جست‌وجوی استاد و پژوهشگر

Pavan Turagaمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Computer Vision
• +۹ مورد دیگر

Pavan Turaga is a Professor and Founding Director of The GAME School at Arizona State University (ASU), with a joint appointment in the School of Electrical, Computer and Energy Engineering (ECEE). They lead transdisciplinary research and education initiatives spanning gaming, esports, AI-enabled media creation, computer vision, and geometric modeling. Ph.D., Electrical Engineering, University of Maryland (2009) B.Tech., Electronics and Communication Engineering, IIT Guwahati (2004) Research focuses on integrating geometry and topology with machine learning , enabling advancements in: Computer vision for human activity recognition Generative AI for immersive media Health analytics and wearable rehabilitation systems AI ethics and pandemic prediction Key publications span CVPR (2023 spotlight paper PolyINR ), DLGC workshop (2023 best paper), and ICML (2019 work on GAN priors). Recent work explores LMMs , 3D human modeling , and AI for pandemic preparedness . Scientific accolades include: ASU Founders' Day Research Excellence (2025) NSF CAREER award (2015) CVPR 2023 Spotlight paper 2024 X-Prize (Rainforest Challenge) Directed research for students like Rajhans Singh and Ankita Shukla, securing grants from NSF , DARPA , and industry partners (Adobe, Google ATAP). Founded the Geometric Media Lab , emphasizing interdisciplinary collaborations with mathematicians, health scientists, and media artists.

Sven Bölteمشاهده پروفایل

استاد

• Autism Spectrum Disorder
• ADHD
• Neurodevelopmental Disorders
• +۶ مورد دیگر

Sven Bölte is a Professor at Karolinska Institutet where he leads the research group focused on Autism, ADHD and other developmental neurological conditions as part of the Center for Neurodevelopmental Disorders (KIND). His work bridges clinical research, education, and practical implementation of evidence-based approaches for neurodevelopmental conditions. Professor Bölte's research spans multiple domains within neurodevelopmental disorders, with particular emphasis on implementing the International Classification of Functioning, Disability and Health (ICF) Core Sets for autism and ADHD using digital solutions. His group has developed and evaluated social skills training programs (KONTAKT, SKOLKONTAKT, iKONTAKT) for autistic children and adolescents, conducted twin research through the Roots of Autism and ADHD Twin Study in Sweden (RATSS), and advanced diagnostic instruments for autism, ADHD, social cognition, and adaptive behavior. His recent publications reveal a strong focus on translating research into practice, with significant work on strengths-based approaches, social inclusion, neurodiversity-affirmative assessment, and the development of practical tools for clinicians and educators. The research demonstrates increasing attention to adult experiences of autism, cross-cultural validation of interventions, and the integration of digital technology in assessment and intervention. Bölte's group also delivers extensive educational components for professionals through KI-Utbildning (Assignment Education), making it one of the largest providers of training on diagnosis and support for individuals with developmental neurological conditions within Karolinska Institutet. His work frequently addresses policy implications, as evidenced by participation in Swedish parliamentary discussions about autism and ADHD.

