جست‌وجوی استاد و پژوهشگر

Daniele Perloمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Deep Learning
• Medical Imaging
• +۳ مورد دیگر

Daniele Perlo is a Postdoctoral Fellow at Luxembourg Institute of Health specializing in Brain Imaging & Neuro Epidemiology. His research bridges artificial intelligence and medical imaging to advance neuro-oncology diagnostics, with emphasis on brain tumor hypoxia detection and MRI analysis. His primary research interests include Artificial Intelligence , Deep Learning , Medical Imaging , and Neuroimaging , with specific focus on hypoxia detection in brain tumors using multiparametric MRI. He develops AI models for medical image synthesis, artifact correction, and tumor characterization, translating computational methods into clinical applications for improved cancer diagnostics. Analysis of Perlo's 15 recent publications (2021-2024) reveals a concentrated research trajectory in AI-driven medical imaging. Key themes include brain tumor hypoxia prediction through MRI-PET synthesis, MRI artifact correction via k-space deep learning, and creation of specialized medical datasets (Unitobrain, Unitochest, Unitopatho). His work demonstrates increasing emphasis on practical clinical implementations, particularly in neuro-oncology and multi-organ cancer imaging, leveraging large-scale deep learning frameworks. Perlo participated as a key contributor in the "Pseudo PET" research project (2022-2024), collaborating with principal investigators Keunen and Niclou to develop deep learning methods for synthesizing pseudo-PET images from MRI data to assess brain tumor hypoxia without radiation exposure. This HPC-intensive project utilized multiple GPUs for medical image processing in neuro-oncology applications. He operates within the Brain Imaging & Neuro Epidemiology research group at Luxembourg Institute of Health, focusing on AI applications for neuroimaging analysis and epidemiological studies of brain disorders through advanced computational techniques.

John Bartonمشاهده پروفایل

دانشیار

• Virology
• Immunology
• Evolutionary Biology
• +۶ مورد دیگر

John Barton, PhD, is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research integrates statistical physics , machine learning , and population genetics to study viral evolution and immunity, with a focus on HIV and SARS-CoV-2. His lab develops computational tools like popDMS for analyzing viral fitness landscapes and has contributed to understanding mechanisms of viral escape from immune responses and vaccine design strategies. Education: PhD in Physics from Rutgers University Research Interests: Barton’s work addresses fundamental questions about viral adaptation, clonal heterogeneity in viral reservoirs, and the interplay between chronic infections and evolutionary dynamics. He applies advanced mathematical frameworks such as Ising/Potts models and covariance factorization to decode genetic data from large-scale surveillance efforts. Key Contributions: Recent studies include modeling SARS-CoV-2 transmission via genomic data, analyzing HIV evolutionary trajectories in humans and macaques, and developing methods to infer mutation effects from deep mutational scans. His lab also explores innate immune adaptation and the design of broadly neutralizing antibody-based therapies. Awards & Recognition: No specific awards listed, though his work has been supported by NIH-funded initiatives in computational virology. Labs/Teams: Leads the Barton Lab, part of the School of Medicine’s Computational and Systems Biology program, collaborating with global networks in infectious disease research and public health.

Natalia Juraمشاهده پروفایل

استادیار

• Structural Biology
• Cancer Signaling
• Receptor Tyrosine Kinases
• +۱۲ مورد دیگر

Natalia Jura is an Assistant Professor at the Cardiovascular Research Institute (CVRI) within the School of Medicine at the University of California San Francisco (UCSF). Her research is centered on understanding the structural and molecular mechanisms of receptor tyrosine kinases and pseudokinases in cancer and disease. She employs cutting-edge techniques such as cryo-electron microscopy (cryo-EM), deep mutational scanning, and structural biology to dissect signaling pathways involving HER2, HER3, MET, and other key oncogenic receptors. Institution: University of California San Francisco School: School of Medicine Department: Cardiovascular Research Institute Position: Assistant Professor Her research focuses on the structural dynamics of receptor tyrosine kinases, particularly in the context of cancer signaling. She investigates how mutations, dimerization, glycosylation, and allosteric regulation affect the activity of receptors like HER2, HER3, and MET. Her work also extends to pseudokinases such as TRIB2 and PEAK3, exploring their scaffolding roles and regulatory mechanisms. Additionally, she has contributed to understanding host-pathogen interactions, especially in SARS-CoV-2, through large-scale protein interaction mapping. The recent publications highlight a strong trend in structural biology and cancer signaling, with an emphasis on using cryo-EM to resolve full-length receptor complexes and uncover novel activation mechanisms. Her work integrates biophysics, genomics, and functional assays to map resistance mutations and regulatory motifs in kinase domains. The research spans oncology, virology, and cellular stress response, demonstrating a multidisciplinary approach to understanding disease mechanisms. While no specific scientific awards are listed in the provided text, her frequent publications in top-tier journals such as Nature , Cell , and eLife reflect significant scholarly impact. She is also involved in methodological advances, including cryo-EM sample preparation and ligand-mediated pulldown techniques. Natalia Jura leads the Jura Lab at UCSF, where she mentors students and researchers in structural and molecular biology. Her lab collaborates widely across UCSF, particularly with the Krogan and Fraser labs, contributing to large consortia such as the QCRG (Quantitative Biosciences Institute Coronavirus Research Group). The lab’s work on kinase regulation, pseudokinases, and cancer signaling continues to advance precision oncology and therapeutic development.

