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Hutan AshrafianView profile

Professor

• Artificial Intelligence in Medicine
• Metabolic Surgery
• Health Policy
• +4 more

Professor Hutan Ashrafian is a clinician-scientist and surgeon at the University of Leeds Business School, holding dual roles as Professor of Research Impact and Senior Research Fellow at Imperial College London. His expertise spans AI in healthcare, metabolic surgery, and ancient history. He pioneered STARD-AI and QUADAS-AI guidelines for AI diagnostics, collaborated on AI-driven breast cancer screening with Google and NHS, and led global health policy initiatives. Ashrafian’s work bridges medicine, history, and philosophy, including his contributions to understanding historical figures’ medical conditions, such as King Tutankhamun’s epilepsy. He has authored over 550 publications, 12 books, and holds a PhD in computational physiology and an MBA with distinction. Awards include the Hunterian Prize and Wellcome Trust Fellowship. His research also explores AI ethics, quantum physics paradoxes, and art-based medical diagnostics. Education: PhD in Computational Physiology (Imperial College London) MBA (Warwick Business School) MD (University College London) Bachelor of Science in Immunology (University College London) Research Interests: Ashrafian’s work spans: AI in Medicine: Diagnostic algorithms, guideline development (STARD-AI/QUADAS-AI), and ethical frameworks. Metabolic Surgery: Bariatric interventions, gut microbiome, and obesity treatments. Ancient History: Medical analyses of historical figures (e.g., Tutankhamun, Julius Caesar) and art-based pathology identification. Philosophy: AI rights (AIONAI law), temporal paradoxes, and the Simulation Argument. Awards: Royal College of Surgeons Arris and Gale Lectureship Hunterian Prize Wellcome Trust Research Fellowship Advising & Innovation: Supervised >50 PhD students, co-founded Oxford Medical Products (weight loss tech), and serves as CSO at Flagship Pioneering’s Preemptive Health division. He advises on NHS digital transformation and global health policy. Labs/Teams: Leads AI initiatives at Imperial’s Institute of Global Health Innovation and collaborates with Google, NICE, and international institutions on health tech solutions.

• Epigenetics
• Retroelements
• Transposable elements
• +5 more

Didier Trono is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Laboratory of Virology and Genetics (LVG) within the School of Life Sciences. Formerly, from 2004 to 2012, he served as the founding dean of EPFL's Faculty of Life Sciences, orchestrating its development and growth during this formative period. Trono received his medical education at the University of Geneva, followed by clinical training in pathology, internal medicine, and infectious diseases in Geneva and at Massachusetts General Hospital in Boston. His scientific career began at the Whitehead Institute of MIT, and in 1990 he was recruited by the Salk Institute of San Diego to launch an AIDS research center. After seven years in the United States, he returned to Europe and eventually joined EPFL. Dr. Trono's research has evolved significantly over his career. Initially focusing on virus-host interactions, he studied pathogens like HIV and Hepatitis B virus, creating HIV-derived genetic transfer tools that are now successfully used in gene therapy. For approximately the last fifteen years, his research has centered on epigenetics, particularly exploring the impact of retroelements and their control mechanisms on development and physiology of higher organisms, including humans. His laboratory investigates how transposable elements and KRAB zinc finger proteins regulate gene expression, with important implications for understanding cancer biology and developing new diagnostic and therapeutic approaches. Analysis of his recent publications (2022-2024) reveals a strong focus on transposable elements, KRAB zinc finger proteins, and their roles in gene regulation and cancer. His work combines molecular biology, genomics, and bioinformatics approaches to understand how these ancient viral remnants have been co-opted by the host genome to regulate development and cellular functions. The research spans basic molecular mechanisms to potential clinical applications in cancer diagnosis and therapy, with some recent work also addressing SARS-CoV-2 and immune responses. Throughout his career, Professor Trono has mentored numerous PhD students, including Bojkowska Karolina, Brandão Sanches Vong Martins Filipe Amândio, Bulliard Yannick, Coluccio Andrea, Corsinotti Andrea, Coudray Alexandre, De Tribolet-Hardy Jonas Caspar, and Dorschel Iris Arianna. His laboratory has received significant funding to support research at the intersection of virology, genetics, and epigenetics, contributing to EPFL's reputation as a leading institution in life sciences research. The Trono Laboratory continues to be at the forefront of research on retroelements and their regulatory mechanisms, maintaining a vibrant research environment that bridges fundamental biological questions with potential medical applications, particularly in cancer research and precision medicine.