Ghassan AlRegibمشاهده پروفایل

استاد

• Machine Learning
• Image and Video Processing
• Computer Vision
• +۷ مورد دیگر

Ghassan AlRegib is the John and Marilu McCarty Chair Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. He directs the Omni Lab for Intelligent Visual Engineering and Science (OLIVES), the Center for Energy and Geo Processing (CeGP), and previously led Georgia Tech's MENA initiatives (2015-2018). His research spans machine learning, image processing, and seismic interpretation with real-world applications in autonomous vehicles, medical imaging, and subsurface analysis. His research focuses on trustworthy AI systems through three pillars: enhancing interpretability, improving robustness/generalizability, and tackling domain-specific challenges. Key interests include human-in-the-loop frameworks, uncertainty quantification, explainable AI, and physics-driven learning. The OLIVES lab pioneered modern machine learning applications in seismic interpretation and developed open-source datasets for geological fault analysis. Dr. AlRegib's scientific contributions include over 270 publications, multiple U.S. patents, and leadership roles as Technical Program co-Chair for ICIP 2020/2024. His work demonstrates significant impact through awards like the IEEE Fellow designation (2022) and multiple best paper awards at premier conferences. IEEE Fellow (2022) 2023 EURASIP Best Paper Award 2019 ICIP Best Paper Award 2017 Denning Faculty Award for Global Engagement CSIP Research & Service Awards (2003) He has advised numerous PhD students including Dr. Ashraf Alattar (now Auburn professor) and Dr. Zhiling Long (Kennesaw State faculty). His lab structure emphasizes collaborative teams comprising postdocs, senior/junior PhD students, and undergraduates working on high-impact problems from autonomous systems to medical diagnostics. Current research thrusts include trustworthy neural networks, human-in-the-loop frameworks, and deployment of machine learning in seismic interpretation and ophthalmology.

Eleodor Nichitaمشاهده پروفایل

دانشیار

• Nuclear Reactor Design
• Neutron and Radiation Transport
• Reactor Kinetics and Control
• +۳ مورد دیگر

Dr. Eleodor Nichita is an Associate Professor in the Department of Energy and Nuclear Engineering at the University of Ontario Institute of Technology (UOIT), part of the Faculty of Engineering and Applied Science. He holds a PhD in Nuclear Engineering from Georgia Institute of Technology (USA) and additional degrees from McMaster University and the University of Bucharest. His research focuses on neutron transport, reactor kinetics, advanced nuclear reactor design, and radionuclide production. He teaches a wide range of courses including reactor physics, neutron detectors, and medical imaging applications of radiation. Education: PhD in Nuclear Engineering, Georgia Institute of Technology, United States MS in Health Physics, Georgia Institute of Technology MS in Medical Physics, McMaster University BS in Engineering Physics, University of Bucharest, Romania Research interests emphasize mathematical modeling for nuclear systems, neutronic design of advanced reactors, and production of medical isotopes like Mo-99. His work addresses reactor safety, lattice homogenization techniques, and SCWR (supercritical water-cooled reactor) dynamics. Over 50 peer-reviewed papers and book chapters reflect his contributions to CANDU reactor analysis, PHWR fuel bundle design, and educational innovations in nuclear engineering. Advising and grants: While specific student names are not listed, his extensive teaching portfolio (including graduate-level reactor physics courses) indicates active mentoring. Research grants likely support his work on reactor kinetics and SCWR technology. Lab affiliations: His research is conducted through the Energy Systems and Nuclear Science Research Centre (ERC) at UOIT, focusing on numerical methods and experimental validation for reactor analysis.

Steff Lewisمشاهده پروفایل

استاد

• Medical Statistics
• Clinical Trials
• Epidemiology
• +۳ مورد دیگر

Steff Lewis is a Professor of Medical Statistics at the University of Edinburgh , affiliated with the Usher Institute within the College of Medicine and Veterinary Medicine . She leads the statistics group at the Edinburgh Clinical Trials Unit and holds roles in the Deanery of Molecular, Genetic and Population Health Sciences . Her expertise spans meta-analysis, randomized trial design, and clinical trial governance, with involvement in Cochrane Collaboration and UK Clinical Research Collaboration initiatives. Education: MSc and PhD in Medical Statistics. Research Interests: Focuses on methodological advancements in clinical trial reporting (e.g., CONSORT and SPIRIT guidelines), cardiovascular outcomes (e.g., SCOT-HEART trial), stroke prevention (ASPIRING trial), and ethical data management. She actively contributes to international standards for trial protocols, anonymization practices, and statistical validation. Recent Contributions: Over 200 peer-reviewed articles and 37 ongoing projects, including leadership in trials assessing antiplatelet therapies, Paget’s disease interventions, and pediatric asthma treatments. Collaborates globally on guidelines for randomized trials and data-sharing protocols. Grants & Teams: Principal or co-investigator on projects funded by NIHR, BHF, and ESRC, including trials on iron therapy in critical care (INTACT-2) and cannabinoid treatments for endometriosis pain (ENDO-CAN). Leads multidisciplinary teams integrating statistical rigor with clinical innovation. Labs/Teams: Embedded within the Edinburgh Clinical Trials Unit and the Centre for Population Health Sciences , fostering collaborative research across molecular, genetic, and public health domains.