Mohamed E Abazeedمشاهده پروفایل

استاد

• Lung Cancer
• Radiation Oncology
• Bioinformatics
• +۷ مورد دیگر

Mohamed E Abazeed, MD, PhD serves as Chair of the Department of Radiation Oncology and holds the William N. Brand, MD Professorship at Northwestern University's Feinberg School of Medicine. He also co-leads the Lung Cancer Program at the Robert H. Lurie Comprehensive Cancer Center. Dr. Abazeed specializes in the care of patients with thoracic cancers and leads a research team focused on developing data-driven tools to personalize and improve cancer treatment. Dr. Abazeed received his BS, MD, and PhD (in Biological Chemistry) from the University of Michigan. He completed a postdoctoral fellowship in Cancer Genomics at the Broad Institute (MIT), followed by residency training in Radiation Oncology at Harvard University. He is board certified by the American Board of Radiology (DABR). Dr. Abazeed's research focuses on the intersection of radiation oncology, cancer genomics, and artificial intelligence. His work aims to improve therapies for lung cancer patients across the translational science spectrum, including developing new technologies and advancing biomarker and augmented intelligence studies. His team has made significant contributions to identifying tumor mutations and cancer cell states that confer resistance to anti-cancer therapies and has developed new technologies designed to predict treatment response. His clinical expertise centers on thoracic cancers, particularly lung cancer. His recent publications demonstrate a strong trend toward applying artificial intelligence and deep learning to radiation oncology challenges, including tumor segmentation, risk stratification, and ethical implementation of AI in medical imaging. These works reflect his commitment to precision medicine and data-driven approaches to cancer care. Dr. Abazeed has received numerous scientific awards including: ARRO Educator of the Year (2021) Emerging Leader Award, AACR/ASTRO/NCI (2018) Young Innovator Award, Cleveland Clinic Foundation (2017) Advanced Clinical Research Award, ASCO and Conquer Cancer Foundation (2017) ASCO's Young Investigator Award (2017) Dr. Abazeed serves as principal investigator on four active grants and leads the RAD-AI clinical trial, a Phase II study of personalized dose guidance for stereotactic body radiotherapy in lung tumor patients. He also holds six patents that, in part, describe inventions of first-in-class technology for patients receiving radiotherapy. As editor, he serves as Guest Editor for Frontiers in Genetics (2021-Present) and Associate Editor for Advances in Radiation Oncology (2016-Present). Dr. Abazeed leads a multidisciplinary research team focused on developing data-driven tools for personalized cancer treatment. His laboratory work integrates cancer genomics, computational biology, and machine learning to identify tumor mutations and cancer cell states that confer resistance to therapies. He is actively involved in the Robert H. Lurie Comprehensive Cancer Center's Lung Cancer Program, where he collaborates with oncologists, radiologists, and computational scientists to advance lung cancer research and treatment through precision medicine approaches.

