Hugues Aschard is a Principal Investigator and Structure Manager at the Pasteur Institute in Paris, where he leads research in statistical genetics, microbiome analysis, and computational genomics. He is the principal investigator of the MicMat project, the EpiGenCOV Consortium, and several bioinformatics software initiatives including JASS, RAISS, and MGMM. Research Interests: Statistical and computational methods in genetics Genome-wide association studies (GWAS) Gene-environment interactions Microbiome and host genetics in inflammatory bowel disease Genetic epidemiology of infectious diseases like COVID-19 Development of open-source tools for multi-trait and summary-statistic analysis Recent Research Trends: His recent publications and projects emphasize integrative genetic modeling, multi-trait analysis across diverse populations, and the development of novel computational methods to handle missing data and improve SNP discovery. His work bridges statistical innovation with biological and clinical applications in complex diseases. Scientific Contributions: Development of JASS, RAISS, and MGMM software tools Leadership in large-scale consortia like EpiGenCOV Advancing methods for cross-ancestry genetic studies Advising and Collaboration: He supervises multiple PhD students and postdoctoral fellows, including Christophe Boetto, Antoine Auvergne, and Lucas Chataigner. He collaborates with major institutions such as APHP and CNRGH. His team includes research engineers and administrative staff, indicating an active and well-supported research group. Laboratories and Teams: He is a key member of the Biomaterials and Microfluidics team at the Pasteur Institute, where he contributes to interdisciplinary research involving Bayesian decision processes and genetic modeling.
George E. Vates, MD, PhD, is a Professor in the Department of Neurosurgery and the Department of Medicine (Endocrine/Metabolism) at the University of Rochester Medical Center. He serves as neurosurgeon co-director of the University of Rochester Multidisciplinary Neuroendocrinology Clinic and is a key member of the University of Rochester Medical Faculty Group (URMFG), which comprises over 900 providers across 19 departments. Dr. Vates specializes in pituitary tumor surgery, cerebrovascular disorders, and skull base procedures, having performed over 120 transsphenoidal pituitary surgeries. Dr. Vates completed his academic training with exceptional distinction: Duke University: Bachelor's degree, summa cum laude (1988, Phi Beta Kappa) Rockefeller University: PhD in Neuroscience Weill Medical College of Cornell University: MD (1997, Alpha Omega Alpha) University of California, San Francisco: Neurosurgery Residency (1998-2003) Brigham and Women's Hospital, Harvard Medical School: Cerebrovascular/Skull Base Fellowship (2003-2004) His research focuses on pituitary tumor biology, neuroendocrinology, and surgical innovation. He established the Multidisciplinary Neuroendocrinology Clinic as a regional referral center for complex pituitary cases, integrating neurosurgical and endocrinological expertise. Current work emphasizes neuroprotective mechanisms in pituitary adenomas, surgical simulation technology, and optimizing outcomes for elderly glioma patients. Analysis of his 15 most recent publications reveals evolving research trajectories: contemporary studies (2019-2022) concentrate on pituitary tumor management, surgical simulation, and neurosurgical education, while earlier work (2002-2009) explored cerebrovascular anomalies, neural pathway mapping, and vascular malformations. Persistent themes include surgical technique refinement, tumor biology, and clinician training. Dr. Vates' scientific contributions have been recognized through: Phi Beta Kappa (1988) and Alpha Omega Alpha (1991) academic honors Neurosurgery Research and Education Foundation Fellowship (2006) Anspach Award for Cerebral Ischemia Research (2007) AANS Leadership Scholarship and Cone Pevehouse Award (2009) Ongoing service as St. Michael's Hospital Animal Care Committee reviewer As an educator, he mentors neurosurgery residents through clinical supervision and curriculum development, notably publishing on palliative care communication training. His research initiatives, including the 3D-printed cervical laminectomy simulator, demonstrate commitment to advancing surgical education. Current grants focus on neuroprotective strategies in pituitary tumors and resident training methodologies. Dr. Vates co-directs the Multidisciplinary Neuroendocrinology Clinic with endocrinologist Dr. Calvi, fostering collaboration between neurosurgery, endocrinology, and oncology. His clinical team manages complex pituitary cases across Rochester and Hornell campuses, while his research group develops surgical innovations and investigates tumor microenvironment interactions to improve patient outcomes.
