جست‌وجوی استاد و پژوهشگر

John Brownsteinمشاهده پروفایل

استاد

• Public Health Surveillance
• Digital Epidemiology
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

John Brownstein, PhD, is a Professor of Pediatrics and Biomedical Informatics at Harvard Medical School and Senior Vice President & Chief Innovation Officer at Boston Children’s Hospital. He directs the Computational Epidemiology Lab and Innovation & Digital Health Accelerator, focusing on digital epidemiology and AI-driven public health surveillance. His work pioneered platforms like HealthMap and Vaccines.gov, instrumental in tracking outbreaks (e.g., Ebola, Zika, and COVID-19) and informing policy globally. Research Interests: Public Health Surveillance Artificial Intelligence in Healthcare Citizen Science Infectious Disease Control Scientific Contributions: Developed AI tools for disease prediction Enhanced global outbreak detection systems Shaped pandemic response strategies Awards: Presidential Early Career Award (2020) Lagrange Prize (2021) Emmy (2022) Collaborations: Advised HHS, CDC, WHO, and partnered with tech giants like Google and OpenAI. Co-founded Epidemico and Circulation.

Ben Reisمشاهده پروفایل

استادیار

• Predictive Medicine
• Health Informatics
• Pharmacovigilance
• +۳ مورد دیگر

Ben Reis is an Assistant Professor of Pediatrics at Harvard Medical School and leads the Predictive Medicine Group within the Computational Health Informatics Program at Boston Children’s Hospital. He specializes in developing predictive approaches for early detection of diseases, drug safety monitoring, and leveraging social networks for public health interventions. His work includes systems predicting clinical risks years in advance, predictive pharmacology for adverse drug effects, and adaptive surveillance frameworks for infectious diseases and public health emergencies. Research interests span predictive analytics in healthcare, computational linguistics, and global health innovation. Notable projects include HealthySocial (social network-driven health behavior promotion) and SpeechWars (historical text analysis). He advises governments globally on biodefense and biosurveillance systems. Awards include recognition from the White House and State Department for health innovation. Publications focus on clinical prediction models, vaccine efficacy, suicide risk prediction, and pandemic response systems. His work emphasizes translating computational methods into actionable healthcare solutions, such as real-time disease surveillance and personalized risk assessment tools.

• Ecological Modelling
• Agent-Based Systems
• Epidemiological Modelling
• +۴ مورد دیگر

Dr. Vianney Sicard is a Researcher in the Department of Ecological Modelling at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany, leading the Ecological Epidemiology research group. He holds a PhD in Epidemiological Modelling and Artificial Intelligence (2019-2022) from INRAE, Nantes, and prior engineering degrees in computer science (2018, École Polytechnique de l'Université de Tours) and software design (2012). His research focuses on agent-based modelling, ecological epidemiology, and computational epidemiology, including applications to livestock disease dynamics and multi-level simulation frameworks. Key contributions include the EMULSION modelling framework and work on Bayesian networks for veterinary diagnostics. Sicard's interdisciplinary work bridges computer science, environmental science, and public health, with publications in journals like PLoS Computational Biology and PAAMS. He collaborates with teams like FORMIND and EcoEpi, addressing challenges in sustainable systems and policy design under global change.

• Phage Genomics
• Microbiome Analysis
• Bioinformatics
• +۲ مورد دیگر

Katelyn Sileo is an Adjunct Assistant Professor in the Department of Epidemiology and Biostatistics at San Diego State University (SDSU), holding a part-time faculty position focused on computational genomics and microbiome research. Her primary research interests include: Phage Genomics Microbiome Analysis Bioinformatics Computational Biology Epidemiology She develops computational tools for genome annotation and analysis, with emphasis on bacteriophage-host interactions and viral evolution. Her recent publications demonstrate expertise in predicting ribosomal frameshifts, analyzing crAssphage diversity, and investigating gut microbiome dynamics in Alzheimer's disease models, reflecting a strong focus on methodological innovation in phage genomics and translational microbiome applications.