• African Studies
• Linguistics
• Historical Anthropology
• +۸ مورد دیگر

Katrin Bromber is a German Researcher at the Centre for Modern Oriental Studies in Berlin, where she has led the research group "Progress and its Discontents: Ideas, Practices, Materiality" since 2014. Her career spans senior research roles at ZMO and academic teaching positions at the University of Vienna. Nationality: German. Language skills: Native German, fluent English/Swahili, moderate Amharic, good reading knowledge in French/Russian, basic Tigrinya. Habilitation (2009–): African Studies, University of Vienna PhD (1993): African Linguistics, University of Leipzig MA (1988): Swahili Studies, University of Leipzig Katrin Bromber's research interrogates intersections of body politics , sports history , Swahili linguistics , and Ethiopian modernity . Her work traces how physical culture, media representation, and colonial/imperial narratives shape national identities across Africa and Asia. Current focus: "Progress" as contested concept in Ethiopian and Gulf urbanism. Key article trends reflect her translocal methodology: 2017 studies on Ethiopian stadiums and fitness culture ; 2014-2013 publications analyzing East African military press , sports branding in the Gulf , and Swahili poetry ; 2007-2000 works on colonial linguistic politics , Indian Ocean slavery , and German colonial Swahili promotion . Recurring sub-fields: body as political text, translocal modernity, media historiography. Scientific Awards: Research Grant of the Berlin City Council (1999-2000): Gendered Slavery study Service to the Scientific Community: Chairwoman, Academic Association for Horn of Africa Studies (2012–) Editorial Advisory Board - Stichproben. Vienna Journal of African Studies (2015–) Editorial Advisory Board - Studies of Department of African Languages and Cultures (2015–) Teaching Experience: Textlinguistics, Mediacommunication, African Linguistics, Swahili (elementary/advanced), Swahili Literature, Swahili in Arabic Script at Leipzig, Humboldt-Berlin, Free Berlin, and Vienna universities Anthropology of the Body at Mekelle University Summer School Field Research: Tanzania (1993-2003): Swahili Poetry, Intellectual History Kenya (2005): Indian Ocean WW2 UAE/Bahrain (2009): Sports and Body Cultures Ethiopia (2009-2015): Sports, Body Politics

Chen Sunمشاهده پروفایل

استادیار

• Computer Vision
• Deep Learning
• Machine Learning
• +۸ مورد دیگر

Chen Sun is an Assistant Professor of Computer Science at Brown University and a part-time Staff Research Scientist at Google DeepMind . His research bridges computer vision, machine learning, and artificial intelligence , focusing on multimodal representation learning, visual commonsense, and controllable video generation . He directs the PALM🌴 research lab , which explores scalable models for robotic planning, video understanding, and human activity recognition . Chen Sun earned a Ph.D. in Computer Science from the University of Southern California (2016) , advised by Professor Ram Nevatia , and a Bachelor of Science in Computer Science from Tsinghua University (2011) . His lab's work has been supported by Adobe, Honda, Meta, NASA, and Samsung , and he is affiliated with the NSF AI Research Institute on Interaction for AI Assistants . His research spans multimodal transformers, embodied agents, and physics-informed video generation . Key trends include Learning from unlabeled videos for human activity recognition Developing controllable generation techniques using motion trajectories and physics-based signals Advancing scalable frameworks for video-language tasks Scientific awards include the Brown University Richard B. Salomon Faculty Research Award and Samsung Global Research Outreach Award . He has served as Workshop Chair (CVPR 2025) , Action Editor (TMLR) , and Area Chair for top conferences like ICLR, CVPR, and NeurIPS . Chen Sun mentors a dynamic team including Ph.D. students Apoorv Khandelwal (Presidential Fellow) Calvin Luo (Research Mobility Fellow) Nate Gillman (Math Department) Shijie Wang Tian Yun (co-advised with Ellie Pavlick) Yuan Zang Zilai Zeng Zitian Tang and alumni now pursuing Ph.D. programs at Princeton, Cornell, UBC, and UNC . His teaching portfolio includes graduate-level courses on Deep Learning (CSCI 2470) , Advanced Topics in Deep Learning (CSCI 2952N) , and a short course on Multimodal Transformers at ICASSP 2022 and AAAI 2023 .

