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Zhengjie ZhouView profile

Assistant Professor

• Nanomedicine
• Cell Biology
• Translational Medicine
• +7 more

Zhengjie Zhou is an Assistant Professor in the Center for Inflammation and Lung Research (CILR) at the Lewis Katz School of Medicine , Temple University. His work bridges nanomedicine, vascular biology, and pulmonary research to develop cell-targeted therapies for inflammatory lung diseases. Education : PhD in Biochemistry and Molecular Biology from East China Normal University (2013–2018), BS in Pharmacy and Organic Chemistry from Lanzhou University (2009–2013). Research Interests : The Zhou Lab focuses on precise modulation of cell-specific signaling pathways in inflammation and disease. Key areas include: Lung Biology in Inflammation and Injury Nanomedicine and mRNA-loaded Lipid Nanoparticles Endothelial Mechanosensitivity in Vascular Inflammation Scientific Trends : Recent work emphasizes mRNA delivery systems for vascular and lung diseases (2025), targeted nanocarriers for fibrosis (2025), and polyelectrolyte micelles for vascular complications (2021). Earlier studies explore photothermal cancer therapies (2016–2020) and autophagy modulation (2016–2017). Scientific Awards : K99/R00 Pathway to Independence Award (2023) Janet D. Rowley Research Day Award (2022) President Scholarship, ECNU (2017) National Scholarship (2016) Multiple travel awards (2023–2024) Labs & Collaborations : The Zhou Lab is located in the Medical Education & Research Building (Floor 11) , Temple University Medical Campus. It combines molecular biology , nanoparticle engineering , and in vivo models to advance therapies for ARDS, viral pneumonia, and fibrotic disorders.

Judith ReindlView profile

Associate Professor

• Particle Radiation Effects
• Radiation Protection
• Cancer Treatment Development
• +5 more

Judith Reindl is an Associate Professor at the University of Oslo, where she focuses on Biophysics and Medical Physics. Her research integrates fundamental physics with engineering and biomedical applications to study particle radiation effects on biological systems. She is actively investigating particle minibeam and FLASH radiotherapy technologies, radiation protection strategies for space missions (e.g., Mars expeditions), and radiation-hardened electronics for space and fusion technologies. Research Focus: Her interdisciplinary work spans: Radiation impact on cellular structures and organs Development of advanced radiotherapy systems for cancer treatment Space radiation shielding and electronic device resilience Biological experiments elucidating particle radiation mechanisms Publication Trends: Recent articles (2024–2025) emphasize experimental methodologies for radiation research, translational applications of focused ion beams in medicine, and pre-clinical tools for radiotherapy innovation. These reflect her core themes: physics-engineering-biology integration, scalable radiation technologies, and solutions for terrestrial/space challenges.

• Oncology
• Radiotherapy
• Palliative Care
• +4 more

Astrid Dalhaug serves as a University Lecturer at the Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway. Her academic work focuses on clinical oncology with particular emphasis on cancer treatment outcomes in rural healthcare settings across Northern Norway. Dr. Dalhaug's research interests center on oncology, specifically radiotherapy, palliative care, and survival prediction models for cancer patients. Her work frequently addresses the challenges of delivering quality cancer care in remote regions with scattered populations. She investigates prognostic factors in various cancer types including prostate cancer, lung cancer, and brain metastases, with special attention to biomarkers, treatment fractionation, and demographic variables that influence patient outcomes. Analysis of her publication record reveals a consistent focus on developing and validating practical prognostic tools for clinical use, particularly the LabPS and LabBM scores. Her research demonstrates how serum biomarkers can enhance survival prediction accuracy across different cancer types and metastatic presentations. A distinctive feature of her work is the examination of rural healthcare delivery challenges and their impact on cancer treatment outcomes in Northern Norway's unique geographical context. Dr. Dalhaug maintains a highly productive research collaboration, most notably with Carsten Nieder, with whom she has co-authored numerous studies across multiple cancer types and treatment modalities. Her work spans clinical trials, retrospective analyses, and validation studies that contribute significantly to evidence-based oncology practice, particularly in resource-limited or geographically isolated settings.