Palash Sashittalمشاهده پروفایل

استادیار

• Computational Biology
• Genomics
• Cancer Genomics
• +۳ مورد دیگر

Palash Sashittal is an Assistant Professor in the Department of Computer Science at Virginia Tech's College of Engineering. His research focuses on computational biology, cancer genomics, and bioinformatics, with a strong emphasis on developing algorithms for genomic data analysis and lineage tracing. He holds a Ph.D. in Aerospace Engineering from the University of Illinois Urbana-Champaign, an M.S. in Computer Science from the same institution, and a B.Tech. in Aerospace Engineering from the Indian Institute of Technology Bombay. His work bridges computational methods with biological systems, particularly in understanding tumor evolution through single-cell sequencing and modeling clonal dynamics. Recent contributions include methods for CRISPR-based lineage tracing (Startle), tumor phylogeny inference (ConDoR), and SARS-CoV-2 variant-specific PCR assay design. His interdisciplinary approach integrates techniques from machine learning, fluid dynamics, and evolutionary biology. Publications highlight advancements in genomic evolution modeling, clonal heterogeneity analysis, and computational tools for cancer research. His research has implications for precision oncology, infectious disease tracking, and understanding cellular mechanisms.

• Biochemistry
• Computational Biology
• Drug Design
• +۴ مورد دیگر

Dr. Sivakumar Dakshinamurthy is a Researcher at the Max Planck Institute for Dynamics of Complex Technical Systems , leading the Molecular Simulations and Design group. His research focuses on protein-protein/ligand interactions using molecular docking and simulation, as well as enzyme engineering employing QM/MM hybrid methods. He is affiliated with the institute’s Sandtorstr. 1, Magdeburg, Germany, and can be reached at sivakumar@dynamicsofcomplextechnicalsystems.mpg.de . His work integrates computational approaches to address challenges in drug design, enzyme specificity, and sustainable chemistry. Current projects include AI-driven de novo drug design for acute myeloid leukemia and studies on SARS-CoV-2 protease inhibitors. His research also explores CO2 conversion via multienzyme systems and anticancer compound evaluation. Dr. Dakshinamurthy’s contributions span over two decades, with notable publications on deubiquitinase specificity, Bcl-2 family proteins, and histidine kinase targeting in bacterial pathogens. He maintains active collaborations in structural bioinformatics and contributes to early career research panels on drug repurposing. His office is located in S 1.11, and professional networks include LinkedIn.

Yuyang Guمشاهده پروفایل

استادیار

• Acoustics
• Ultrasound Imaging
• Wave Control
• +۴ مورد دیگر

Yuyang Gu is an Assistant Professor in the Department of Mechanical Engineering at Binghamton University. His research focuses on acoustics, wave control, ultrasound imaging, microfluidics, and biomedical micro/nano systems. Previously, he conducted postdoctoral research at Harvard Medical School (HMS) and Massachusetts General Hospital (MGH), where he worked on ultrasound imaging and elasticity imaging using advanced acoustic wave control. Education: BS and MS in Acoustics, Nanjing University, China PhD in Mechanical Engineering and Materials Science, Duke University Research Interests: Dr. Gu's work emphasizes the development of acoustic tweezers, acoustofluidics, and microfluidics for biomedical applications. His lab explores novel methods for particle manipulation, diagnostic imaging, and therapeutic systems. Recent advancements include acoustic-based separation technologies for exosomes, viruses, and extracellular vesicles, as well as physics-inspired machine learning approaches for ultrasound elastography. Grants & Collaborations: His research is supported by projects in medical imaging, nanotechnology, and biomedical engineering. Collaborations include work at HMS/MGH and Duke University, with a focus on translating acoustic technologies into clinical applications.

