Garrett M. Morris is an Associate Professor in Systems Approaches to Biomedicine at the University of Oxford, affiliated with the Department of Statistics and Green Templeton College. He holds roles as Deputy Director of Graduate Studies, Co-Director of the SABS R³ Centre for Doctoral Training, and Research Fellow at Green Templeton College. His research focuses on computational chemistry, drug discovery, and AI integration in biomedicine. He earned his DPhil from Oxford under Prof. W. Graham Richards, with subsequent work at The Scripps Research Institute and Oxford spinouts like InhibOx and Crysalin. Research interests include protein-ligand docking, virtual screening, and machine learning applications in cheminformatics. Notable contributions include the AutoDock software and the FightAIDS@Home project. He co-organizes conferences like the Royal Society of Chemistry’s 'AI in Chemistry' and founded Comp Chem Kitchen. His lab, Oxford Protein Informatics Group (OPIG), develops novel methods for drug discovery and evaluates AI-based docking methods' validity (e.g., PoseBusters). Recent work critiques AI docking methods' physical plausibility and generalizability. He advises numerous graduate students in statistics and drug discovery, with alumni in academia, pharma, and venture capital. Publications span molecular generation, scoring functions, and computational tools for drug design. Collaborations emphasize reproducibility, responsible research, and cloud computing in biomedicine.
Nuno Miguel Fonseca Ferreira is a Full Professor at the Instituto Superior de Engenharia de Coimbra (ISEC), part of the Polytechnic of Coimbra, where he currently serves as President of the Scientific Council. His academic career spans over 25 years at ISEC, progressing from Assistant to Professor Coordenador Principal. He has held significant leadership positions including Vice-President of ISEC (2001-2005), Pro-President of the Polytechnic of Coimbra (2009-2010), President of ISEC (2010-2013), and Vice-President of the Polytechnic of Coimbra (2013-2017), where he was responsible for internationalization initiatives. His educational background includes a degree in Electrical Engineering from the University of Porto (1996), a Doctorate in Electrical Engineering from the University of Trás-os-Montes and Alto Douro (2006), and a Habilitation Title (Aggregation) from the same institution (2020). His research focuses on Robotic Systems, with specialization in cooperative robotic systems as evidenced by his Habilitation work. Professor Ferreira's research spans multiple domains of robotics and intelligent systems, with particular emphasis on multi-robot coordination, environmental applications, and medical robotics. His work bridges theoretical control systems with practical applications across diverse fields including forestry, healthcare, manufacturing, and education. He has developed innovative approaches to robotic manipulation, sensor integration, and human-robot interaction, often incorporating advanced techniques from artificial intelligence and machine learning. His recent publications demonstrate a strong trend toward practical applications of robotics in real-world environments, particularly in forestry maintenance, industrial automation, and medical applications. The research shows progression from theoretical control systems to applied robotics in challenging environments, with increasing integration of computer vision, deep learning, and collaborative systems. His work spans both fundamental robotics research and immediate industrial applications, reflecting a balance between academic inquiry and practical implementation. Professor Ferreira has supervised two doctoral theses and participated in numerous research projects with substantial funding. His leadership extends to coordinating 15 of the 33 national and international R&D projects he has participated in, demonstrating significant grant acquisition and management capabilities. His international collaborations through Erasmus+ and other European programs highlight his role in fostering global research partnerships. He is an integrated member of GECAD (Research Group in Engineering and Intelligent Computing for Innovation and Advanced Development), a Portuguese R&D unit classified as Excellent by the Portuguese Science and Technology Foundation. Additionally, he is a member of LASI (Associated Laboratory for Intelligent Systems), the Portuguese laboratory associated with Artificial Intelligence, connecting him to a broader national research ecosystem.
William F. Speier is an Associate Professor in the Department of Radiological Sciences at the University of California, Los Angeles (UCLA) School of Medicine . His work spans Medical Informatics , Biomedical Engineering , and Neurology , focusing on applying Artificial Intelligence and Deep Learning to medical imaging and patient monitoring systems. Speier's research emphasizes improving diagnostics for Thyroid Cancer via multimodal ultrasound and molecular testing, advancing Brain-Computer Interfaces (BCIs) for ALS patients, and optimizing Heart Failure remote monitoring through biometric data analysis. He leads the NIH-funded project Predicting Clinically Significant Thyroid Cancer using Ultrasound (R21EB030691), integrating AI into clinical workflows. His recent publications highlight trends in High-Frequency Oscillations for epilepsy, Gleason Grading in prostate cancer, and Language Models for BCI communication. Collaborations with co-authors like Corey Arnold and Hiroki Nariai underscore his interdisciplinary approach. Speier's work also addresses Diagnostic Imaging , Neural Signal Processing , and Health Technology accessibility. Grants and clinical trial integrations further demonstrate his commitment to translating AI into practical healthcare solutions. His methodologies include 3D ConvNets , Federated Learning , and Active Learning frameworks for histopathology and radiology.