Valerie SpeirsView profile

Professor

• Molecular Oncology
• Breast Cancer
• Glioblastoma
• +7 more

Professor Valerie Speirs is Chair in Molecular Oncology at the University of Aberdeen, with a visiting professorship at the University of Leeds. She holds a BSc in Zoology (1986, University of Aberdeen) and a PhD in Cancer Biology (1990, University of Glasgow). Her research focuses on breast cancer biology, tumor-stroma interactions, oestrogen receptor dynamics, and environmental endocrine disruptors. She employs advanced techniques including 3D cell culture, digital pathology, and Raman spectroscopy. Established Aberdeen Cancer Centre for translational research Co-PI for Breast Cancer Now Tissue Bank Founder of SEARCHBreast initiative Current funding includes grants from Breast Cancer Now, NC3Rs, and Animal Free Research UK. She supervises PhD students in biomedical sciences and has led international collaborations with institutions in London, Leeds, and Nottingham. Her awards include the Breast Cancer Now Outstanding Contribution award (2011) and multiple conference prizes.

Joseph A. GogosView profile

Professor

• Schizophrenia Research
• Genetics of Psychiatric Disorders
• Neural Circuit Mechanisms
• +5 more

Joseph A. Gogos, MD, PhD is a Professor of Neuroscience and Physiology and Cellular Biophysics at Columbia University's Vagelos College of Physicians and Surgeons. He serves as Codirector of Columbia's Stavros Niarchos Foundation Center for Precision Psychiatry and Mental Health and is a Principal Investigator at Columbia's Zuckerman Mind Brain Behavior Institute. Dr. Gogos's research focuses on understanding the molecular, cellular, synaptic and circuit mechanisms that give rise to schizophrenia. His work combines human genetic studies with animal models to trace how specific genetic mutations lead to psychiatric disorders. He has made significant contributions to identifying rare de novo and inherited mutations that increase schizophrenia risk and has developed relevant model systems to understand their impact on neural mechanisms. His laboratory has published extensively in top journals including Neuron, Nature, and Cell, with recent work focusing on brain organoids, neural circuitry, and precision psychiatry approaches. Dr. Gogos's research has demonstrated the potential to reverse schizophrenia-related phenotypes in animal models, paving the way for new therapeutic strategies. His notable awards include: Brain & Behavior Research Foundation Distinguished Investigator Award (2017) Columbia University Dr. Harold and Golden Lamport Research Award in Clinical Sciences (2004) Dr. Gogos actively mentors students and postdoctoral researchers through the Doctoral Program in Neurobiology and Behavior and maintains an active laboratory recruiting scientists with expertise in genome engineering, behavioral experimentation, electrophysiology, and neural circuit manipulation. His collaborative work at the Zuckerman Institute brings together diverse scientific perspectives to address the complex challenges of psychiatric disorders. His laboratory is located at the Jerome L. Greene Science Center as part of the Mortimer B. Zuckerman Mind Brain Behavior Institute, providing state-of-the-art facilities for neuroscience research.

Maged HenaryView profile

Assistant Professor

• Synthetic Organic Chemistry
• Fluorophore Design
• In Vivo Imaging
• +2 more

Maged Henary is an Assistant Professor at Georgia State University's College of Arts & Sciences, specializing in synthetic organic chemistry with applications in biomedical imaging and cancer therapy. Research focuses on designing near-infrared fluorophores for medical imaging, developing DNA-targeted anticancer agents, and creating sensors for biological applications. Recent work includes fluorophores for endocrine gland imaging, G-quadruplex DNA binders, and pH-sensitive probes. Publication trends show strong emphasis on: Cyanine/squaraine fluorophore design Optoacoustic imaging contrast agents Targeted cancer therapeutics Metal/pH sensing molecules Dr. Henary leads an active research laboratory developing novel imaging agents and maintains collaborations with medical institutions for translational applications.

