جست‌وجوی استاد و پژوهشگر

Geoffrey Handsfieldمشاهده پروفایل

استادیار

• Biomedical Imaging
• Rehabilitation Engineering
• Musculoskeletal Biomechanics
• +۴ مورد دیگر

Geoffrey Handsfield is an Assistant Professor at the University of North Carolina at Chapel Hill, holding appointments in the Department of Orthopaedics and the Lampe Joint Department of Biomedical Engineering. His work integrates advanced medical imaging, computational modeling, and mechanical experimentation to improve clinical orthopaedic medicine and understand musculoskeletal form and function. Educated at East Carolina University (B.S. Physics, Summa Cum Laude with Mathematics Minor), the University of Virginia (Ph.D., Biomedical Engineering), and as a Whitaker Postdoctoral Scholar at the University of Auckland, his research focuses on musculoskeletal MRI, computational modeling of muscle-tendon interactions, and pediatric cerebral palsy rehabilitation. Education: Ph.D., Biomedical Engineering, University of Virginia, 2014 Postdoctoral Fellowship, Auckland Bioengineering Institute, 2014–2016 (Whitaker Scholar) B.S., Physics (Summa Cum Laude), Mathematics Minor, East Carolina University, 2008 Research Interests: Dr. Handsfield’s lab pioneers techniques like ultra-high contrast MRI and 3D ultrasound to study muscle-fascia interactions, tendon mechanics, and pediatric cerebral palsy. Key areas include: Image-based computational models for personalized musculoskeletal analysis Muscle architecture and regeneration in children and athletes Biomechanical interventions for cerebral palsy rehabilitation Non-invasive muscle profiling for clinical decision-making Awards: Aotearoa Early Career Research Fellow, Robertson Foundation Early Career Research Award, Australia-New Zealand Orthopaedic Research Society Whitaker Postdoctoral Scholar Academic All-American in Swimming & Diving (2007–2008) Advising & Grants: While specific grant details are not listed, his lab’s focus on pediatric cerebral palsy and musculoskeletal modeling suggests involvement in NIH-funded or foundation-sponsored research. No formal advisees are listed in the provided data. Labs & Teams: His interdisciplinary lab collaborates with clinicians and engineers to translate imaging and modeling innovations into clinical practice, focusing on tools like the dSIR MRI sequence and high-dimensional muscle clustering for athlete and pediatric populations.

• Agricultural Ecology
• Sustainable Food Production
• Evidence Synthesis
• +۴ مورد دیگر

Professor Nicola Randall is a Professor of Evidence Synthesis and Agroecology at Harper Adams University, where she leads the Centre for Evidence-Based Agriculture (CEBA) and the Agroecology for Sustainable Agri-food (AFS) research group. She holds a BSc (Hons), PhD, and a CertTHE in higher education. Her research focuses on agricultural ecology, sustainable food systems, and evidence-based decision-making in environmental and agricultural policies. She chairs the EU-NESA Network (CA23107 2024-2028) and serves on advisory boards for organizations such as the Food Standards Agency and Ceres2030. Her work emphasizes systematic reviews, evidence synthesis methodologies, and bridging gaps between research and policy. She has secured over £1 million in research funding, collaborating with bodies like BBSRC, DEFRA, and EU H2020. Education: BSc (Hons), PhD, CertTHE Teaching Roles: Course leader for Agroecology MSc, module leader for Fundamentals of Agroecology and International Agroecology Professional Memberships: British Ecological Society (Agroecology Committee), Society for Conservation Biology Her research spans topics like regenerative agriculture, pollinator ecology, and humane slaughter practices. She advises on international projects, including FAO initiatives and smallholder farming interventions in Africa. Her work bridges academic research with practical applications for sustainable agriculture and environmental governance.