Thomas Boddaert is an Assistant Professor at the Institut de Chimie Moléculaire et des Matériaux d'Orsay (ICMMO), Université Paris-Saclay . His research focuses on organic photochemistry , synthesis of constrained β-amino acids , and conformational studies of peptide-based foldamers . He leads the photochemistry theme and instrumental platform in the CP3A Organic Synthesis group and manages collaborations with industry partners like Diverchim. PhD in Organocatalysis (Aix-Marseille University, 2009) Postdoctoral research: Manchester University (2010), Rouen University (2010-2012) HDR (2021) for PhD supervision qualification His research includes: Photochemical domino reactions for sulfur heterocycles Peptide foldamer design with cyclobutane motifs Asymmetric synthesis using N-heterocyclic carbenes (NHCs) Visible-light photocatalysis Recent publications demonstrate expertise in: Light-initiated cascade synthesis of alkylidenecyclobutanes (2024) Thia-Paternò-Büchi reaction applications (2024, 2022) Conformational analysis of oxetin oligomers (2018) Fluorinated β-peptide folding studies (2015) Awards: Thieme Chemistry Journals Award (2019) Emergence@international scholarship (INC/CNRS, 2020) Teaching and administrative roles: Co-responsible for L3 Organic Photochemistry Head of L2 Organic Chemistry courses Manager of the Villebon – Georges Charpak Institute chemistry program Member of Paris-Saclay University advisory commission (2021–) He supervises 6 Paris-Saclay PhD students , 2 foreign PhD students , and 2 postdoctoral researchers , with notable projects on: Photochemical post-functionalization of thietanes (2024–) Domino reactions for sulfur heterocycles (2023–) Light-controlled kinase inhibitors (2021)
Professor Sara Bernardini is a leading academic in Artificial Intelligence at the University of Oxford's Department of Computer Science, where she holds a joint appointment as a Tutorial Fellow at Mansfield College. Her research specializes in decision-making for autonomous systems, automated planning, and robotics, with applications in extreme environments like space missions, nuclear decommissioning, and offshore energy. She bridges theoretical AI with real-world challenges through projects funded by Innovate UK, EPSRC, NERC, and the Alan Turing Institute. Her research interests span: Autonomous Systems : Developing agents that support humans in complex cognitive tasks. Automated Planning : Algorithms for goal recognition, pathfinding, and multi-agent coordination. Robotics : Solutions for subterranean exploration, offshore wind farms, and UAV operations. AI Safety : Risk-aware autonomous systems and interpretable decision-making. Bernardini's publications emphasize algorithmic robustness in path planning, multi-agent coordination , and real-world AI deployments . Recent work explores goal legibility in uncertain environments, energy-efficient robotics, and AI education tools. Her 65+ papers in top venues (e.g., AIJ, JAIR, ICAPS) show a trend toward safety-critical applications and human-AI collaboration. Awards & Leadership: ICAPS-2020 Best Paper Honorable Mention Executive Council Member, Association for the Advancement of Artificial Intelligence (AAAI) Program Chair, International Conference on Automated Planning and Scheduling (ICAPS 2024) Associate Editor, Artificial Intelligence Journal She leads interdisciplinary teams for projects like autonomous offshore wind farm maintenance and modular robots for extreme environments. As Principal Scientist at the UK National Oceanography Centre, she advanced marine robotics. She mentors PhD candidates and collaborates globally (e.g., NASA Ames, MIT).
Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.
Omar Rifki is an Associate Professor (Maître de Conférences) specializing in combinatorial optimization and artificial intelligence applications. His research bridges theoretical computer science with practical logistics challenges, focusing on routing problems, process mining, and machine learning integration for complex decision systems. His core research interests include phase transitions in NP-hard problems, vehicle routing optimization under time constraints, and healthcare process modeling. Rifki's work demonstrates a consistent pattern of integrating reinforcement learning with traditional optimization techniques to solve large-scale real-world problems in transportation and logistics, with particular emphasis on spatio-temporal data effects and collaborative systems. Analysis of his 15 publications (2019-2025) reveals three dominant research thrusts: (1) Fundamental studies of combinatorial problem hardness using phase transition frameworks, (2) Practical applications of deep reinforcement learning in vehicle routing and taxi assignment, and (3) Healthcare process optimization through advanced process mining techniques. His work consistently addresses scalability challenges in real-world implementations while maintaining theoretical rigor. No scientific awards were documented in the provided materials. His collaborative work with researchers like Christine Solnon and Thierry Garaix indicates active participation in European operations research communities, though specific grant details remain unreported. Rifki's research shows increasing integration of graph theory and machine learning in transportation applications, particularly evident in his Lyon City case studies on autonomous ride-sharing systems.