Karen S. Wilcoxمشاهده پروفایل

استاد

• Epilepsy Research
• Neuropharmacology
• Drug Development
• +۳ مورد دیگر

Karen S. Wilcox, PhD, is a Professor at the University of Utah Health College of Pharmacy , specializing in epilepsy research and neuropharmacology. Her work focuses on developing novel antiseizure therapies, understanding mechanisms of epileptogenesis, and optimizing drug delivery systems. She leads research in viral-induced epilepsy models, neuroinflammation, and closed-loop stimulation techniques. Research Interests: Neuropharmacology of antiseizure drugs Epileptogenesis and neurodegenerative processes Drug delivery via neural implants and focused ultrasound Preclinical screening platforms for epilepsy therapies Impact of inflammation on seizure susceptibility Awards: Recipient of the NINDS Landis Award for Outstanding Mentorship (2022), recognizing her contributions to training the next generation of neuroscientists. Labs & Affiliations: Active member of the Skaggs Pharmacy Institute and affiliated with the Pharmtox research group. Collaborates with the NIH Epilepsy Therapy Screening Program to advance translational epilepsy research.

• Endothelial Cell Biology
• Inflammation
• Aging
• +۴ مورد دیگر

Professor Jennifer Gamble holds the Wenkart Chair of Endothelium at the University of Sydney and the Centenary Institute. She completed her undergraduate degrees at the University of Melbourne and the Walter and Eliza Hall Institute of Medical Research, followed by a PhD at the University of Adelaide. She established the Vascular Biology Program at the Centenary Institute in 2007. Research Interests : Her work focuses on endothelial cell function in inflammation, aging, Alzheimer’s disease, and cardiovascular diseases. She is an Editor for Aging Cell and Senior Editor for Vascular Biology Journal , and co-chaired the 2019 World Congress on Inflammation. Current Projects : Investigates the role of aged vasculature in disease initiation, Alzheimer’s blood-brain barrier dysfunction, and calcific aortic valve disease (CAVD). Techniques include tissue culture, molecular biology, high-resolution imaging, and single-cell RNA sequencing. Publications : Over 141 publications with >15,000 citations, an H-index of 64, and recent work on endothelial senescence, tumor vasculature, and blood-brain barrier mechanisms. Grants & Awards : Recipient of multiple grants, including NHMRC Ideas Grant (2019) and Senior Researcher Grant (2024), focusing on aging endothelium, Alzheimer’s, and cardiovascular disease. Labs & Teams : Leads the Vascular Biology Program and collaborates with the Brain and Mind Centre and Centenary Institute teams.

• Multiple Sclerosis
• Neurology
• Neuroinflammatory Diseases
• +۷ مورد دیگر

Hanne Flinstad Harbo serves as the Dean of the Faculty of Medicine at the University of Oslo (UiO) since January 2023, alongside her position as Professor II in the Department of Neurology at UiO and senior consultant at the Department of Neurology, Oslo University Hospital (OUH). She has extensive leadership experience in academic and clinical settings, including roles as Deputy Head of the Institute of Clinical Medicine (2015–2018), Head of OUH’s Neurology Department (2018–2022), and leader of the Norwegian Brain Council (2014–2017). Her academic background includes a Dr. med (PhD) from UiO (2003), a Master’s in Health Administration (2015), and postdoctoral research at the Institute of Immunology, Rikshospitalet, Oslo (1997–2006). She has held visiting roles at the University of California San Francisco (2011–2012) and University of Cambridge (2001). Her research focuses on multiple sclerosis (MS) diagnosis and treatment, with emphasis on neuroinflammatory mechanisms, genetic predisposition, and advanced imaging techniques (e.g., diffusion MRI and restriction spectrum imaging). She co-leads UiO/OUH research groups for “Molecular and immunological studies of MS” and “Imaging studies of MS,” and leads international initiatives like the MultipleMS EU project and the International MS Genetics Consortium . Her work integrates machine learning for predicting disease progression, studying brain aging, and identifying biomarkers such as serum neurofilament light chain. She actively participates in professional networks including the Nordic MS Genetics Network , MAGNIMS (MRI in MS), and collaborates with institutions like Ospedale San Raffaele (Milan) and UC Berkeley. Her teaching contributions include clinical neurology instruction at UiO and co-editing the textbook Nevrologi og nevrokirurgi fra barn til voksen . Leadership priorities include fostering interdisciplinary collaboration and optimizing clinical-research synergies.