• Nutrition and Chronic Disease
• Cancer Epidemiology
• Obesity and Physical Activity
• +3 more

Dagfinn Aune serves as a Research Fellow at the Department of Epidemiology and Biostatistics within the School of Public Health, Faculty of Medicine at Imperial College London. He concurrently holds positions as Associate Professor at Oslo New University College and Senior Researcher at the Cancer Registry of Norway in Oslo. His work centers on large-scale epidemiological investigations into diet, obesity, and chronic disease mechanisms across international populations. Education: PhD in Epidemiology, Norwegian University of Science and Technology (2016) MSc in Nutrition, University of Oslo (2008) Research interests focus on the interplay between dietary patterns, adiposity, physical activity, and smoking with chronic disease outcomes. His work examines how these factors influence cancer risk (particularly breast, gastrointestinal, and hematological malignancies), pregnancy complications, diabetes progression, and mortality across diverse populations. He employs systematic review methodologies and analyzes data from major cohorts including EPIC and Norwegian registries. Publication trends reveal consistent emphasis on obesity-cancer relationships, with recent work (2023-2025) expanding into metabolomic mediators, cardiometabolic interactions, and rare cancer epidemiology. His research frequently utilizes systematic reviews, meta-analyses, and multinational cohort studies to establish evidence for cancer prevention guidelines. Scientific Awards: No awards specified in source materials Advising and grant activity centers on major collaborative projects including the World Cancer Research Fund's Continuous Update Project, the EPIC study, and South American case-control research. While specific student mentorship isn't documented, his leadership in systematic review protocols suggests substantial training responsibilities. His grant portfolio includes funding from WCRF International and Norwegian research councils for large-scale epidemiological analyses. Labs and teams include the Centre for Translational Nutrition and Food Research at Imperial College London, where he collaborates with nutrition scientists and biostatisticians. He maintains active roles in the EPIC consortium and WCRF International's CUP Global Programme, coordinating multinational analyses of diet-cancer relationships through the Cancer Registry of Norway.

Thomas WalzView profile

Professor

• Membrane Biology
• Structural Biology
• Cryo-electron Microscopy
• +5 more

Thomas Walz, PhD, is a Professor at The Rockefeller University and Head of the Laboratory of Molecular Electron Microscopy. Previously, he held positions as Assistant, Associate, and Professor at Harvard Medical School (1999–2015) and was an Investigator at the Howard Hughes Medical Institute (2008–2015). He earned his PhD and BS in biophysics from the University of Basel, Switzerland, and completed postdoctoral research at the University of Sheffield. Walz completed his education at the Biozentrum, University of Basel, Switzerland, where he received his Diploma in Biophysics (1992) and PhD in Biophysics (1996). He furthered his training as a postdoctoral researcher at the University of Sheffield (1996–1999). His research focuses on understanding membrane-related processes and the structural biology of membrane proteins in lipid environments. Utilizing cryo-electron microscopy and nanodisc technology, he investigates how lipid bilayers influence membrane protein structure and function. Key areas include mechanosensitive channels, T-cell receptor dynamics, and telomere maintenance mechanisms. Collaborations with the de Lange lab explore the CST-Polα/primase complex's role in telomere regulation. Walz has been recognized with the Genzyme Award for Outstanding Achievement in Biomedical Sciences (2004) and continues to contribute to advancements in structural biology and membrane protein research. While specific student advisees are not listed, Walz actively mentors through his roles in the David Rockefeller Graduate Program and Tri-Institutional programs. His research is supported by grants and institutional funding, though specific grants are not detailed here. He directs the Laboratory of Molecular Electron Microscopy at Rockefeller, a hub for innovative structural biology and membrane protein studies. The lab collaborates widely, integrating cryo-EM with electrophysiology and molecular dynamics simulations.