Douglas Richardsonمشاهده پروفایل

مدرس

• Light Microscopy
• Super-resolution Microscopy
• Tissue Clearing
• +۳ مورد دیگر

Douglas Richardson serves as Director of Imaging at the Harvard Center for Biological Imaging (HCBI) since 2013 and Lecturer in Molecular and Cellular Biology within Harvard's Faculty of Arts and Sciences since 2016. He leads a state-of-the-art microscopy core facility serving Harvard and Greater Boston researchers through confocal, light sheet, super-resolution, and slide scanning systems. His educational background includes: PhD in Cancer Cell Biology from Queen's University (Canada), Department of Pathology and Molecular Medicine Alexander von Humboldt Postdoctoral Fellowship at Max Planck Institute for Biophysical Chemistry under Nobel Laureate Stefan Hell Richardson's research expertise spans super-resolution microscopy , light sheet imaging , tissue clearing techniques , and image processing methodologies . He actively develops and evaluates advanced microscopy approaches for biological applications in cancer, neuroscience, and ophthalmology. His work emphasizes practical implementation of cutting-edge imaging technologies for diverse research questions. Analysis of his recent publications reveals dominant trends in 3D tissue imaging applied to neurodegenerative diseases (Alzheimer's), cancer biology (melanoma, breast cancer), and vascular ophthalmology. His contributions to tissue clearing standardization and light sheet microscopy optimization enable high-resolution whole-organ analysis, while his technical tutorials address critical microscopy artifacts. His scientific recognition includes: Alexander von Humboldt Postdoctoral Fellowship Richardson teaches MCB 68 (Cell Biology through the Microscope) and MCB 352 (Microscopy), directs the HCBI Lunch and Learn Lecture Series, and organizes tissue clearing workshops. The HCBI facility he leads provides critical infrastructure for Harvard researchers, with recent expansions including high-content screening (2024) and Zeiss Lightfield 4D integration (2025). Under Richardson's leadership, the Harvard Center for Biological Imaging serves as a national resource for advanced microscopy training and consultation, maintaining active YouTube educational content and developing protocols for challenging biological specimens through its tissue clearing initiatives.

Jesse D. Bloomمشاهده پروفایل

دانشیار

• Molecular Evolution
• Virology
• Computational Biology
• +۲ مورد دیگر

Jesse D. Bloom is an Associate Professor in Microbiology at the University of Washington and an Assistant Member at the Fred Hutchinson Cancer Research Center (Fred Hutch). He leads the Bloom Lab, which integrates experimental and computational approaches to study molecular evolution, viral proteins, and immune interactions. The lab is affiliated with the UW Genome Sciences Department and the Howard Hughes Medical Institute (HHMI). Research Focus: Evolution of viruses (influenza, SARS-CoV-2, RSV), deep mutational scanning, antigenic drift, and antibody escape mechanisms. Key Tools: Development of high-throughput assays like sequencing-based neutralization and yeast-display escape calculators. Recent Publications highlight trends in viral evolution, including pleiotropic constraints on hemagglutinin stability and the impact of immune imprinting on SARS-CoV-2 antibody specificity. His work informs vaccine design (e.g., stabilized H5 HA) and tracks antigenic changes across pathogens. Awards: HHMI Investigator. Students: Mentions graduate researchers like Caleb Carr, Caroline Kikawa, and Tim Yu. Lab Affiliation: Based in Fred Hutch's Basic Sciences Division, with collaborative ties to UW's Microbiology and Genome Sciences departments.

• Breast Cancer
• Cancer and Oncology
• Basic Cancer Research
• +۶ مورد دیگر

Johan Vallon-Christersson is a Researcher at Lund University Cancer Centre (LUCC) , Department of Clinical Sciences, Lund University. His work focuses on breast cancer genomics , epigenetics , and molecular subtyping , particularly in ER-positive/HER2-negative and triple-negative breast cancer subgroups. Recent research includes multi-omics analyses of high-risk breast cancer subtypes through the SCAN-B cohort, investigating alternative promoter methylation in endocrine resistance, and Caveolin-1's role in tumor aggressiveness. He contributes to bioinformatics infrastructure for genomic data analysis and participates in LUCC collaborative conferences as a speaker. His publications emphasize genomic characterization , epigenetic regulation , and machine learning applications in breast cancer diagnostics. Key projects include Integrative molecular analyses of ER+/HER2- disease (2022–ongoing), where he serves as an assistant supervisor.