Yulong Wei is a Researcher in the Department of Microbial Pathogenesis at Yale School of Medicine. His work focuses on understanding viral persistence mechanisms, particularly in HIV-1 and SARS-CoV-2, using cutting-edge genomic and immunological approaches. He explores how host cellular environments influence viral integration, reservoir formation, and immune evasion. Research interests include: HIV reservoir dynamics and latency mechanisms Host-pathogen interactions in viral persistence Single-cell multiomics analysis of viral infections Antiviral drug discovery and repurposing Ribosomal adaptation and translation mechanisms in bacteria Recent work highlights his contributions to understanding how interferon signaling and chromatin structure affect HIV integration sites, as well as computational studies of griseofulvin's potential in combating SARS-CoV-2. He has also investigated evolutionary genomic signatures in microbes related to translation efficiency and environmental adaptation. His lab is part of the Yale School of Medicine's broader efforts in microbial pathogenesis and infectious disease research, with a focus on translational applications for persistent viral infections.
Carina Hanashima is a Professor at the Faculty of Education and Integrated Arts and Sciences , Waseda University, Japan. Her research focuses on neuroscience , developmental biology , and molecular mechanisms underlying cortical development . She has held academic positions at Kobe University (2014.04-2018.03), RIKEN (2008.10-2017.03), Osaka University (2012.04-2015.03), and Nara Women's University (2007.09-2014.11). Research Interests Neuronal specification and cortical circuit formation Role of transcription factors (e.g., Foxg1, Robo1) in brain development Gene regulatory networks in neurogenesis Evolutionary origins of the neocortex Recent Trends in Publications : Her work explores transcriptional repression , axon guidance signaling , and developmental clock mechanisms in mammalian and non-mammalian models (chicks, mice). Key themes include neurodevelopmental disorders (e.g., autism, schizophrenia), angiogenesis , and cell migration . Scientific Awards : Poster Award, Asia-Pacific Developmental Biology Conference APDBC (2012.10) Grants and Projects : Japan Society for the Promotion of Science Grants-in-Aid (2016.06-2021.03, 2021.04-2022.03) RIKEN Joint Retreat Organizer (2011-2017) Labs and Collaborations : She leads the Hanashima Lab at Waseda University, focusing on spatiotemporal control in neuronal identity and neurovascular coupling . Her lab employs genetic lineage tracing , in situ hybridization , and in utero electroporation techniques.
Dr. Sumanta Das is an Associate Professor and Graduate Director in the Department of Civil and Environmental Engineering at the University of Rhode Island. His research focuses on sustainable infrastructure materials, with particular expertise in cementitious materials, composite structures, and advanced computational modeling techniques. He directs a vibrant research group that bridges experimental mechanics with computational modeling and machine learning approaches to address challenges in infrastructure durability and performance. Dr. Das received his educational training from prestigious institutions: Ph.D. in Materials and Structures from Arizona State University (2015) M.Tech. in Structural Engineering from Indian Institute of Technology, Kanpur (2012) B.E. in Civil Engineering from Jadavpur University (2010) His research interests center around developing sustainable and durable infrastructure materials through innovative design approaches. Dr. Das investigates microstructure-property relationships in cementitious systems, with special focus on materials containing microencapsulated phase change materials for freeze-thaw durability, fiber-reinforced composites, and smart cementitious materials with self-sensing capabilities. His work integrates advanced experimental techniques like nanoindentation with computational modeling approaches including finite element analysis, molecular dynamics simulations, and machine learning algorithms to predict material behavior and optimize performance. Dr. Das's recent publications demonstrate a clear trajectory toward integrating machine learning with traditional materials science approaches. His research group has made significant contributions to understanding the behavior of cementitious composites under extreme conditions, developing multifunctional composites with embedded sensing capabilities, and creating computational frameworks that bridge multiple scales from molecular to structural levels. The work shows increasing sophistication in combining experimental validation with predictive modeling. Dr. Das has successfully secured numerous research grants as PI or Co-PI from diverse funding sources including the Office of Naval Research, Department of Defense, US Department