• Ophthalmology
• Diabetic Retinopathy
• Macular Degeneration
• +۵ مورد دیگر

Professor Mark Gillies is a leading academic in the Faculty of Medicine and Health at the University of Sydney , specifically within the Clinical Ophthalmology and Eye Health department. He holds the title of Professor and is affiliated with the Save Sight Institute . His research focuses on medical retina, macular degeneration, and diabetic retinopathy, with pioneering work in intravitreal steroids for diabetic retinopathy and internet-based outcome tracking systems like the Fight Retinal Blindness! Project . Education: Gillies earned his PhD from the Walter and Eliza Hall Institute, making him the first Australian ophthalmologist with this distinction. His expertise spans clinical trials, retinal metabolism, and Müller cell biology. He has been a vocal advocate for treatments like Photodynamic Therapy and public education on retinal diseases. Research Interests: His work addresses central retinal diseases, including diabetic retinopathy, macular degeneration, and stem cell therapies. He emphasizes translational research, bridging clinical practice with innovations like drug delivery systems and outcome registries. Advising & Grants: Supervises students like Grace CHAN (digital transformation in organ culture) and Jialing ZHANG (RNA-based drug delivery). His projects involve large-scale registries tracking real-world outcomes for retinal diseases, ensuring evidence-based practices. Labs & Teams: Leads the Macula Research Group and collaborates with global networks through the Save Sight Institute . His work integrates clinical, genetic, and metabolic data to advance retinal therapies.

• Journalism
• Communication Technology
• Social Media
• +۳ مورد دیگر

Yee Man (Margaret) Ng is an Associate Professor in Journalism and the Institute of Communications Research at the University of Illinois. She combines data science methodologies with communication research to study social media dynamics, digital journalism, and technology adoption patterns. Her research interests include: Computational social science Social media analytics Data visualization techniques Communication technology impacts Journalism innovation Post-adoption technology behavior Ng's methodology integrates big data analysis, machine learning algorithms, and traditional survey/experimental approaches. Current work extends diffusion of innovations theory by examining social media users' discontinuance and readoption behaviors. Academic contributions span both empirical research and educational practice. She has taught courses like: JOUR 460 - Data Storytelling JOUR 410 - Data Storytelling for Journalism JOUR 425 - Multimedia Editing and Design JOUR 199 - Hands-on Media Technology Her publications analyze topics ranging from YouTube's recommendation algorithms to digital sustainability in news media, with particular focus on: Platform migration patterns Algorithmic content moderation Political communication dynamics Media technology adoption Regional web usage differences Incivility measurement techniques

• Sports Medicine
• Cardiovascular Health
• Health Services Research
• +۷ مورد دیگر

Hilde Moseby Berge is an Associate Professor in the Department of General Practice at the University of Oslo. Her research focuses on cardiovascular health in athletes, injury and illness prevention in elite sports, and the psychological and social impacts of cardiac arrest survival among young exercisers. She has collaborated extensively with institutions like the Norwegian Olympic and Paralympic committees, contributing to longitudinal health monitoring programs for athletes. Her work includes evaluating automated external defibrillator (AED) availability in sports clubs and analyzing post-surgical outcomes for musculoskeletal injuries. Berge is also affiliated with the Clinical General Practice Research (Allmix) and General Practice Health Services Research (ALHF) groups, emphasizing her commitment to practical healthcare solutions. Key research themes include: 1) Cardiac events in sports contexts, 2) Health disparities affecting Paralympic athletes, and 3) Long-term health surveillance for Olympic/Paralympic participants. Her studies often use systematic reviews and multi-year cohort analyses, with findings published in journals like British Journal of Sports Medicine and Resuscitation . Berge’s contributions to healthcare systems include designing prevention protocols for sudden cardiac arrest and investigating bone density issues in elite Para athletes. She has co-authored over 15 peer-reviewed articles since 2014, addressing topics such as ECG interpretation in athletes, post-cardiac arrest quality of life, and the epidemiology of sports-related injuries. Her work bridges clinical research and real-world healthcare applications, particularly in sports medicine and emergency preparedness.

Maia Jacobsمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Health Technology Design
• Behavioral Science
• +۳ مورد دیگر

Maia Jacobs is an Assistant Professor of Computer Science and Preventive Medicine at Northwestern University. Her research focuses on human-centered computing to design health technologies that adapt to longitudinal health needs. She holds a Ph.D. in Human-Centered Computing from Georgia Institute of Technology and a B.S. in Industrial and Systems Engineering from the University of Wisconsin-Madison. Her work emphasizes user-centered design principles to create equitable and adaptive health interventions. Key research areas include wearable health tools, voice assistants for mental health, telehealth cancer care, and AI integration in healthcare workflows. She collaborates with low-income communities and informal caregivers to ensure technologies address real-world healthcare challenges. Recent publications explore AI-physician collaboration in oncology, burnout support for frontline workers, and ethical design of voice-assisted mental health services. Her projects often involve co-design with marginalized groups to promote health equity. Jacobs’ interdisciplinary approach bridges computer science, behavioral science, and clinical practice to advance personalized healthcare solutions.