Dr. Ken Ferens is an Assistant Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba. He serves as the Computer Engineering Champion in the Centre for Engineering Professional Practice and Engineering Education and directs the Applied Cognitive Intelligence (ACI) Research Group. Dr. Ferens is a senior member of the Institute of Electrical & Electronics Engineers (IEEE), Chair of the EduManCom Chapter of the IEEE, Vice-Chair of the Computer and Computational Intelligence Chapter of the IEEE, and Chair of the Industry, Teaching Assistants, and Student Forums for Engineering Curriculum Review and Improvement. Ph.D. (Computer Engineering), University of Manitoba, 1996 M.Sc. (Computer Engineering), University of Manitoba, 1991 B.Sc. (Electrical Engineering), University of Manitoba, 1989 Dr. Ferens has over 33 years of research experience in computational intelligence, focusing on cognitive machine learning, artificial intelligence, cognitive computational intelligence, chaos theory applications, agent-based models, and various optimization algorithms including simulated annealing, genetic algorithms, artificial neural networks, and particle swarm optimization. His research applies these techniques to develop software and hardware intrusion detection systems for cybersecurity applications. He teaches graduate-level courses on Computer Network Security and Applied Computational Intelligence, providing students with theoretical background and hands-on experience in state-of-the-art security methods. Analysis of Dr. Ferens' recent publications reveals a strong focus on applying cognitive and chaotic computational techniques to cybersecurity challenges, particularly malware detection and network intrusion detection. His work increasingly integrates complexity theory, fractal analysis, and hybrid optimization approaches to enhance security systems' effectiveness. There's a clear progression toward more sophisticated machine learning architectures applied to increasingly complex security scenarios, with growing emphasis on real-world IoT and network security applications. Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2022) Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2015) Best Journal Paper Award for 2013 (Journal of ICT Research and Applications) Best Poster Award at 12th International Conference on e-Health Networking, Application & Services (2010) Best Paper Award at IASTED International Conference on Computer, Electronics, Control, and Communication (1991) Dr. Ferens collaborates with national and international industry partners including the Department of Advanced Information Management, Content Technology Canadian Tire Corporation (CTC), and Magellan Aerospace. His research group has received funding supporting the Cyber-security Research Program, developing practical applications of computational intelligence for security systems. He has supervised numerous graduate students in the Electrical and Computer Engineering department, focusing on research at the intersection of machine learning and cybersecurity. Dr. Ferens leads the Applied Cognitive Intelligence (ACI) Research Group within the Department of Electrical and Computer Engineering, which focuses on applying cognitive, chaotic, and computationally intelligent algorithms to build intrusion detection systems. The group collaborates with industry partners to develop practical security solutions while providing students with hands-on research experience in cutting-edge security technologies. Their work spans both theoretical algorithm development and practical hardware implementation for real-world security applications.
Professor Michael W. Shaw is a distinguished academic at the University of Reading's School of Agriculture, Policy and Development, Department of Plant Sciences, with a research career spanning over two decades. His expertise lies at the intersection of plant pathology, disease epidemiology, and sustainable disease management strategies. Shaw's research interests encompass plant-pathogen interactions , particularly focusing on fungal diseases affecting major crops. His work investigates the epidemiology of plant diseases , fungicide resistance mechanisms , biological control strategies , and asymptomatic pathogen infections . He has made significant contributions to understanding pathogen evolution, host specificity, and the environmental factors influencing disease development. His recent publications demonstrate a consistent research trajectory examining the molecular, ecological, and epidemiological aspects of plant diseases. Shaw's work spans multiple pathosystems including Botrytis cinerea (gray mold), Venturia inaequalis (apple scab), begomoviruses affecting okra, and banana Xanthomonas wilt. His research integrates molecular techniques, field studies, and mathematical modeling to address complex plant health challenges. Professor Shaw has contributed significantly to the understanding of fungicide resistance development, particularly in cereal pathogens, and has explored innovative approaches to disease management through biological control agents and integrated strategies. His work on asymptomatic infections has revealed novel insights into host-pathogen relationships that extend beyond traditional disease paradigms. His collaborative research network spans internationally, with co-authors from multiple countries, reflecting the global relevance of his work in plant health and food security. Shaw's research has practical applications for sustainable agriculture and crop protection strategies worldwide.