Deni S. GalileoView profile

Professor

• Cell Migration
• Neurobiology
• Developmental Biology
• +3 more

Deni S. Galileo is a Professor in the Department of Biological Sciences at the University of Delaware. His research focuses on cell migration mechanisms in the developing brain and malignant gliomas, utilizing chick embryo models and retroviral gene transfer technologies. His work explores how integrins, extracellular matrix molecules, and adhesion proteins like L1CAM regulate normal and abnormal cell migration. Key projects include developing novel models for studying glioma invasiveness and breast cancer brain metastases, and investigating the role of QSOX1 and PMCA4 in tumor progression. Education: B.A., New College of Florida Ph.D., University of Florida College of Medicine and Whitney Laboratory Postdoctoral Research, Washington University School of Medicine (St. Louis) Research interests span developmental neurobiology, tumor biology, and gene therapy. Current projects include: Control of glioma invasiveness via L1CAM Integrins' roles in neuronal migration and survival Ex vivo analysis of glioblastoma behavior using chick embryos His lab has pioneered the use of replication-competent retroviral vectors and in ovo electroporation for widespread protein misexpression in developing brains. Collaborations with Dr. John Koh (Chemistry and Biochemistry) explore axon outgrowth on gene-patterned cell monolayers. Lab Resources: Office 232 Wolf Hall, Lab 248 Wolf Hall Teaching: Courses include Cell Biology (BISC 305), Developmental Neurobiology (BISC 439/639), and Special Topics in Modern Biological Microscopy (BISC 400). Notable contributions include establishing chick embryo models for studying glioma and breast cancer metastasis to the brain, and discovering roles for integrin α6β1 and α8β1 in cell migration and survival.

• Cancer Biology
• Oncology
• Molecular Biology
• +3 more

Weei-Chin Lin is a Professor at Baylor College of Medicine , affiliated with the Department of Medicine and cross-appointed to the Department of Molecular & Cellular Biology and Duncan Cancer Center . His research focuses on Cancer Biology , Molecular Biology , and Biochemistry , particularly mechanisms of DNA damage response, oncogenic pathways, and therapeutic targeting. Selected publications highlight work on TopBP1 in cancer, PARP inhibitors , EGFR regulation , and 14-3-3 proteins . Key themes include synthetic lethality , checkpoint control , ubiquitination , and metastasis mechanisms . Scientific awards include NIH grants, NIH BCO Study Section member (2025-2029) Cancer Center pilot awards Leukemia & Lymphoma Society Scholar (2006-2011) His work bridges translational oncology and molecular mechanisms , with clinical implications for chemotherapy resistance and novel cancer therapies .

Marc De BenedettiView profile

Assistant Professor

• Machine Learning
• Medical Data Analysis
• Geophysical Modeling
• +3 more

Marc De Benedetti is an Assistant Professor, Teaching Stream in the Department of Computer Science at the University of Toronto's Mississauga campus within the Mathematical and Computational Sciences school. His work bridges computational methods with healthcare analytics, geophysical modeling, and educational innovation. He specializes in applying machine learning to medical datasets (e.g., SEER cancer data) for predictive modeling and has contributed to CAR T-cell therapy efficacy studies in oncology. His geoscience research focuses on spatial-temporal variability in climate systems, particularly in the Congo Basin and UK wind dynamics. De Benedetti also designs supplementary educational programs to support undergraduate STEM learners. His research emphasizes data-driven approaches to address challenges in healthcare, environmental science, and pedagogy. Research interests include: Machine learning applications in healthcare survival prediction Immunotherapy comparative efficacy analysis Spatial variability in climate and hydrology systems Wind energy potential modeling Innovative undergraduate physics/mathematics tutoring strategies His recent articles analyze treatment outcomes for blood cancers using CAR T-cell therapies, explore model resolution impacts on geophysical data accuracy, and develop predictive tools for cancer prognosis via SEER datasets. No scientific awards are explicitly mentioned in the provided materials. While no formal grants or student advisement records are listed, his work demonstrates strong engagement with both academic research and educational development initiatives. His research locations include the Congo Basin for hydroclimatic studies and the UK for wind energy modeling. Collaborations likely span medical institutions for oncology studies and climatological agencies for environmental data analysis.