Hang LuView profile

Professor

• Microfluidics
• Systems Biology
• Neuroscience
• +6 more

Hang Lu is a Professor and holds the Cecil J. "Pete" Silas Chair of Chemical & Biomolecular Engineering at the Georgia Institute of Technology. Dr. Lu also holds a Love Family Professorship and leads the Lµ Fluidics Group, which focuses on engineering microfluidic systems and machine learning tools to address complex questions in neuroscience, developmental biology, and cell biology that are difficult to address with conventional techniques. Dr. Lu's research lies at the intersection of engineering and biology, with primary interests including: Microfluidic systems for high-throughput screens and image-based genetics and genomics Systems biology: large-scale experimentation and data mining Microtechnologies for optical stimulation and optical recording Big data, machine vision, and automation Developmental neurobiology, behavioral neurobiology, and systems neuroscience Cancer biology, immunology, embryonic development, and stem cells Her laboratory engineers microfluidic devices and BioMEMS to study neuroscience, genetics, cancer biology, and biotechnology. These miniaturized Lab-on-a-chip tools operate at scales comparable to biological systems, leveraging unique micro and nano-scale phenomena to gather large-scale quantitative data about complex biological systems. Current projects include Microfluidics for Life Sciences, Optical Neuron Recordings and Manipulations, Machine Learning Tools for Neuroscience, Measuring and Modeling Behavior, and High-throughput, High-content Cell-based Assays. Analysis of Dr. Lu's recent publications (2024-2025) reveals a strong trend toward integrating microfluidics with advanced computational methods: Development of deep learning frameworks for biological image analysis Advanced neuron tracking and functional imaging techniques Non-invasive characterization of 3D organoid cultures Sophisticated neuromechanical modeling of locomotion Microfluidic temperature control systems for in vivo studies Label-free imaging pipelines for neural development Dr. Lu's significant professional honors include: Cecil J. "Pete" Silas Chair of Chemical & Biomolecular Engineering Love Family Professorship The Lµ Fluidics Group actively mentors students and postdocs, currently accepting new postdoctoral researchers. The lab receives substantial funding for interdisciplinary projects at the engineering-biology interface, with research implications spanning fundamental biological understanding to therapeutic development. The group operates within Georgia Tech's School of Chemical & Biomolecular Engineering, with specialized facilities for microfluidic device fabrication, biological experimentation, and advanced imaging, maintaining strong collaborative ties across engineering, neuroscience, and biological disciplines.

Syed Hani Hassan AbidiView profile

Associate Professor

• Virology
• Immunology
• Viral Oncology
• +7 more

Syed Hani Hassan Abidi is an Associate Professor at the Department of Biomedical Sciences , School of Medicine , Nazarbayev University , Kazakhstan. His research integrates virology , immunology , viral oncology , and bioinformatics , with a focus on HIV molecular epidemiology , viral evolution , and drug resistance . He has led international projects across Pakistan, Kenya, Afghanistan, and Kazakhstan, and is recognized for innovative teaching and MOOC development. Education: PhD in Virology and Immunology Research Interests: His laboratory employs bioinformatics (machine learning, AI), genomics , and proteomics to study HIV phylodynamics , viral co-infections , and oncogenic viruses like EBV in prostate cancer. He also explores microbiome-immunity interactions and designs antiviral drugs/vaccines . Recent Research Trends: His 2025 publications emphasize COVID-19 immunopathology , HIV/syphilis epidemiology in Pakistan , and particle physics contributions via ATLAS , showcasing interdisciplinary impact. Awards & Recognition: Outstanding Teachers Award (2019, Aga Khan University) Fellowship of Higher Education (UK, 2022) Teaching & Grants: He pioneered Pakistan’s first MOOC on Computer-Based Drug Discovery (2014) and received a 2022 SoTL grant for MOOC-based molecular biology education. His teaching integrates animations , films , and flipped classrooms . Collaborations & Labs: Leads projects on HIV drug resistance , HCV genomics in Kazakhstan , and AI-driven dementia diagnostics (Kazakh Brain Atlas). His lab collaborates with global institutions to advance viral disease surveillance and therapeutic innovation .

• Bayesian statistics
• Stochastic simulation
• Markov chain Monte Carlo
• +5 more

Professor Chris Holmes is a Professor of Biostatistics at the University of Oxford, where he moved from Imperial College London in February 2004. He is a Fellow at St Anne's College and works in the Department of Statistics. His research focuses on applications and statistical methods development in genomic sciences and genetic epidemiology, holding a prestigious Programme Leaders Grant in Statistical Genomics from the Medical Research Council. Prior to his position at Oxford, Professor Holmes completed his doctorate in Bayesian statistics at Imperial College London, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Before his academic career, he worked in industry for several years in scientific computing, developing techniques for real-time pattern recognition models in defense and SCADA systems. Professor Holmes has a broad interest in the theory, methods and applications of statistics and statistical modeling, with a particular foundation in Bayesian statistics which he views as providing a unified framework for stochastic modeling and information processing. His specific research interests include: Bayesian statistics and stochastic simulation Markov chain Monte Carlo methods Pattern recognition and nonlinear, nonparametric methods Spatial statistics Statistical genetics and genomics Genetic epidemiology His recent publications (2023-2025) demonstrate a strong focus on the intersection of biostatistics, artificial intelligence, and healthcare applications. His work spans multiple domains including AI-driven disease classification in neurology, genomic data analysis for health equity, machine learning tools for healthcare prediction, and addressing bias in medical AI systems. A notable trend across his research is the application of advanced statistical methods to solve pressing problems in genomics, epidemiology, and medical diagnostics, with an increasing emphasis on health equity and the ethical implications of AI in healthcare. Professor Holmes currently supervises PhD students Oscar Clivio, Sahra Ghalebikesabi, and Natalia Garcia Martin. His research is supported by multiple grants, including the MRC Programme Leaders Grant in Statistical Genomics which funds his work in statistical genomics. He is actively involved in three research groups at Oxford that reflect the breadth of his scholarly interests: Computational Statistics and Machine Learning Statistical Genetics and Epidemiology Statistical Theory and Methodology