Avniel Singh Ghumanمشاهده پروفایل

دانشیار

• visual cognition
• neural dynamics
• face recognition
• +۶ مورد دیگر

Dr. Avniel Singh Ghuman is an Associate Professor in the Department of Neurological Surgery at the University of Pittsburgh School of Medicine. He serves as Director of the Cognitive Neurodynamics Lab and plays a key role in advancing MEG (Magnetoencephalography) Research at the university. His work bridges clinical neurosurgery with fundamental neuroscience research to understand visual perception mechanisms. Dr. Ghuman's educational background includes: BA in Math and Physics from The Johns Hopkins University (1998) PhD in Biophysics from Harvard University (2007) Postdoctoral training at the National Institute of Mental Health Dr. Ghuman's research focuses on how the brain transforms visual input into meaningful perception of objects, faces, words, and social images in real-world contexts. His laboratory employs both invasive (intracranial EEG) and non-invasive (MEG) techniques to examine the spatiotemporal dynamics of neural activity during visual processing. The lab integrates multivariate machine learning methods, network analysis, and direct neural stimulation to investigate information processing at both local brain regions and distributed network levels. Recent work has pioneered methods for studying brain activity during authentic social interactions and natural behavior. His publication record demonstrates significant contributions to understanding real-world face perception, neural dynamics during natural behavior, and the application of advanced analytical techniques to brain imaging data. His research has revealed how brain network dynamics form a 'punctuated equilibrium' of stable states with transitory bursts between them, coinciding with behavioral shifts in everyday activities. Dr. Ghuman has received notable recognition for his work: Young Investigator Award from NARSAD (2012) Award for Innovative New Scientists from the National Institute of Mental Health (2015) His research has been featured in prominent media outlets including MIT Technology Review, The Wall Street Journal, and Carnegie Mellon University publications. As Director of the Cognitive Neurodynamics Lab, Dr. Ghuman leads a research program that has advanced our understanding of how the brain processes visual information in real-world environments, with implications for both fundamental neuroscience and clinical applications.

Sharon P. Kaneمشاهده پروفایل

استادیار

• Economic Impact Analysis
• Community Development
• Applied Economics
• +۵ مورد دیگر

Sharon P. Kane is an Assistant Professor in the Department of Financial Planning, Housing and Consumer Economics at the University of Georgia . As an applied economist, her work focuses on economic impact analysis , community development , and econometric analysis . She teaches courses such as FHCE 2100E Introduction to Consumer Economics and FHCE 3100 Consumer Decision Making , emphasizing the family as a producing and consuming unit and exploring systematic departures from rational decision-making. Education: PhD in Agricultural and Applied Economics from University of Georgia MS in Economics from University of Kentucky BS in Economics from University of Tennessee Chattanooga Research Interests span applied economics, economic impact assessment, and community development. Her work bridges agribusiness , consumer economics , and policy analysis , with a focus on econometric modeling and statistical tools. Recent articles analyze Georgia's agricultural industry, pandemic effects on farming, and transportation economics. Scientific Awards: None listed. Advising: No student names provided. She has over a decade of experience in the mortgage banking industry and worked as an economist for a Fortune 500 corporation.

Dina Katabiمشاهده پروفایل

استاد

• Digital Health
• Wireless Sensors
• Machine Learning
• +۳ مورد دیگر

Dina Katabi is the Thuan and Nicole Pham Professor of Electrical Engineering and Computer Science at MIT, leading the Katabi Lab and directing the MIT Center for Wireless Networks and Mobile Computing. Her research bridges AI, wireless systems, and digital health, focusing on non-invasive health monitoring via wireless signals and machine learning. She is a MacArthur Fellow and holds the Andrew & Erna Viterbi Professorship. Key research areas include emotion recognition (EQ-Radio), sleep posture monitoring (BodyCompass), and through-wall human pose estimation. Her lab develops AI systems for biosensors, leveraging RF signals to detect diseases like Parkinson's and Alzheimer's. Notable awards include the ACM Prize in Computing and SIGCOMM's Lifetime Achievement Award. Publications span wireless networks, computer vision, and health tech, with impactful work in CVPR, ECCV, and Nature Medicine. She advises over 20 students/postdocs and collaborates on technologies like in-body backscatter communication and AI-driven drug development monitoring. Labs: Katabi Lab (MIT CSAIL) and the MIT Wireless Center. Ongoing work explores digital biomarkers, self-supervised learning, and scalable health monitoring systems for chronic diseases.