of Transportation, and industry partners like Goetz Composites. His research portfolio spans infrastructure durability, composite materials for marine applications, and smart sensing technologies for structural health monitoring. As an educator and mentor, Dr. Das has supervised multiple doctoral and master's students who have completed theses on topics including: Multiscale simulation and machine learning-assisted performance prediction for cementitious composites Performance-based multiscale tuning of inclusion-modified and 3D printed composites Enhancing freeze-thaw durability of cementitious composites through innovative materials design Underwater explosion response of composite structures Implosion pulse mitigation using additively manufactured filler profiles
Dr. Alanna (Leni) Green is a Senior Research Fellow at the School of Medicine and Population Health, University of Sheffield. She leads the Cancer and Bone (CAB) Lab, focusing on eradicating chemotherapy-resistant dormant cancer cells in bone. Her academic journey includes a BBiomedSci at Monash University, a PhD at the University of Melbourne, and postdoctoral roles in the Sheffield Myeloma Research Team and Helleday’s lab. Education: BBiomedSci (Hons), Monash University PhD, University of Melbourne Her research explores bone-immune-cancer interactions, particularly how bone microenvironment cells protect tumors from therapy. Key areas include retinoic acid receptor signaling, vitamin A regulation of hematopoiesis, and novel drug development for myeloma and bone-metastatic cancers. Recent publications highlight her work in cancer metabolism (MTHFD2 inhibition), bone repair mechanisms, and microenvironmental regulation of lymphopoiesis. She has received over 20 awards, including Young Investigator Prizes from ECTS and ASBMR. Scientific Awards: Wellcome Trust Career Development Award (2024) Yorkshire Cancer Research Pioneer Advanced Fellowship (2024) Blood Cancer UK Project Grant (2023) Faculty MDH Early Career Researcher Prize (2020) Dr. Green supervises the Cancer and Bone Lab, which includes postdoctoral researchers and PhD students. She lectures on translational oncology and molecular medicine courses and actively contributes to professional societies like the Bone Research Society and ECTS.
Professor Ziad Mallat is a distinguished Professor of Cardiovascular Medicine at the University of Cambridge, where he serves as the BHF Professor of Cardiovascular Medicine since 2010. He is affiliated with the Victor Phillip Dahdaleh Heart & Lung Research Institute and is a Principal Investigator in the Cardiovascular and Respiratory Medicine section of the Department of Medicine. Elected as a Fellow of the Academy of Medical Sciences (FMedSci) in 2020, Professor Mallat has established himself as a leading figure in cardiovascular immunology research. Professor Mallat received his MD and degree in Cardiovascular Disease from University of Paris VI, and his PhD from University of Paris VII. He was appointed Director of Research at Inserm, France, in 2007. His academic journey has positioned him at the forefront of cardiovascular research, with particular expertise in immune mechanisms of cardiovascular disease. Professor Mallat's research focuses on the immune mechanisms leading to cardiovascular inflammation in atherosclerosis, post-ischaemic injury (such as myocardial infarction), and aortic aneurysm and dissection. His laboratory develops novel immuno-modulatory and vaccination-based strategies to promote protective immune responses, aiming to radically change the management and treatment of these common and serious cardiovascular diseases. His approach combines basic science research, pre-clinical experimentation in animals, and translation clinical investigation in patients. Analysis of Professor Mallat's recent publications reveals a strong focus on the intersection of immunology and cardiovascular disease, particularly investigating regulatory T cells, B cell responses in atherosclerosis, and immune-modulatory therapies. His work spans from fundamental mechanisms to clinical translation, with several studies examining therapeutic approaches like low-dose interleukin-2 for cardiovascular inflammation. Fellow of the Academy of Medical Sciences (FMedSci) Co-Editor of Atherosclerosis journal Editorial Board member of Circulation Research and JCI Insight Professor Mallat has published over 250 papers in peer-reviewed journals, with landmark contributions including identifying prominent roles for specific pathogenic and regulatory immune pathways in atherosclerosis and post-ischaemic remodeling. His basic research activities are complemented by proof-of-concept clinical trials using immune-modulatory therapies in patients with coronary artery disease. He maintains active collaborations with the British Heart Foundation and is involved in the Cambridge BHF Centre of Research Excellence.