• Transparent and Reliable AI
• Precision Biomedicine
• Personalized Healthcare
• +4 more

Dr. Tapabrata Chakraborty is a Principal Research Fellow at University College London (UCL) Cancer Institute and an Honorary Associate Professor in UCL's Department of Medical Physics and Biomedical Engineering. He serves as Lead Tutor for Information Engineering at the University of Oxford's Engineering Science Department and is a non-stipendiary Fellow of Linacre College, Oxford. As Theme Lead for the Alan Turing Institute's partnership with Roche, he drives advancements in transparent AI for precision healthcare. He is an invited expert on Responsible AI with the Global Partnership on AI (GPAI) and an Associate Editor for Springer Nature Computer Science . His research focuses on developing reliable AI systems for biomedicine, particularly leveraging multimodal data (imaging, clinicogenomics) in cancer research. He emphasizes explainable AI mechanisms, personalized uncertainty quantification, and ethical AI governance. His work has led to tools like 2dSpAn-Auto for spine analysis and frameworks like Pan-Ret for retinal disease detection. Education: PhD (details unspecified) Key Roles: Turing-Roche Partnership Lead, GPAI Advisor, HEA/IET Fellow His publications highlight breakthroughs in medical AI, including uncertainty quantification and multimodal data fusion. He advocates clinician-AI collaboration and policy-driven AI safety. Current projects include fair AI for skin lesion classification and drug discovery via synthetic data generation. Awards: HEA Fellowship, IET Fellowship Team Leadership: Oversees early-career researchers at Turing/UCL

Menggang YuView profile

Professor

• Causal Inference
• Observational Studies
• Risk Prediction
• +7 more

Dr. Menggang Yu is a Professor of Biostatistics at the University of Michigan School of Public Health. He holds academic leadership roles, including former Director of the Biostatistics Core at UW Carbone Cancer Center and Associate Director of the Center for Health Disparities Research. His expertise spans causal inference, clinical biostatistics, and precision health, with a focus on cancer and chronic disease research. Education: PhD in Biostatistics (University of Michigan, 2004), MS in Applied Statistics (Bowling Green State University, 1999), BS in Computational Mathematics (Fudan University, 1996). Research interests emphasize causal inference, risk prediction, and treatment selection, particularly in clinical trials and observational studies. His work addresses methodological challenges in healthcare, including optimal surveillance strategies and subgroup analysis. Key awards include the Distinguished Student Paper Award (ENAR 2023) and ASA Biometrics Section Travel Awards (2017, 2018). He collaborates widely, contributing to high-impact journals like Biometrics , Journal of the American Statistical Association , and Cancer Cell . Grants and lab involvement include leadership roles in cores for cancer research and health disparities. Courses taught include survival analysis, causal inference, and clinical trial biostatistics.

• Microbiome Research
• Hepatology
• Genetic Epidemiology
• +3 more

Xinlian Zhang is an Assistant Professor in Residence at the Herbert Wertheim School of Public Health & Human Longevity Science at UC San Diego. Their research focuses on microbiome dynamics, liver diseases (including NAFLD and alcoholic hepatitis), and statistical modeling in biomedical contexts. Collaborations include work with institutions like Altman Clinical and Translational Research Institute. Key research areas include the role of mycobiome and virome in liver pathology, host-microbiota interactions, and the application of advanced statistical methods to microbiome data. Zhang has contributed to studies linking microbiota composition to disease severity, drug responses, and psychological factors like loneliness. Publications emphasize interdisciplinary approaches, integrating virology, microbiology, and computational biology. Notable work includes analyzing fecal mycobiome in NAFLD patients and identifying virome signatures in alcoholic hepatitis. Co-authors include prominent researchers like B. Schnabl and R. Loomba. No specific awards or grants are listed, but their work has been cited widely (e.g., 87+ mentions for a 2020 Gastroenterology paper). Collaborations span institutions within the UC system and beyond, reflecting a network engaged in translational and computational biomedical research.