Nicholas Polson is the Robert Law, Jr. Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His academic career centers on Bayesian statistics with applications in financial econometrics and machine learning. Polson's research interests span Bayesian statistics, financial econometrics, Markov chain Monte Carlo methods, particle learning, and deep learning applications in finance. His work has significantly contributed to understanding stochastic volatility models and developing new algorithms for Bayesian inference. He has pioneered applications of deep learning in asset pricing, portfolio management, and financial prediction, demonstrating how neural networks can detect complex patterns invisible to traditional financial models. His recent publication trends reveal a strong focus on integrating deep learning with financial econometrics, particularly in developing characteristics-sorted factor models, portfolio optimization techniques, and explaining the performance differences between active and passive investment strategies. His work consistently bridges theoretical statistical methods with practical financial applications, with a particular emphasis on nonlinear modeling and high-dimensional data analysis. His article 'Bayesian Analysis of Stochastic Volatility Models' was named one of the most influential articles in the 20th anniversary issue of the Journal of Business and Economic Statistics Polson teaches courses including 'Bayes, AI and Deep Learning' and 'Business Statistics' at Chicago Booth, with scheduled offerings for both 2024-2025 and 2025-2026 academic years. His work has been featured in Chicago Booth Review, where he has contributed insights on statistical analysis in chess, machine learning applications in money management, and the odds of cheating in competitive settings. His research demonstrates the powerful intersection of Bayesian statistics, financial modeling, and modern machine learning techniques.
Professor Riikka Rinnan (University of Copenhagen) is a leading expert in ecosystem-atmosphere interactions, focusing on volatile organic compounds (VOCs) in Arctic environments. Her groundbreaking discovery of VOCs in permafrost has advanced climate prediction models, revealing complex interactions between climate warming, insect herbivory, microbial activity, and vegetation shifts. Current position: Professor, Department of Biology, University of Copenhagen Major research themes: Permafrost VOCs, Arctic climate feedbacks, plant-insect-microbial interactions International collaborations: China, Germany, Russia Her work combines field expeditions in extreme Arctic conditions with laboratory experiments and advanced VOC analysis. Climate warming experiments show VOC emissions could increase 40-fold with combined warming and insect attacks, while Arctic soils may act as unexpected VOC sinks. Key publications appear in Nature Communications , Nature Geoscience , and Global Change Biology . Riikka Rinnan has received prestigious awards including the EliteForsk Award, European Research Council Consolidator Grant, and Sapere Aude Research Leader. She leads international research teams, advises five PhD candidates, and supervises four postdocs (including two Marie Curie fellows). Her Siberian expedition plans demonstrate commitment to real-world scientific challenges.
Associate Professor Jiakun Liu (FAustMS) is affiliated with the School of Mathematics and Statistics, University of Sydney . He holds a BSc from Zhejiang University (2006) and a PhD from the Australian National University (2010). Following a Simons Postdoctoral Fellowship at Princeton (2010-2013), he served as Lecturer, Senior Lecturer, and Associate Professor at the University of Wollongong (2013-2024), securing an ARC DECRA in 2014 and an ARC Future Fellowship in 2024. Specializes in nonlinear elliptic/parabolic PDEs with applications in geometry and optimal transportation Research focuses on Monge-Ampère/Hessian equations , regularity theory, and geometric flows Contributions to convex geometry , minimal surfaces, and stochastic PDEs . His 2024-2023 publications in Communications on Pure and Applied Mathematics , Advanced Nonlinear Studies , and Archive for Rational Mechanics demonstrate expertise in free boundary regularity , noncompact Minkowski problems , and global geometric analysis . Recognized with ARC Future Fellowship and conferences organized across Australia-China collaborations.