Niklas Mattsson-Carlgren serves as an Associate Professor and Senior Lecturer at Lund University's Faculty of Medicine, Department of Clinical Sciences. He holds multiple significant roles including Deputy Research Team Manager and Principal Investigator for several major research projects. His affiliations extend to the Wallenberg Centre for Molecular Medicine (WCMM), LU Profile Area: Proactive Ageing, and MultiPark: Multidisciplinary Research Focused on Parkinson's Disease. Dr. Mattsson-Carlgren's research primarily focuses on Alzheimer's disease and other neurodegenerative conditions, with additional work on acute brain injuries such as those following cardiac arrest. His expertise spans neurochemistry, including the regulation of pain and sleep. He employs biochemical measurements, neuroimaging, and cognitive testing to study disease processes in vivo across the spectrum from preclinical disease to advanced dementia. His work aims to improve diagnostic and prognostic methods in clinical practice, enhance clinical trial design for novel therapies, and deepen understanding of disease mechanisms. His recent publications demonstrate a strong emphasis on plasma biomarkers for Alzheimer's disease detection and monitoring, with particular focus on tau and amyloid pathology. The research shows increasing integration of machine learning approaches with traditional biomarker analysis, reflecting a trend toward more sophisticated diagnostic tools that combine multiple data sources for improved accuracy in predicting disease progression. As Principal Investigator for multiple significant projects including 'Longitudinal plasma biomarkers, cognitive data and amyloid PET to improve early prevention of Alzheimer's disease' and 'Validation of an MTBR tau immunoassay for CSF and plasma,' he leads substantial research efforts funded by organizations including Familjen Rönströms stiftelse, Eli Lilly and Company, and the Knut and Alice Wallenberg Foundation. He also serves as supervisor for PhD students, notably for 'Studies of induced neuronal cells in Alzheimer's disease.' Dr. Mattsson-Carlgren is actively involved in the neuroscience community, serving on the program committee for Neuroscience Day 2025. His research contributes to UN Sustainable Development Goals related to health and wellbeing. His work has gained significant attention, with multiple papers being picked up by news outlets and referenced across social media platforms including X (Twitter) and Bluesky.
Jens Carlsson is a Professor at Uppsala University, affiliated with the Department of Cell and Molecular Biology and the Science for Life Laboratory (SciLifeLab) . His research focuses on computational biochemistry , particularly G protein-coupled receptors (GPCRs) , using physics-based modeling to advance structure-based drug design . Academic rank: Full Professor (since 2022) Key methodologies: Molecular dynamics simulations, docking, free energy calculations Research themes: GPCR ligand interactions, virtual chemical space screening, allosteric modulators Recent work (2025) highlights AI-driven discovery of brain disease therapeutics and DNA repair inhibitors , while 2024 projects explore AlphaFold applications in TAAR1 agonist design . His group has received Swedish Research Council grants (3.6M SEK, 6M SEK) and industry collaborations . Scientific awards include the Göran Gustafsson Prize (2016), Excellence Prize in Molecular Design (2022), and Ingvar Carlsson Award (2012). Key students include PhD candidates Mariama Jaiteh and Pierre Matricon , with postdocs like Nicolas Panel and Duy Duc Vo .
Professor Ian Marschner is a leading academic in biostatistics, currently holding the position of Professor of Biostatistics and Co-Director of Biostatistics at the NHMRC Clinical Trials Centre, University of Sydney. He has extensive experience spanning over 30 years, including roles as Professor and Head of the Department of Statistics at Macquarie University, Director of Biometrics at Pfizer, and Associate Professor at Harvard University. His research focuses on biostatistical applications in clinical trials, epidemiology, and public health, with a particular emphasis on adaptive trial designs, meta-analysis, and disease surveillance. Professor Marschner has contributed to major clinical trials in cardiovascular medicine, oncology, HIV/AIDS, neonatal/perinatal care, and COVID-19. He co-authored the book Inference Principles for Biostatisticians and is involved with the Biostatistics Collaboration of Australia (BCA) in developing and teaching the Masters of Biostatistics program. His grants include the NHMRC Centre of Research Excellence (AusTriM) and a National Critical Research Infrastructure Initiative grant totaling over $20 million. Research students under his supervision include Aydin HIBBERT, focusing on generalized joint regression models for longitudinal data. His work addresses methodological challenges such as bias in early-stopped trials, surrogate endpoints, and statistical frameworks for adaptive experiments. Recent contributions include risk modeling for diabetes, cardiovascular mortality prediction, and biomarker analysis in cancer therapies.