Christian Nansenمشاهده پروفایل

استادیار

• Applied Insect Ecology
• Integrated Pest Management
• Hyperspectral Imaging
• +۴ مورد دیگر

Christian Nansen is an Assistant Professor in the Department of Entomology and Nematology at the University of California, Davis. His research focuses on applied insect ecology, integrated pest management (IPM), and the use of hyperspectral imaging and machine vision systems to develop sustainable agricultural practices. He explores how optical sensing technologies can reduce pesticide reliance while maintaining crop health and economic viability. Recent publications highlight his work in hyperspectral imaging , plasma-activated water for pest control, and AI-driven ecological predictions . His studies span diverse areas such as light-based pest suppression , UAV precision agriculture , and insect vector migration modeling , all aligned with the UN Sustainable Development Goals (SDGs) in controlled environment agriculture. His research integrates remote sensing , optical data analytics , and sustainable nitrogen management to address critical challenges in crop protection and environmental health. He also contributes to educational tools for insecticide resistance and economics in pest management.

Brad Pollockمشاهده پروفایل

استاد

• Pediatric Oncology
• Clinical Trials
• Health Disparities
• +۳ مورد دیگر

Brad Pollock, Ph.D., is a Professor in the Department of Public Health Sciences at the University of California, Davis. His research focuses on pediatric oncology, disparities in cancer care, implementation science, and public health responses to epidemics. He has expertise in clinical trial design, telemedicine, and health policy analysis. Dr. Pollock’s work addresses gaps in cancer clinical trial enrollment, particularly among adolescents and young adults (AYAs), and evaluates healthcare access barriers. Key areas of investigation include: Clinical trials for pediatric cancers and supportive care interventions Health disparities in oncology treatment outcomes Public health strategies for pandemic management (e.g., SARS-CoV-2 testing adherence) Telemedicine applications in underserved populations Recent research highlights include analyzing delays in cancer diagnosis among young patients, evaluating the feasibility of multi-institutional data collection in oncology, and studying socioeconomic factors impacting metastatic bone disease survival. His work integrates epidemiological methods with implementation science to bridge research and practice. Dr. Pollock has contributed to major initiatives like Healthy Davis Together, a community-driven pandemic control program, and led studies on medication authorization barriers in pediatric oncology. His publications span over two decades, addressing topics from burn care transfusion strategies to the oncogenic effects of topical medications. His research emphasizes actionable solutions for improving healthcare equity, particularly in vulnerable populations such as rural children and AYA cancer patients. Collaborations include the Children’s Oncology Group, National Cancer Institute networks, and Clinical and Translational Science Award programs.

Michele Berselliمشاهده پروفایل

پژوهشگر ارشد

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

Michele Berselli is a Research Fellow in Biomedical Informatics at Harvard Medical School, Department of Biomedical Informatics. He is an active member of the 4DNucleome Data Coordination and Integration Center, where he specializes in developing and implementing automated pipelines and genomic workflows in cloud computing environments, particularly Amazon Cloud. Dr. Berselli earned his PhD in 2019 from the University of Padova, where his dissertation research focused on computational approaches to studying nucleic acid secondary structures. During his doctoral studies, he developed two innovative algorithms: nessie for identifying approximate DNA sequence symmetries and QPARSE for detecting long-looped or multimeric G-quadruplex structures. He also contributed to a comprehensive web-database evaluating G-quadruplex structures in human viruses, demonstrating his early expertise in non-canonical DNA structures and bioinformatics tool development. His research interests span bioinformatics, computational genomics, and structural biology, with particular expertise in G-quadruplex structures, DNA sequence analysis, and genomic workflow automation. Dr. Berselli's work bridges computational methodology development with biological applications, creating tools that enable deeper understanding of genomic architecture and function. His research has evolved from fundamental algorithm development for DNA structure analysis to more applied work in clinical genomics and viral genomics. An analysis of his publication record reveals a consistent trajectory of innovation in bioinformatics tool development. His work shows progression from specialized algorithms for DNA structure analysis (nessie, QPARSE) to broader genomic analysis tools (Chromoscope, BamSnap, GBRAP). Recent publications demonstrate increasing focus on clinical applications, particularly in rare disease diagnosis through genomic analysis. This evolution reflects the growing importance of computational approaches in translating genomic discoveries to clinical practice. As a member of the Harvard Medical School faculty, Dr. Berselli collaborates extensively with researchers across multiple laboratories, contributing his expertise in cloud-based genomic workflows and pipeline development to advance biomedical research. His work with the 4DNucleome initiative positions him at the forefront of research on three-dimensional genome organization and its functional implications.