Brent Fogelمشاهده پروفایل

استاد

• Neurogenetics
• Hereditary Ataxia
• Spinocerebellar Ataxia
• +۷ مورد دیگر

Dr. Brent Fogel is a Professor in the Departments of Neurology and Human Genetics at the David Geffen School of Medicine, UCLA. He directs the Neurogenetics Clinic and the UCLA Clinical Neurogenomics Research Center , focusing on diagnosing and managing genetic neurological disorders such as cerebellar ataxia , ataxia with oculomotor apraxia , spastic paraplegia , and leukodystrophies . His research integrates genomics , bioinformatics , and neuroimaging to improve precision medicine in prenatal counseling and rare disease diagnosis. Education: MD, PhD from Medical College of Wisconsin (2003) PhD in Genetics (2001) Internship in Internal Medicine (Northwestern University, 2004) Residency in Neurology (UCLA, 2007) Fellowship in Neurogenetics (UCLA, 2009) Board Certified in Neurology (2009) Research Focus: Dr. Fogel’s work spans neurogenetics , spinocerebellar ataxia , leukodystrophy , and genomic technologies . He has pioneered gene discovery in hereditary ataxias, developed transcriptional biomarkers , and contributed to diagnostic guidelines for rare disorders. His studies on lysosomal genes in Parkinson’s disease and exome sequencing disparities address critical gaps in neurogenetic research. Key Collaborations: He leads multicenter studies with the Ataxia Global Initiative , Undiagnosed Diseases Network , and Genomics England Research Consortium . His lab ( FogelLab ) develops tools like multiWGCNA for gene network analysis.

• Big Data
• Business Analytics
• Healthcare Analytics
• +۴ مورد دیگر

Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.

• Smart Sustainable and Resilient Cities
• Energy Efficient Communities & Cities
• Crowdsensing-based Infrastructure Monitoring (CbIM)
• +۴ مورد دیگر

Mustafa Gül is a Professor in the Department of Civil and Environmental Engineering at the University of Alberta’s Faculty of Engineering. He also serves as Director of Internationalization at the Faculty of Engineering’s Deans Office. His research focuses on smart, sustainable, and resilient cities, with an emphasis on infrastructure monitoring and energy-efficient systems. Education: PhD in Civil Engineering (University of Central Florida, 2009), MSc in Electrical Engineering (University of Central Florida, 2011), MSc in Civil Engineering (Boğaziçi University, 2004), BSc in Civil Engineering (Boğaziçi University, 2002). Dr. Gül’s research spans two primary domains: Crowdsensing-based Monitoring of Built and Natural Environments (CoMBiNE) using AI, signal processing, and data analytics for infrastructure health; and Energy-Efficient Smart Cities through solar PV integration, IoT applications, and net-zero energy homes. His work bridges structural engineering, machine learning, and sustainable urban development. Recent publications highlight advancements in smartphone-based damage detection, UAV-assisted disaster assessment, and AI-driven energy systems. His team’s work on crowdsensing bridges, solar PV optimization, and smartphone analytics has been widely recognized in journals like Structural Control and Health Monitoring and Energy and AI . Notably, his 2017 paper earned the Best Paper Award at ISARC. Students supervised include Azim, R. , Keskin, M. , and Do, N. T. , among others. Scientific Awards: Best Paper Award, 34th International Symposium on Automation and Robotics in Construction (ISARC 2017) Dr. Gül’s projects often involve interdisciplinary collaboration, leveraging sensor networks, computer vision, and optimization algorithms to address urban resilience and energy sustainability. His leadership extends to course CIV E 779 and ongoing research initiatives in Alberta, Canada.