Prof. Nan Yang is a Professor at the Australian National University's ANU College of Engineering, Computing and Cybernetics, leading the Information and Signal Processing Cluster and the Emerging Communications Laboratory. He holds a PhD in Electronic Engineering from Beijing Institute of Technology (2011) and has held postdoctoral roles at CSIRO and UNSW before joining ANU in 2014. His research focuses on terahertz communications, ultra-reliable low-latency systems, and cyber-physical security, with notable contributions to molecular communications and massive MIMO systems. Education: B.S. in Electronics, China Agricultural University (2005) M.S. in Electronic Engineering, Beijing Institute of Technology (2007) Ph.D. in Electronic Engineering, Beijing Institute of Technology (2011) Key Roles: Associate Dean for Higher Degree Research (2019–2021) Editorial Board Member of IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, IEEE Communications Letters, and others Organizer of workshops at IEEE ICC, GlobeCOM, and ACM MobiCOM His research interests span terahertz communication systems, cyber-physical security, and intelligent communications. Recent work emphasizes secure beamforming, UAV-assisted networks, and molecular communication protocols. He has authored over 180 publications and secured grants totaling millions in funding for projects like the Ultra-Fast and Secure Terahertz Communications for 6G Wireless Systems (2023–2026). Awards & Recognition: IEEE ComSoc Distinguished Lecturer (2023–2024) Best Paper Awards at IEEE ICC 2024, GlobeCOM 2022, and VTC Spring 2013 Exemplary Editor/Reviewer Awards from IEEE Transactions Grants & Projects: iLAuNCH: SWIFT-iLAuNCH Project A (SC-9) (2024–2026) Ultra-Fast and Secure Terahertz Communications for 6G (2023–2026) Facility for Energy Security and Resilience Research (2022) His lab, the Emerging Communications Laboratory, develops cutting-edge solutions for 6G networks, including hybrid beamforming for terahertz systems and secure short-packet protocols. Collaborations span global institutions, emphasizing interdisciplinary research in communications and signal processing.
Professor Neil Berry is a distinguished academic and researcher in the Department of Chemistry at the University of Liverpool's School of Physical Sciences. He currently serves as Head of Department (2018-2024) and has held various significant administrative roles including Director of Post Graduate Research for the School of Physical Sciences (2015-2018) and Departmental PGR Lead. His academic journey began at Exeter College, University of Oxford where he earned his MChem in Chemistry (1999) followed by a DPhil (2002) under the supervision of Professor Paul Beer. Professor Berry's research expertise spans computational chemistry with a focus on applying AI, machine learning, and molecular modeling to solve complex problems in chemistry. His work primarily centers on four key areas: medicinal chemistry (particularly antimalarial and antiparasitic drug discovery), materials chemistry (including metal-organic frameworks and supramolecular gels), reaction mechanisms, and chemoinformatics. His group adopts a rational approach to research through molecular and material design, integrating computational modeling with experimental validation through close collaborations with the Liverpool School of Tropical Medicine, University of Washington, and industry partners including GSK, Bayer, and Unilever. His publication record demonstrates a strong focus on applying computational methods to drug discovery for neglected tropical diseases and advanced materials science. Recent work shows increasing integration of machine learning techniques across all research areas, with significant contributions to antimalarial drug development, snakebite treatment, and materials science applications. His research consistently bridges computational prediction with experimental validation, demonstrating the practical impact of his work. Treasurer - Royal Society of Chemistry Chemical Information and Computer Applications Group (2021 - present) Invited committee member - Royal Society of Chemistry Chemical Information and Computer Applications Group (2015 - present) Fellow of Higher Education Academy (2012 - present) Member of Royal Society of Chemistry (2005 - present) Referee for journals including Nature Communications, Journal of Medicinal Chemistry, and Journal of Computer Aided Molecular Design As an educator, Professor Berry has supervised numerous PhD students and postdoctoral researchers, with a particular emphasis on integrating computational approaches with experimental chemistry. His teaching innovations include Chemtube3D (web-based interactive 3D simulations of organic reactions), lecture recording systems, and ChemPreLab (a pre-lab interactive tutoring system). His research group operates at the intersection of chemistry, biology, and computer science, securing substantial funding from EPSRC, MRC, Wellcome Trust, and industry partners.