Prof. Dr. Frank Meisel holds the Chair for Supply Chain Management at the Christian-Albrechts-University of Kiel, within the Faculty of Law, Economics and Business. His research focuses on mathematical modeling and quantitative solution methods for the design and operation of production, distribution, and service networks. 1998-2003: Studied Traffic Engineering at the Technical University of Dresden 2008: Received Dr. rer. pol. with thesis "Seaside Operations Planning in Container Terminals" 2014: Completed Habilitation in Business Economics with thesis "Papers on the Design and Operations of Production-, Distribution- and Service-Networks" Since 2013: Professor of Supply Chain Management at Kiel University Prof. Meisel's research spans multiple areas of logistics and operations research. His primary interests include maritime logistics, particularly container terminal operations; vehicle routing problems with synchronization requirements; and integrated planning of production-distribution networks. He develops mathematical models and optimization algorithms to address complex logistical challenges in various industry contexts, from seaport operations to healthcare logistics and urban waste management. His work bridges theoretical operations research with practical logistics applications across diverse sectors. His publication record demonstrates a progression from specialized maritime logistics problems to broader supply chain applications. Recent work shows increasing focus on sustainability considerations and the integration of multiple operational decisions across different parts of supply networks. His research has significant practical implications for container terminal operations, intermodal transportation, and service logistics. Prof. Meisel actively contributes to the academic community through conference presentations at major events including EURO, IFORS, and specialized workshops on maritime logistics. His work appears in top-tier journals such as Transportation Science, European Journal of Operational Research, and Computers & Operations Research. He teaches courses including Supply Chain Management, Production and Logistics, and Operations Management at both undergraduate and graduate levels. His educational contributions include developing curriculum for English-language business programs and supervising student research projects in logistics optimization.
Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections
Lauri Heikonen is a University Lecturer at the Department of Educational Sciences, University of Helsinki, where he is affiliated with the Research and Training Group for Educational Leadership KAJO and the University of Helsinki Centre for Educational Evaluation HEA. He serves as a supervisor in the Doctoral Program in School, Education, Society and Culture and maintains an active research profile with 39 publications to date. Dr. Heikonen's research focuses on educational sciences and educational psychology, with particular emphasis on teacher education, school leadership, and educational evaluation. His work examines factors influencing teacher motivation, professional development, and the attractiveness of teaching as a profession. He has conducted significant research on teacher efficacy, school leadership practices, and educational reform implementation at various levels, often employing both qualitative and quantitative methodologies to address complex educational issues in the Finnish context and beyond. His recent publications demonstrate a strong focus on contemporary educational challenges, including the impact of the COVID-19 pandemic on teaching communities, supervisory practices in teacher education, and collaborative approaches to school development. His research consistently addresses practical educational issues while contributing to theoretical understanding in the field. Dr. Heikonen is actively involved in multiple significant research projects, including 'EDUCA: Koulutus tulevaisuutta varten' (Education for the Future, 2024-2028), 'Cornér Solveig: SFV 23672 SkolForsk' (2024-2026), 'Ahtiainen: OPH VEPO voimaa johtamiseen' (2023-2025), 'Elevating Teacher Training Programs in the UAE' (2023-2024), and 'Erasmus+ Cooperation partnerships in school education: Co-creating inclusive school communities' (2021-2024). These projects reflect his commitment to advancing educational practices through research and international collaboration. As a supervisor in the doctoral program and through his active participation in conferences and peer review activities, Dr. Heikonen contributes significantly to the development of future educational researchers and practitioners, sharing his expertise in educational leadership and evaluation.
Benjamin Shore, MD, MPH, FRCSC, is Associate Professor of Orthopedic Surgery at Harvard Medical School and a practicing pediatric orthopedic surgeon at Boston Children’s Hospital. He serves as Co-Director of the Cerebral Palsy and Spasticity Center and Director of the Pediatric Orthopaedic Surgery Fellowship. Education and Training Undergraduate: Biology, University of Victoria, 1999 MPH: Harvard School of Public Health, 2013 MD: University of Western Ontario, 2003 Residency: Orthopedic Surgery, University of Western Ontario, 2008 Fellowship 1: Pediatric Orthopedics, Royal Children's Hospital, Melbourne, 2009 Fellowship 2: Pediatric Orthopedics, Boston Children’s Hospital, 2010 Research Focus Dr. Shore’s research centers on improving outcomes for children with cerebral palsy and other complex musculoskeletal conditions. His work spans hip surveillance and reconstruction, gait abnormalities, trauma care, and the implementation of evidence-based surgical pathways. He has pioneered investigations into anesthesia protocols, infection prevention, and patient-reported outcome measures for pediatric orthopedic populations. Scientific Awards St. Giles Young Investigator Award (POSNA) Clinician Scientist Development Program Award (CSDP) Charles H. Hood Foundation Child Health Research Award Leadership & Multi-Disciplinary Teams At Boston Children’s Hospital, Dr. Shore leads a high-performance team within the Cerebral Palsy and Spasticity Center that integrates orthopedic surgery, neurology, physical therapy, and social work to deliver patient- and family-centered care. He mentors fellows and residents and actively contributes to national consensus projects using Delphi methodology to standardize surgical indications in cerebral palsy.