Vivienne Szeمشاهده پروفایل

استاد

• Energy-Efficient Machine Learning
• Computer Vision
• Video Compression/Processing
• +۷ مورد دیگر

Vivienne Sze is a Professor at MIT's Department of Electrical Engineering and Computer Science (EECS), part of the School of Engineering. Her research focuses on energy-efficient computing systems for machine learning, computer vision, and video compression, with applications in autonomous systems, healthcare, and IoT. She leads projects integrating algorithmic innovations with hardware design to achieve low-power solutions for embedded and mobile devices. Her work has been recognized through prestigious awards, including the Primetime Engineering Emmy Award for co-developing the HEVC video compression standard and multiple faculty awards from tech giants like Google and Qualcomm. She co-authored the book *Efficient Processing of Deep Neural Networks*, emphasizing practical hardware-software co-design strategies. Research Interests: Energy-Efficient Machine Learning Accelerators Video Coding and Compression Standards Embedded Systems and Mobile Computing Processing-in-Memory (PIM) Architectures AI for Health Monitoring and Digital Health Sustainability in AI Infrastructure Publications highlight trends in: Optimizing DNNs for edge devices Innovations in entropy coding and CABAC Memory-efficient Gaussian-based algorithms Energy-aware design for photonic computing Awards include IEEE conference best paper awards and industry recognitions for her contributions to video coding and hardware acceleration. Her lab's collaborative efforts span academia and industry, aiming to bridge theoretical research with real-world deployable systems.

Luis Novoaمشاهده پروفایل

دانشیار

• Business Analysis
• Management Science
• Supply Chain Management
• +۳ مورد دیگر

Luis Novoa is an Associate Professor in the Department of Computer Information Systems and Business Analytics at James Madison University’s College of Business, where he also contributes to the MBA program. His academic journey includes a Ph.D. in Decision Sciences from The George Washington University (2016), an M.S. and B.S. in Industrial Engineering from Universidad de los Andes (2007 and 2005, respectively). He has held roles such as Assistant Professor at JMU since 2017, Visiting Assistant Professor at The George Washington University (2016–2017), and Instructor at Universidad de los Andes (2007–2011). His research focuses on business analysis, management science, and applied decision analysis under uncertainty, particularly in supply chain management, logistics, education, and healthcare. Notable work includes optimizing automated package sorting systems, developing educational tools like STRATA for operations research assessment, and Bayesian methods for academic motivation analysis in business analytics courses. Recent articles highlight contributions to bike-sharing system decision-making, supply chain curriculum alignment with industry practices, and stochastic optimization in energy systems. His awards include JMU College of Business Distinguished Teacher (2021–2022) and recognition for summer research excellence (2011). Dr. Novoa’s teaching and research emphasize practical applications of analytics, bridging academic theory with real-world challenges in business and public sectors. He has authored or co-authored over 15 peer-reviewed publications spanning operations research, education, and industry case studies.

• Urban Sustainability
• Climate Action
• Urban Resilience
• +۶ مورد دیگر

Professor Joao Porto de Albuquerque is a Professor in Urban Analytics at the University of Glasgow's School of Social and Political Sciences, serving as Deputy Director of the Urban Big Data Centre (UBDC). He holds affiliate roles at the Centre for Research & Development in Adult and Lifelong Learning (CR&DALL) and previously led the Institute for Global Sustainable Development at the University of Warwick. His interdisciplinary work bridges geography and computer science, focusing on urban sustainability, participatory data methods, and addressing global inequities through community-driven approaches. Education: PhD in Computer Science (University of Campinas, 2006), postdoctoral research at University of Hamburg (2006-2008), and prior academic roles at University of São Paulo and Heidelberg University. Research emphasizes participatory urban analytics, citizen science, and AI ethics in disaster resilience, funded by major grants (e.g., £5.5M+ as PI from ESRC, Gates Foundation). Research interests include urban resilience, climate adaptation, participatory GIS, and data equity in marginalized communities. Notable projects include the Waterproofing Data Project (flood resilience in Brazil), IDEAMAPS (deprivation mapping in Africa), and co-creation of Earth-observation AI systems for slum areas. Publications span over 120 peer-reviewed articles, focusing on spatial data analysis, participatory methods, and urban sustainability. Awards include the ESRC Impact Prize for societal contributions to flood resilience. Active in global collaborations, his work integrates social sciences with environmental and technical disciplines.