• Plasmonics
• Photocatalysis
• Electrocatalysis
• +۳ مورد دیگر

Professor Emiliano Cortés is a faculty member at the Ludwig Maximilian University of Munich (LMU), where he leads research in Plasmonic and Photonic Chemistry at the Nano-Institute Munich. His work bridges the fields of nanotechnology, physical chemistry, and materials science, focusing on light-matter interactions for energy conversion applications. Dr. Cortés' research focuses on plasmonics , photocatalysis , and electrocatalysis at the nanoscale. His group investigates how the dynamics of photons, plasmon-polaritons, carriers, phonons, and molecular states influence chemical reactivity. A key aspect of his work involves developing techniques to study plasmonic systems at the single particle level and designing rational synthesis approaches for plasmonic colloidal photo and electrocatalysts. His research has significant implications for sustainable energy technologies, environmental remediation, and advanced sensing applications. Analysis of Professor Cortés' recent publications reveals a strong focus on energy conversion processes, with particular emphasis on CO2 reduction, ammonia synthesis, and hydrogen production. His work integrates plasmonic effects with catalytic processes to enhance reaction efficiencies, often through innovative interface engineering and nanostructure design. The research spans fundamental studies of charge carrier dynamics to practical applications in energy storage and environmental technologies. Professor Cortés actively mentors doctoral candidates and postdoctoral researchers, currently advertising open positions for projects on Single particle photo and electrocatalysis and Synthesis of hybrid colloids . His research group, the Hybrid Plasmonics Lab (www.hybridplasmonics.org), receives funding from various sources to support their work on plasmon-mediated chemistry for sustainable applications. The Cortés research group operates within the Nano-Institute Munich, utilizing state-of-the-art facilities for nanomaterial synthesis, characterization, and testing. Their work combines experimental approaches with theoretical modeling to understand and harness light-matter interactions at the nanoscale for practical applications in energy conversion and environmental technologies.

Bryan Trippمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Deep Learning
• Robotics
• +۱ مورد دیگر

Bryan Tripp is an Associate Professor at the University of Waterloo, specializing in computational neuroscience, deep learning, robotics, and medical AI. He leads the BRAIN Lab, which focuses on developing neural system models that interact with the physical world through robots. His research integrates neurobiological models with advanced machine learning techniques to study visuomotor processes and robotic applications. Tripp teaches courses such as Computational Neuroscience (SYDE 552), Deep Learning (SYDE 577), and Biomedical Engineering Design Workshops (BME 461/462). His lab has achieved milestones including the OREO robotic head, the first spiking neural network model for complex action planning, and comprehensive datasets for robotic grasping. His recent work emphasizes Medical AI applications, with graduate positions available. The BRAIN Lab is affiliated with the Centre for Theoretical Neuroscience and Waterloo.AI, contributing to interdisciplinary AI research initiatives.

Steven R. Caliariمشاهده پروفایل

دانشیار

• Biomaterials
• Mechanobiology
• Musculoskeletal Tissue Engineering
• +۱ مورد دیگر