• Leishmaniasis
• Immunology
• Parasitology
• +3 more

Deborah Frances Smith is a Professor affiliated with the Centre for Immunology and Infection. She has held former roles including Head Of Department, Biology Pro-Vice-Chancellor for Research, and Special Adviser to the Vice Chancellor in the Vice Chancellor's Office. She is also associated with CNAP (Cancer and Neuroscience Academic Programme) and the Jack Birch Unit. Her research focuses on leishmaniasis, parasite biology, and drug/vaccine development. Key projects include leading the 'C2D2 research 1a & 2b' (2012–2012) to establish sandfly colonies for leishmaniasis studies and co-investigating an integrated crystallization facility (2013–2018). She secured the Wolfson Research merit Award (2009–2010) from the Royal Society. Her work spans academic leadership, collaborative research, and translational medicine targeting neglected tropical diseases.

• Gynecologic Oncology
• Ovarian Cancer
• Breast Cancer
• +5 more

Federica Tomao is an Associate Professor at the Department of Maternal, Child and Urological Sciences within Sapienza University of Rome. She actively teaches and supervises courses in Medicine and Surgery , Nursing , and Midwifery programs across multiple institutions. Current faculty member with academic rank Teaching roles in 6th, 3rd, and 2nd year courses Specialized in gynecologic oncology Research Focus : Her work spans ovarian cancer, breast cancer, and endometrial cancer, emphasizing chemotherapy optimization, precision medicine, and radiomics. Notably, she contributes to understanding PARP inhibitors, immune checkpoint therapies, and fertility preservation techniques in cancer survivors. Recent Publications highlight advancements in sarcopenia analysis, BRCA testing, and radiogenomic nomograms. These studies demonstrate her commitment to bridging imaging and molecular data for improved cancer management. Email : federica.tomao@uniroma1.it

Alexis BattleView profile

Associate Professor

• Genomics
• Machine Learning
• Computational Biology
• +3 more

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .

Martin T. WellsView profile

Professor

• Applied Statistics
• Theoretical Statistics
• Bayesian Statistics
• +7 more

Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.

Pascal SyrenView profile

Researcher

• Cardiac Electrophysiology
• Histone Deacetylases
• Ventricular Arrhythmias
• +3 more

Dr. Pascal Syren is a **Researcher** and **Resident** at Heidelberg University Hospital (UKHD), affiliated with the **Department of Cardiology, Angiology, and Pulmonology** and the **Heidelberg Center for Cardiac Arrhythmias**. His academic role includes contributing to the **Group of Molecular and Translational Cardiac Electrophysiology**, focusing on epigenetic and molecular mechanisms underlying cardiac arrhythmias and heart failure. He holds a PhD from Heidelberg University (2021) on histone deacetylases' influence in cardiac electrophysiology. **Research Interests**: Cardiac electrophysiology, epigenetic regulation (HDACs), ventricular and atrial arrhythmias, echocardiography, and translational cardiology. His work spans basic science to clinical applications, emphasizing ion channel remodeling and therapeutic targets for heart rhythm disorders. **Awards**: Recipient of the **Ernst & Berta Grimmke Foundation Research Grant (2023–2024)** and **Otto-Hess Scholarship (2017–2018)** from the German Cardiac Society. His research bridges molecular mechanisms with clinical cardiology, with contributions to understanding HDAC2's role in action potential dynamics. **Publications**: Over 8 peer-reviewed articles (2016–2025) in journals like *Basic Research in Cardiology* and *Cells*, focusing on histone deacetylase pathways, atrial fibrillation, and ventricular arrhythmia models. Recent work explores neonatal cardiomyocyte electrophysiology and TREK-1 potassium channels in heart failure. **Affiliations**: Active member of the **German Cardiac Society (DGK)** and **European Society of Cardiology (ESC)**, contributing to interdisciplinary cardiac arrhythmia research at Heidelberg's medical faculty.