• Systems biology
• Dynamical modeling
• Mathematical oncology
• +۴ مورد دیگر

Leonard Schmiester is a Postdoctoral Researcher at the Oslo Centre for Biostatistics and Epidemiology (OCBE), University of Oslo, Norway, since 2021. His research focuses on computational oncology and systems biology, developing dynamical models to predict treatment outcomes in breast cancer while advancing parameter estimation methodologies for biological systems. His academic background includes: PhD candidate (2016-2021) at Helmholtz Centre for Environmental Research and Technical University of Munich M.Sc. in Industrial Mathematics (2012-2016) from University of Hamburg B.Sc. in Mathematics (2008-2012) from University of Hamburg Dr. Schmiester's research integrates mathematical modeling with clinical oncology to personalize cancer treatment. He specializes in simulating tumor evolution under therapeutic pressure, particularly for estrogen receptor-positive breast cancer subtypes. His work combines dynamical systems theory with high-throughput data to decode mechanisms of drug resistance in Luminal B breast cancer, focusing on endocrine therapy and CDK4/6 inhibitor combinations. This approach enables computational prediction of patient-specific treatment responses, contributing to precision oncology frameworks that optimize therapeutic sequencing. Analysis of his publication record reveals two dominant research streams: clinical applications in breast cancer evolution (60% of recent work) and computational methodology development (40%). The oncology-focused publications examine immune-malignant cell co-evolution during aromatase inhibitor therapy, while methodological papers introduce innovations like pyPESTO for ODE parameter estimation and mini-batch optimization for large-scale datasets. Both streams converge on translating mathematical frameworks into clinically actionable insights for personalized cancer medicine. Dr. Schmiester actively contributes to the Norwegian Centre for Knowledge-driven Machine Learning and RESCUER project, applying stochastic modeling to biomedical challenges. As part of the Stochastic Models and Inference research group at OCBE, he develops statistical frameworks for interpreting heterogeneous biological data, with current work extending computational oncology approaches to machine learning applications in disease progression modeling.

Alejandro Colaneriمشاهده پروفایل

استادیار مدعو

• Genetics
• Cancer Biology
• Plant Genetics
• +۳ مورد دیگر

Alejandro Colaneri, PhD, is an Adjunct Assistant Professor in the Department of Genetics at the University of North Carolina School of Medicine. His research focuses on molecular genetics, cancer biology, and plant genomics, with a particular emphasis on understanding cellular heterogeneity in cancers like medulloblastoma and signaling pathways in plant stress responses. He has contributed to advancements in single-cell transcriptomics, epigenetic regulation, and viral detection methodologies. Colaneri’s work bridges basic research with translational applications, including studies on therapeutic resistance mechanisms and SARS-CoV-2 monitoring techniques. Education details are not explicitly stated in the provided text, but his academic roles and publications suggest advanced training in molecular biology and genetics. His research has been published across disciplines, including virology, oncology, and plant science. Collaborations with postdocs, students, and interdisciplinary teams are highlighted in departmental publications lists. His research interests span from single-cell analysis of tumor subpopulations to the role of G-protein signaling in plant stress tolerance. He has developed methods for batch correction in single-cell data (e.g., projected t-SNE) and pioneered droplet digital PCR applications for SARS-CoV-2 variant monitoring. Notable projects include defining SHH inhibitor resistance mechanisms in medulloblastoma and elucidating salt stress responses in rice/maze through G-protein signaling pathways. While no specific grants or awards are listed, his frequent publications in high-impact journals and collaborative work indicate active research involvement. His work often involves epigenetic profiling (e.g., DNA methylation studies in Arabidopsis) and mitochondrial function in plant reproduction. Colaneri’s lab or team affiliation is not detailed, but his contributions to the Department of Genetics reflect a strong commitment to interdisciplinary genetic research.