Evan BiederstedtView profile

Researcher

• Computational Biology
• Cancer Genomics
• Bioinformatics
• +3 more

Evan Biederstedt is an Associate in Biomedical Informatics at Harvard Medical School, affiliated with the Gehlenborg Lab. He holds a Master of Science (MSc) and specializes in computational biology with a focus on cancer genomics. His work includes developing the Cell Annotation Platform (CAP) to enhance cellular state interpretation through metadata and molecular signature analysis. Biederstedt’s research spans single-cell analysis, spatial transcriptomics, and genomic tools for structural variant discovery. His contributions include scaling cross-tissue annotation models and haplotype-aware somatic variation analysis. Key areas of focus include bioinformatics tool development, cancer genomics, and genomic data integration. He has collaborated on projects like the Virus Discovery Codeathon and international hackathons for genomic analysis. Biederstedt’s GitHub profile showcases his open-source contributions. His publications highlight advancements in tensor decomposition for patient cohort analysis, spatial transcriptomics, and pangenome strategies. Biederstedt’s work bridges computational methods with biomedical applications, emphasizing scalable solutions for complex genomic data challenges.

Walter O’DellView profile

Associate Professor

• Medical Imaging
• Radiation Oncology
• Biomedical Engineering
• +3 more

Walter O’Dell is an Associate Professor in the Department of Radiation Oncology at the University of Florida. His research focuses on developing novel image analysis and computational techniques to improve cancer detection, treatment follow-up, and therapy, particularly in stereotactic body radiation therapy (SBRT). The O’Dell Lab emphasizes translational research with direct clinical applications in patient care, alongside animal and in-vitro studies to validate findings. Key research areas include 3D tumor detection for lung, brain, and breast cancers; finite element modeling for needle biopsy deformation analysis; and quantitative CT imaging to assess radiation-induced tissue damage. Additionally, the lab explores MRI techniques such as diffusion-weighted imaging and spectroscopy for modeling tumor spread in brain cancers, as well as cardiac MRI tagging to study chemotherapy and radiation effects on long-term cancer survivors’ hearts. His work bridges engineering and medicine, aiming to enhance treatment precision and patient outcomes through advanced imaging technologies. The lab’s efforts include potential applications in drug development for protecting healthy tissues during radiation therapy.

Claes LundströmView profile

Adjunct Professor

• Medical Imaging
• Artificial Intelligence
• Digital Pathology
• +4 more

Claes Lundström is an Adjunct Professor at Linköping University's Department of Science and Technology (ITN), affiliated with the Media and Information Technology (MIT) school. His primary research focuses on medical imaging, integrating machine learning, visualization, and human-computer interaction in clinical settings. He leads the technical side of digital pathology research at the Center for Medical Image Science and Visualization (CMIV), directing national-scale grants and serving as Arena Director for the Analytic Imaging Diagnostics Arena (AIDA). Since 2010, he has held dual roles as Research Director at Sectra AB and academic researcher, driving innovations that translate into commercial healthcare solutions. Lundström's work spans AI-driven diagnostics, uncertainty visualization, and precision orthopedics, with contributions recognized through leadership in major projects like the €70M BIGPICTURE initiative. His academic credentials include a PhD (2007) and Docent degree (2014), alongside extensive industry collaboration. Education: PhD in 2007 and Docent degree in 2014 from Linköping University. PhD: 2007 Docent: 2014 Research interests emphasize AI integration in diagnostics, particularly digital pathology and medical imaging workflows. His work addresses challenges like domain adaptation in AI models, uncertainty quantification in segmentation tasks, and interactive visualization tools for clinicians. Recent projects include the VAI-B platform for AI validation in breast imaging and the BigPICTURE collaboration for global pathology data sharing. Key grants include leadership roles in national-scale projects, such as the AIDA arena and SCAPIS study-based AI lab. His contributions to AI ethics and clinical adoption include studies on human-AI collaboration and quality assurance frameworks. Lundström also oversees labs like CMIV and AIDA, fostering cross-disciplinary research in medical imaging and AI.