Olga DontsovaView profile

Professor

• Molecular Biology
• Bioorganic Chemistry
• Ribonucleoprotein Complexes
• +3 more

Olga Dontsova is a Full Professor at Moscow State University (MSU) in the Faculty of Chemistry. She serves as Head of the Division of RNA Structure and Function at the Belozersky Institute of Physico-Chemical Biology and Head of the Chair of Chemistry of Natural Compounds. Her research spans molecular biology, bioorganic chemistry, and RNA-based mechanisms. Research Focus: She investigates structure-functional relationships in ribonucleoprotein complexes, with emphasis on translation machinery, transfer-messenger RNA (tmRNA) interactions with ribosomes, RNA methyltransferases, and telomerase's role in cancer. Her team pioneered a chemical-biochemical-genetic approach to map mRNA topography in ribosomes, elucidate trans-translation dynamics, and characterize novel RNA-modifying enzymes. Scientific Contributions: Developed a molecular dynamic model for trans-translation Discovered unique yeast telomerase with unconventional properties Investigated functional roles of modified RNA residues in translation Honors: Member of Academia Europaea (2014) Corresponding Member of Russian Academy of Sciences (2006) European Academy Award for Young Scientists (1994) Grants & Leadership: Her work has been funded by HHMI, HFSP, CRDF, INTAS, RFFI, and Russian Ministry of Science and Education. She chairs the Biology Panel of the Russian Scientific Foundation and serves on editorial boards for Biochimie, Russian Journal of Molecular Biology, and Acta Naturae. Teaching: As a supervisor of 21 Ph.D. students and numerous diploma projects, she teaches advanced courses at MSU while maintaining an active research program.

• RNA Biology
• Myeloid Malignancies
• Hematology
• +4 more

Dr. Giulia Biancon is an Assistant Professor Adjunct in the Department of Medical Oncology and Hematology at Yale School of Medicine. She holds a PhD from the University of Milan (2019) and is a member of the Halene Lab, focusing on RNA biology and hematologic malignancies. Her research combines high-throughput methodologies to study RNA mechanisms in diseases like myeloid leukemias and splicing factor mutations. Education: PhD in Molecular Biology from the University of Milan (2019). Research Interests: RNA splicing, stress granules in cancer, epitranscriptomics, clonal hematopoiesis, and the interplay between genetic mutations and cellular pathways in blood cancers. Awards: 2024 Eclipse Award, 2022 ASH Abstract Achievement Award, and 2022 RNA Society Best Poster Award. Her work has been published in journals like Cell Reports , Blood , and Molecular Cell . Labs/Teams: Principal member of the Halene Lab and coordinator at the Yale Center for RNA Science and Medicine. Collaborates with institutions like the SeroNet network for immunology studies.

Alexandre Bouchard-CôtéView profile

Professor

• Computational Statistics
• Bayesian Inference
• Monte Carlo Methods
• +4 more

Alexandre Bouchard-Côté is a Professor of Statistics at the University of British Columbia (UBC), affiliated with the Department of Statistics within the Faculty of Science. His research focuses on computational statistics, Bayesian methods, and Monte Carlo techniques, with applications in evolutionary biology, cancer genomics, and computational linguistics. Education : PhD in Computer Science (with Designated Emphasis in Statistics) from UC Berkeley (2010), BSc in Mathematics and Computer Science from McGill University (2005). Affiliations : Director of the Blang probabilistic programming project and leader of the Bouncy Particle Sampler research group. Research Interests : Bouchard-Côté develops scalable Bayesian computational methods, including non-reversible Monte Carlo algorithms like the Bouncy Particle Sampler, and applies these to problems in cancer phylogenetics, evolutionary dynamics, and historical linguistics. His work emphasizes bridging theoretical foundations with practical tools for data science. Publications Trends : Recent work spans distributed sampling frameworks (e.g., Pigeons.jl), variational phylogenetic inference, and cancer clonal evolution modeling. His articles often address algorithmic scalability and interdisciplinary applications in biology and astronomy. Awards : CRM-SSC Prize in Statistics (2024) PIMS-UBC Mathematical Sciences Young Faculty Award (2018) Tweedie New Researcher Award (2016) Advising & Grants : Supervises graduate students (e.g., Son Luu, Nikola Surjanovic) and leads funded projects on distributed MCMC and cancer genomics. Collaborates with institutions like the Simons Foundation and the Canadian Statistical Sciences Institute (CANSSI). Labs/Teams : Core member of the UBC Statistical Machine Learning group, contributing to open-source tools like Blang and the Bouncy Particle Sampler implementation.