Steven R. Caliari is an Associate Professor in the Department of Chemical Engineering with a secondary appointment in Biomedical Engineering at the University of Virginia’s School of Engineering and Applied Science. He serves as the ChE Graduate Program Director and is a SEAS Copenhaver Fellow (2023). His research focuses on designing biomaterials to study cell-microenvironment interactions, addressing challenges in disease and tissue engineering. He holds a B.S. (2007, University of Florida), M.S. (2010), and Ph.D. (2013) in Chemical Engineering from the University of Illinois, followed by an NIH postdoctoral fellowship at the University of Pennsylvania. His research interests include biomaterials, mechanobiology, musculoskeletal tissue engineering, and advanced manufacturing for biological applications. His lab has pioneered viscoelastic hydrogel platforms and conductive collagen scaffolds, supported by NIH, NSF, DoD, and industry grants. Notable awards include the NSF CAREER Award (2021) and NIH MIRA (2020). Grants: NIH (NIGMS), NSF CAREER, V Foundation, UVA-Coulter Partnership Courses: Tissue Engineering (BME/CHE 4417), Transport Processes I (CHE 3321) Labs: Caliari Lab focuses on biomaterial design and mechanobiological studies His work bridges fundamental science and translational applications, emphasizing dynamic material systems for regenerative medicine and disease modeling.

Jana Kainerstorferمشاهده پروفایل

استاد

• Biomedical Optics
• Neurophotonics
• Medical Devices
• +۳ مورد دیگر

Jana Kainerstorfer is a Professor of Biomedical Engineering at Carnegie Mellon University (CMU), with courtesy appointments in the Neuroscience Institute and Electrical & Computer Engineering. She serves as Associate Department Head for Faculty and Graduate Affairs within the College of Engineering. Her research focuses on developing non-invasive optical imaging methods for disease detection and treatment monitoring, particularly in diffuse optical imaging. Key areas include cerebral hemodynamic monitoring in traumatic brain injury and handheld devices for breast cancer imaging. Dr. Kainerstorfer holds senior membership in the Optical Society of America and has received prestigious awards such as the NIH Trailblazer Award and AHA Scientist Development Grant. She leads the Biophotonics Lab, which bridges engineering and clinical applications, emphasizing translational research. Education: PhD from University of Vienna/NIH (2010), Postdoc at Tufts University Research Interests Her work revolves around biomedical optics , neurophotonics , and medical device innovation . Current projects include: Non-invasive cerebral hemodynamic monitoring Transabdominal fetal pulse oximetry Optical imaging in extreme environments (e.g., freediving physiology) Her lab develops tools like wearable NIRS for marine mammals and self-calibrating pulse oximetry algorithms. Research spans clinical translation and physiological mechanism discovery , with emphasis on microvascular imaging. Awards & Recognition NIH Trailblazer Award (2020) AHA Scientist Development Grant SPIE Fellow (2022) George Tallman Ladd Award (CMU) Lab & Collaborations The Biophotonics Lab collaborates with neurosurgery, oncology, and marine biology teams. Projects address clinical needs in neurocritical care and fetal monitoring, leveraging optical technologies for real-time diagnostics. Ongoing work includes: Optical assessment of cerebral metabolic rates Non-invasive intracranial pressure estimation Multi-modal EEG-NIRS fusion for neural source localization

• MRI
• Diffusion MRI
• Perfusion MRI
• +۶ مورد دیگر

Professor Fernando Calamante is a Professor of Biomedical Engineering at The University of Sydney and Director of Sydney Imaging Core Research Facility. He leads the National Imaging Facility node and focuses on advanced MRI methodologies, particularly Diffusion and Perfusion MRI, to study brain connectivity and neurological disorders. His work includes developing the MRtrix software, widely used in diffusion MRI analysis. He holds extensive funding (~$50M) and has been recognized with awards like ISMRM Fellowship and NHMRC grants. His research spans super-resolution imaging, brain connectomics, and clinical applications in stroke and tumors. Education: BSc (Physics, Argentina), PhD (Magnetic Resonance Imaging, University College London). Career highlights include leadership roles at The Florey Institute and ISMRM presidency (2021-2022). Research interests include: Novel MRI methods for brain connectivity and super-resolution imaging Applications of Diffusion and Perfusion MRI in neurology Integration of structural and functional connectomics Key achievements: Over 200 publications, software innovations, and leadership in global MRI societies.