• Autonomous Systems
• Signal Processing
• Vehicle Health Management
• +۷ مورد دیگر

Dr Ivan Petrunin is a Research Professor in Signal Processing for Autonomous Systems and a DARTeC Fellow at Cranfield University's School of Aerospace, Transport and Manufacturing. His work focuses on advancing sensor technologies, data fusion, and decision-making systems for Cyber-Physical Systems, with applications in aerospace, ground-based autonomous systems, and urban air mobility. Key areas include Position, Navigation and Timing (PNT), vehicle health management, and AI-driven fault detection. He leads research at facilities like the Muti-User Environment for Autonomous Vehicle Innovation (MUEAVI) and collaborates with industry partners like Airbus, Rolls-Royce, and Thales. Education: BSc and MSc in Design of Electronic Equipment from National Technical University of Ukraine (1996–1998), followed by a PhD in Signal Processing for Condition Monitoring from Cranfield University (2013). Prior to Cranfield, he was a Lecturer in Digital Signal Processing at NTU Ukraine (2001–2005). Research Interests: Autonomous Systems & Sensor Fusion Machine Learning in Navigation and Safety GNSS Integrity & Urban Air Mobility Condition Monitoring & Structural Health Multi-Agent Reinforcement Learning Publications: Over 100 journal/conference articles and book chapters, with recent works emphasizing hybrid sensor fusion, resilient navigation architectures, and AI-driven solutions for GNSS-denied environments. Notable contributions include multi-sensor fusion frameworks for UAVs and Bayesian filter innovations. Awards: FRIN Fellowship, SMAIAA Membership, IEEE and ION Fellowships, and FHEA recognition. His work is supported by ESA, Innovate UK, and EPSRC. Advising & Labs: Supervises PhD students in UAV navigation and machine learning. Leads Cranfield's facilities for autonomous systems experimentation and advanced timing node infrastructure.

Ryan Chapmanمشاهده پروفایل

استادیار

• Musculoskeletal Biomechanics
• Wearable Sensors
• Optical Motion Capture
• +۷ مورد دیگر

Ryan Chapman is an Assistant Professor in the Department of Kinesiology at the University of Rhode Island (URI), leading the Biomechanics & Wearables Laboratory (BWL). His research focuses on musculoskeletal biomechanics, wearable sensor technology, and clinical decision-making, with applications in joint replacement, rehabilitation, and sports performance. Chapman earned his B.S. in Electrical Engineering from the University of St. Thomas, M.S. in Biomedical Engineering from the University of Iowa, and Ph.D. in Biomedical Engineering from Dartmouth College. He held teaching roles at Dartmouth before joining URI. His work integrates optical motion capture, machine learning, and AI to monitor human movement clinically and in daily life. Education highlights include: B.S.E.E., University of St. Thomas (200X) M.S., Biomedical Engineering, University of Iowa (20X) Ph.D., Biomedical Engineering, Dartmouth College (2018) Research interests emphasize wearable sensor validation, joint biomechanics post-surgery, and data-driven clinical tools. His studies on knee and hip arthroplasty recovery, published in journals like Journal of Biomechanics and Journal of Shoulder & Elbow Surgery , highlight his technical expertise. Awards include the 2022 URI College of Health Sciences Research Award and the 2019 ISTA Young Investigator Award. Chapman’s lab develops innovative systems for postoperative monitoring, such as gyroscopic alignment tools and IMU-based motion tracking. He advises students on biomechanical projects, including hip biomechanics in expectant mothers and neural network applications for joint angle quantification. His patents include leg alignment systems and movement monitoring technologies, reflecting his translational research impact.

Hyune-Ju Kimمشاهده پروفایل

استاد

• Statistics
• Biostatistics
• Regression Analysis
• +۳ مورد دیگر

Hyune-Ju Kim is a Professor of Mathematics at Syracuse University's College of Arts & Sciences, affiliated with the Applied Statistics program. Her research focuses on change-point problems, resampling tests, regression model selection, sequential analysis, and statistical applications in genetics. She holds a Ph.D. in Statistics from Stanford University (1988) and a B.S. in Mathematics from Seoul National University (1983). Recent work emphasizes advancements in Joinpoint regression software, including model selection methodologies for health data analysis. Her contributions address complex survey data challenges and longitudinal medical trend studies. She has served on multiple departmental committees, including executive roles in faculty search committees and graduate programs. Teaching responsibilities include advanced statistics courses such as MAT 652 Probability & Statistics II, MAT 654 Linear Models, and MAT 750 Statistical Consulting. Her service roles include statistics liaison for Syracuse University Project Advance and leadership in curriculum development.