Lars Andreas Akslen is a Professor at the Department of Clinical Medicine, University of Bergen, and serves as the Centre Director of CCBIO (Centre for Cancer Biomarkers). He is based at Haukeland University Hospital and leads a major translational cancer research group focused on biomarker discovery and validation. Position: Professor, Centre Director of CCBIO Institution: University of Bergen Department: Department of Clinical Medicine Location: Haukeland University Hospital, Bergen, Norway Email: lars.akslen@uib.no His research is centered on translational oncology, with a strong emphasis on identifying and validating novel biomarkers for improved biological classification and grading of malignant tumors. His work spans breast cancer , malignant melanoma , prostate cancer , and gynecologic cancers . By integrating human tumor sample analysis with experimental cell and animal models, his team aims to enhance the clinical utility of biomarkers in predicting aggressive tumor behavior and guiding personalized treatment strategies. The recent publications highlight a consistent focus on tumor microenvironment, immune biomarkers, imaging mass cytometry, AI in diagnosis, and age-related phenotypes in cancer. There is a strong trend towards high-dimensional spatial profiling and integration of molecular and clinical data to refine prognostic and predictive models. Lars Andreas Akslen has no listed scientific awards in the provided text. He leads the Tumor Biology Research Group (established in 1995) and the CCBIO center, indicating significant mentorship and leadership in cancer research. While specific students are not listed, his extensive collaboration network suggests active supervision of PhD and postdoctoral researchers. No specific grants are mentioned, but leadership of a national research center implies substantial funding acquisition. He is affiliated with CCBIO and the Tumor Biology Research Group, both based at the Department of Clinical Medicine, University of Bergen, and operating from Haukeland University Hospital. These teams focus on translational cancer biomarker research using advanced molecular and imaging technologies.
Scott T. Doyle is an Associate Professor in the Department of Pathology and Anatomical Sciences at the Jacobs School of Medicine & Biomedical Sciences, University at Buffalo. His research integrates biomedical imaging, artificial intelligence, and computational pathology to develop quantitative tools for clinical diagnostics and anatomical modeling. Education: PhD in Biomedical Engineering, Rutgers, The State University of New Jersey (2011) BS in Biomedical Engineering, Rutgers, The State University of New Jersey (2006) Optical Microscopy & Imaging in the Biomedical Sciences, Marine Biological Laboratory (2014) hES Stem Cell Culture Training, WNYSTEM (2014) R Bioconductor Training, Roswell Park Cancer Institute (2016) Dr. Doyle’s research focuses on developing AI-driven algorithms for biomedical image analysis, particularly in digital pathology and 3D anatomical modeling. His work spans tumor segmentation, risk prediction in oral and thyroid cancers, and integration of virtual and physical anatomy in medical education. He applies machine learning, deep learning, and computational modeling to enhance diagnostic accuracy and patient outcomes. His recent publications reflect a strong trend in applying artificial intelligence to histopathology, with emphasis on active learning, 3D reconstruction, and multi-institutional data fusion. Key areas include oral cavity cancer recurrence prediction, thyroid cancer subtyping, and computational modeling of surgical margins and anatomical structures. Scientific Service and Recognition: Reviewer for NIH SPORE grants Peer reviewer for journals including Medical Image Analysis , BMC Bioinformatics , IEEE Transactions on Biomedical Engineering Program Committee and Session Chair, SPIE Medical Imaging: Digital Pathology (2016–present) Member, Graduate Program Steering Committee, Pathology & Anatomical Sciences Mentor, McNair Scholarship and CSTEP programs for underrepresented students Dr. Doyle has secured significant research funding as Principal Investigator on NIH and CTSI grants, including a $2M+ NIH grant for predicting oral cancer recurrence. He has also contributed to educational innovation through hybrid anatomy curriculum development and AI training for pathologists. He leads the 'Atoms to Anatomy' research initiative and is active in strategic planning at the Jacobs School. Laboratories and Collaborative Teams: Dr. Doyle collaborates with the Center for Computational Research (CCR) and is involved in the Structural Sciences Learning Center (SSLC). He has led projects with teams at Ibris, Inc., Veterans Affairs Hospital, and Mount Sinai School of Medicine.
