciplinary approaches to study viral reservoirs across the whole body, with recent expansion into SARS-CoV-2 research following the pandemic onset. Analysis of Dr. Henrich's recent publications reveals a strong focus on viral persistence mechanisms across multiple pathogens, with particular attention to HIV reservoir dynamics and Long COVID pathogenesis. His work combines advanced imaging techniques, multi-omic approaches, and clinical cohort studies to characterize viral reservoirs and immune responses in chronic viral infections. Dr. Henrich serves as Principal Investigator on multiple NIH-funded research projects including R01AI152932 (In Vivo PET Imaging of HIV Infection), R01AI141003 (Targeting Non Viral Markers of HIV Persistence), R21MH116716 (Biomarkers of CNS HIV Persistence), and several other grants focused on HIV reservoir characterization and elimination strategies. His lab maintains a collaborative research approach with numerous interdisciplinary partnerships. The Henrich Lab operates at the intersection of translational virology and infectious disease research, with a strong emphasis on team science and collaborative approaches to address urgent clinical and research needs in viral persistence. Their work has evolved from primarily HIV-focused research to include SARS-CoV-2 and human herpes viruses, particularly examining viral persistence mechanisms and post-acute sequelae of viral infections.

Ryan E. Millsمشاهده پروفایل

استاد

• Structural Genomic Variation
• Somatic Mutation Analysis
• Computational Biology
• +۳ مورد دیگر

Ryan E. Mills is a Professor of Computational Medicine and Bioinformatics and Human Genetics at the University of Michigan Medical School, where he also serves as the Program Director of DCMB Computing Infrastructure. He actively mentors trainees and contributes to precision health initiatives through his research. Education: PhD, Georgia Institute of Technology (2006) MS, Georgia Institute of Technology (2003) AB, Wabash College (2000) Ryan E. Mills' research focuses on structural genomic variation across human populations and somatic mosaicism in non-cancerous tissues. His work includes developing computational methods for identifying copy number variants , nuclear mitochondrial insertions , and mobile element dynamics using whole genome sequencing and cloud-based systems like AWS. He investigates the role of somatic mutations in brain aging and neurodevelopmental disorders, and explores HPV integration mechanisms in head and neck cancers. Recent publications highlight his contributions to resolving complex structural variants , characterizing somatic mosaicism across tissues, and advancing computational frameworks for genomic data integration. His lab collaborates extensively through consortia such as the Brain Somatic Mosaicism Network and the Somatic Mosaicism across Human Tissues Network .

Jenny Xiangمشاهده پروفایل

استاد

• Genomics
• Epigenomics
• DNA Methylation Profiling
• +۴ مورد دیگر

Jenny Xiang is a Professor affiliated with the Graduate School of Medical Sciences at Weill Cornell Medicine and serves as a core facility leader for the Genomics Resources Core Facility (GRCF) and Epigenomics Core. Established in 2000, the GRCF provides advanced genomics services including sample preparation, next-generation sequencing (NGS), and data analysis for biomedical researchers. The Epigenomics Core specializes in DNA methylation profiling, single-cell transcriptomics, spatial transcriptomics, and bioinformatics. Her work supports critical experimental design, data interpretation, and validation using cutting-edge technologies such as Illumina NovaSeq 6000, 10X Genomics Chromium, and Drop-Seq systems. Recent developments include expanded services in Single-Cell Spatial Imaging (CosMx) and Visium HD for high-resolution gene expression studies.

Steffen Heberمشاهده پروفایل

استاد

• Bioinformatics
• Computational Biology
• Algorithms and Theory of Computation
• +۷ مورد دیگر

Steffen Heber is a Professor in the Department of Computer Science at NC State University with a joint appointment in the College of Sciences to support the Bioinformatics Research Center. His work bridges computational methods with biological discovery, focusing on algorithm development for biological data analysis and translation regulation in plants. Ph.D. in Mathematics (2001) Staatsexamen in Mathematics and Biology (1998) Diploma in Mathematics (1995) His research interests span Bioinformatics , Computational Biology , Alternative Splicing , and Translation Regulation . He develops novel algorithms for analyzing genomic data and investigates translational control mechanisms in plants using ribosome footprinting technologies. Recent publications focus on ChIP-seq processing , Ribo-seq analysis , and translational regulatory elements in Arabidopsis. Key themes include data quality control, ribosome positioning algorithms, and plant hormone signaling networks. Key Scientific Awards: IBM Faculty Award (2008) Carol Miller Graduate Lecturer Award (2018, 2013) Thank a Teacher Recognition (multiple years) Best Paper Award, ACMSE (2007) Heber has secured significant funding from the National Science Foundation, including grants for RiboPI technology development and translational hormone-response networks . His work also emphasizes undergraduate research training and K-12 science outreach programs.

Yi Zhangمشاهده پروفایل

استادیار

• Computational Biology
• Bioinformatics
• Machine Learning in Genomics
• +۴ مورد دیگر

Yi Zhang is an Assistant Professor at Duke University with primary appointments in the Department of Neurosurgery and secondary affiliations in Biostatistics & Bioinformatics. As a core member of the Duke Brain Tumor Omics Program and the Duke Cancer Institute, Zhang's research integrates machine learning, genomics, and computational biology to address challenges in tumor microenvironment analysis, human genetics, and immunotherapy. The lab develops methods for single-cell and spatial transcriptomics, focusing on interpretable AI models to dissect multi-cellular disease systems like brain tumors. PhD in Bioengineering from University of Illinois at Urbana-Champaign (2019) Postdoctoral training at Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health Research Interests: Machine Learning for Omics: Developing interpretable AI models to analyze single-cell, spatial transcriptomics, and multi-omics data Tumor Microenvironment: Investigating cancer-intrinsic/extrinsic interactions and targetable immunity modulators Human Genetics: Mapping genetic variants to functional genomics mechanisms via integrative methods Scientific Leadership: Zhang's 15 most recent publications (2025-2018) span computational methods (STHD, MetaTiME), tumor-immune dynamics, functional genomics (GWAS integration), and immunotherapy modeling. Key themes include spatial transcriptomics, regulatory variant interpretation, and machine learning-driven drug discovery. Awards: EECS Rising Star, University of Texas Austin (2022) Professional Engagement: Zhang organizes Duke Single Cell Initiative symposia, serves on Duke Cancer Institute review committees, and contributes to editorial/review roles for journals like Bioinformatics and Genetics.