• Machine Learning
• Computational Biology
• Structural Biology
• +۳ مورد دیگر

Valentina Sora is a Postdoc in the Machine Learning section at the Department of Computer Science , University of Copenhagen , focusing on interdisciplinary research at the intersection of machine learning and structural biology. Research Interests Developing machine learning algorithms for quantum-classical simulations in computational chemistry . Modeling biological data with applications in autophagy , cancer genomics , and protein structure networks . Designing computational tools for protein interaction network analysis and high-throughput mutational scans . Key Trends in Publications Her work bridges machine learning and quantum computing with structural biology , emphasizing protein dynamics , mutation effects , and biomolecular simulations . Recent studies apply deep learning to gene expression and genomic variant interpretation , alongside quantum embedding for molecular assemblies. Collaborations span computational biology, quantum chemistry, and cancer research with institutions like the SCIENCE AI Centre at the University of Copenhagen and researchers such as Yevgeny Seldin and Andrea Krogh .

• Systems Science
• Medical Robotics
• MRI Technology
• +۲ مورد دیگر

Alpay Özcan is a Professor in the Department of Electrical and Electronics Engineering at Bogazici University. He directs the Systems Science and Mathematics Laboratory (SSML) and Magnetic Medical Devices Laboratory (MMDL). Özcan holds a DSc in Systems Science from Washington University and an MSc from Imperial College London. Research integrates systems theory with biomedical applications, including MRI-compatible robotics, diffusion tensor imaging, and AI-driven cancer diagnostics. Recent work develops nanoparticle-enhanced MRI techniques and deep learning models for glioma genotyping using multiparametric scans. He pioneered robotic systems for real-time MRI-guided interventions at Washington University. Current projects involve QSM mapping for neurodegeneration, hyperthermia devices, and low-complexity imaging algorithms. Özcan collaborates globally on neuro-oncology studies using advanced MR spectroscopy and diffusion analysis.

Christopher Byron Brookeمشاهده پروفایل

دانشیار

• Host-Pathogen Interactions
• Molecular Evolution
• Molecular Immunology
• +۳ مورد دیگر

Christopher Byron Brooke is an Associate Professor at the University of Illinois, affiliated with the Carl R. Woese Institute for Genomic Biology and the Interdisciplinary Health Sciences Institute. He holds a B.A. in Biology from Washington University (2003), a Ph.D. in Microbiology & Immunology from the University of North Carolina (2010), and completed a postdoctoral fellowship in Viral Immunology at the NIAID's Laboratory of Viral Diseases (2010-2015). His research focuses on understanding viral replication, pathogenesis, and evolution, particularly in influenza virus. Key areas include viral heterogeneity's impact on evolution, immune escape mechanisms, and collective interactions within viral populations. His lab employs techniques like single-cell microfluidics, ultra-deep sequencing, and mathematical modeling. Recent work explores how viral genetic diversity influences infection outcomes and vaccine strategies. Brooke's publications (62 total) span virology, molecular biology, and evolutionary biology, with recent articles addressing avian influenza vaccines, viral protein constraints, and proteome expansion. His work has been featured in journals like Cell Reports , Nucleic Acids Research , and PLoS Pathogens . He collaborates globally and engages in public health discourse, advising on vaccine strategies and pandemic preparedness. His lab's future directions include refining universal influenza vaccines and dissecting host-virus interactions at single-cell resolution.

David McCandlishمشاهده پروفایل

دانشیار

• Computational Biology
• Molecular Evolution
• Protein Engineering
• +۱ مورد دیگر

Dr. David McCandlish is Associate Professor at Cold Spring Harbor Laboratory, where he develops computational tools to predict mutational effects using deep mutational scanning data. Research focus: Modeling higher-order genetic interactions Predicting evolutionary trajectories in proteins Analyzing cancer mutation patterns Developed MAVE-NN framework for learning sequence-function relationships from multiplex assays. Research integrates biophysics, machine learning, and evolutionary theory to understand protein evolution and design. Honors include Sloan Research Fellowship. Teaches graduate courses on Gaussian Processes and Quantitative Biology. Mentors students in interdisciplinary projects combining computational and experimental approaches.

Hee Jung Chungمشاهده پروفایل

دانشیار

• Epilepsy Research
• Neurological Disorders
• Ion Channel Function
• +۳ مورد دیگر

Hee Jung Chung is an Associate Professor in the Department of Molecular and Integrative Physiology at the University of Illinois at Urbana-Champaign (UIUC), with affiliations in the Neuroscience Program and the Beckman Institute for Advanced Science and Technology. Her research focuses on understanding mechanisms underlying homeostatic plasticity and epilepsy, particularly the role of ion channels like KCNQ/Kv7 in neuronal excitability. She holds a B.S. from Cornell University (1995), a Ph.D. from Johns Hopkins University School of Medicine (2002), and completed postdoctoral training at the University of California, San Francisco (2002-2009). Her work combines interdisciplinary approaches—neuronal culture, microscopy, biochemistry, and mouse genetics—to investigate how ion channel mutations contribute to epilepsy and how homeostatic plasticity regulates neuronal activity. Key projects include studying Kv7 channel localization and function in axons, and the role of STEP61 in synaptic plasticity and disease. Her lab develops novel tools, such as in vitro platforms for neuronal interfacing and advanced imaging techniques like artificial confocal microscopy. Dr. Chung’s research has been recognized with awards including the James E. Heath Award for teaching excellence (2014) and grants from the Epilepsy Foundation and March of Dimes. Her recent publications span topics like exosome-mediated brain-muscle communication, STEP61’s role in hyperexcitability disorders, and Kv7 channel dysfunction in epileptic encephalopathy. Her lab’s future directions include developing transgenic models to study homeostatic plasticity in vivo and exploring therapeutic strategies for epilepsy mutations. Collaborations extend to imaging technology, neuroengineering, and translational medicine.

John P. Bartonمشاهده پروفایل

دانشیار

• Pathogen Evolution
• Innate Immunity
• Computational Biology
• +۴ مورد دیگر

John P. Barton is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. He holds a PhD in Physics from Rutgers University and completed postdoctoral training at MIT. His research focuses on pathogen evolution, innate immunity, and computational methods to analyze viral dynamics and immune responses. He is currently an invited professor at QBio (ENS-PSL) collaborating on quantitative biology projects. Education: PhD in Physics, Rutgers University Postdoctoral Fellowship, MIT (Institute for Medical Engineering and Science) Previous faculty position at University of California, Riverside Research Interests: Dr. Barton develops quantitative models to study viral evolution (e.g., HIV, SARS-CoV-2) and immune system interactions. His lab uses statistical physics, machine learning, and population genetics to predict pathogen behavior and improve vaccine design. Collaborations: Active collaborations with QBio researchers (Simona Cocco, Rémi Monasson) and multidisciplinary teams combining physics, biology, and medicine. His work bridges theoretical frameworks with experimental data from viral sequencing and immune cell studies. Labs/Teams: Leads the Barton Lab at the University of Pittsburgh, focusing on computational biology approaches to infectious disease and immunity.

• Computational Biochemistry
• Drug Design
• Molecular Thermodynamics
• +۴ مورد دیگر

Dr. Matteo Ferla is a Postdoctoral Researcher at the University of Oxford's Department of Biochemistry, affiliated with the Oxford Protein Informatics Group. His research focuses on computational biochemistry, drug design, and molecular thermodynamics, with a growing interest in deep learning applications. He develops tools like Fragmenstein (for fragment-based drug discovery), Michelanglo (protein structure visualization), and Venus (variant functional analysis). His work bridges structural biology, bioinformatics, and experimental validation, contributing to understanding protein-ligand interactions, genetic variants' effects, and drug development. Key Projects: Fragmenstein: A computational tool stitching molecules for drug discovery. Michelanglo: Web-based protein structure annotation platform. Venus: Analyzes missense variants' functional impacts beyond structural destabilization. Research Themes: Fragment-based drug design. Computational methods for protein engineering. Genetic and structural basis of rare diseases. Publications: Over 20 peer-reviewed articles, including high-impact contributions to Science , Genome Medicine , and Brain , focusing on SARS-CoV-2 inhibitors, genetic disorder mechanisms, and structural biology tools.

Noah Zaitlenمشاهده پروفایل

استاد

• Genetics
• Genomics
• Medical Informatics
• +۷ مورد دیگر

Noah Zaitlen is a Professor in both the Department of Neurology and the Department of Human Genetics at the University of California Los Angeles (UCLA) . Research focuses on genetics, genomics, and computational biology with applications in neurology and precision medicine. Active grants include NIH-funded projects on gene regulation, epigenomics, and multi-ethnic population health. Key publications address cancer heterogeneity, neurodegenerative disease biomarkers, and computational methods in genomics. His work spans genetic architecture , epigenetic stratification , and AI-driven biomedical imaging . Recent studies explore cell-free DNA methylation , gene-environment interactions , and multi-ancestry polygenic mechanisms . Although no formal awards are listed, his collaborative NIH grants and leadership in multi-institutional consortia highlight his impact. He also contributes to graduate mentorship and genetic methodology development at UCLA.