جست‌وجوی استاد و پژوهشگر

Grant Tinsleyمشاهده پروفایل

دانشیار

• Body Composition Assessment
• Exercise Physiology
• Sports Nutrition
• +۶ مورد دیگر

Grant Tinsley is an Associate Professor of Exercise Physiology in the Department of Kinesiology & Sport Management at Texas Tech University. He directs the Energy Balance & Body Composition Laboratory, which specializes in advanced body composition assessment, metabolism testing, and dietary supplementation trials. His research integrates exercise physiology, nutrition, and pharmaceutical interventions to modify body composition. B.S. in Physiology and Nutritional Sciences, Oklahoma State University M.S. in Biomedical Sciences, Colorado State University Ph.D. in Kinesiology and Exercise Nutrition, Baylor University Dr. Tinsley's research focuses on body composition assessment methodologies, the impact of nutritional and exercise interventions on body composition, and the validity of consumer health technologies. His work also explores energy balance manipulations such as intermittent fasting and overfeeding, with a particular interest in skeletal muscle estimation, hydration enhancement, and thermogenic supplements. The 15 most recent articles highlight his expertise in body composition assessment (including 3D scanning and bioimpedance validation), nutritional strategies (omega-3 fatty acids, postbiotics, creatine), and exercise interventions. These publications span systematic reviews, clinical trials, and technological evaluations, reflecting interdisciplinary approaches to sports nutrition, metabolic health, and athlete performance analysis. The Energy Balance & Body Composition Laboratory employs dual-energy x-ray absorptiometry, air displacement plethysmography, and ultrasonography to study body composition. Adjacent shared facilities support muscular performance evaluation and exercise training programs. The lab also investigates digital anthropometry and segmental body composition using cutting-edge technologies.

• Biomechanics
• Biomedical Signal Processing
• Gait Analysis
• +۷ مورد دیگر

Marco Caruso is a Assistant Professor at the Department of Electronics and Telecommunications (DET) , College of Biomedical Engineering , Politecnico di Torino . He is a member of the PolitoBIOMed Lab - Biomedical Engineering Lab and focuses on clinical studies and human motion analysis. Research Interests: Biomechanics, Sensor Fusion, Gait Analysis, Digital Medicine, Medical Signal Processing, Wearable Technology Teaching Roles: Course Owner for Design of Programmable Biomedical Devices , Collaborator for Biomedical Signal Processing and Biomedical Instrumentation and Safety courses (2019/2020–2025/2026) Supervised PhD Student: Paolo Tasca ( Bioengineering and Medical-Surgical Sciences , 39th cycle, 2023–ongoing) Patents: System for measuring resistance to passive movement in subjects with muscular disorders (National/International Patent) His recent publications focus on IMU-based motion analysis, telerehabilitation systems, and sensor fusion techniques for digital health applications. Key methodologies include Kalman filters, complementary filters, and machine learning algorithms applied to post-stroke recovery and elderly mobility assessment.

• Robot Manipulation
• Human Measurement
• Haptics
• +۱۲ مورد دیگر

Zixi Gu is an Assistant Professor at Waseda University's School of Creative Science and Engineering, Department of Integrative Bioscience and Biomedical Engineering, since 2025.04. With a Ph.D. in Engineering (2025) and Master of Engineering (2018) from Waseda University, their research focuses on Human-Machine Interfaces Wearable Sensor Systems Intelligent Robotics for Rehabilitation Muscle Activity Estimation Algorithms Research trends show a consistent focus on gait analysis and assistive robotics , utilizing IMU-based systems for real-time muscular activity measurement and developing training devices for elderly mobility preservation. Key innovations include non-contact sensors for knee extensor monitoring and humanoid robots for cultural acceptance in elder care. Scientific recognition includes 2019 : Best Student Paper Award, IEEE ICMA 2019 2019 : Best Paper Finalist, IEEE ICMA 2019 Current teaching responsibilities include Fundamentals of Robotics and Control Systems courses at Waseda University. Actively involved in research projects like the 2025 Research Base Formation Grant for academic infrastructure development.

Joseph J. Sarverمشاهده پروفایل

استاد آموزشی

• Biomechanics
• Orthopaedic Biomechanics
• Tendon Mechanics
• +۵ مورد دیگر

Dr. Joseph J. Sarver serves as a Teaching Professor at Drexel University's School of Biomedical Engineering, Science & Health Systems since 2012, maintaining concurrent research affiliation with the University of Pennsylvania's McKay Orthopaedic Laboratory since 2001 where he progressed from post-doctoral fellow to Senior Research Investigator under Dr. Louis J. Soslowsky. His educational foundation includes: B.S. in Mechanical Engineering from Purdue University (1994) M.S. in Biomedical Engineering from Drexel University (1997) Ph.D. in Biomedical Engineering from Drexel University (2001) Postdoctoral training in Orthopaedic Surgery at the University of Pennsylvania (2003) Dr. Sarver's research program centers on orthopaedic biomechanics with emphasis on tendon mechanics, rotator cuff repair optimization, and neuromuscular adaptation to injury. His methodology integrates animal models (primarily rat and mouse), mechanical testing apparatus development, and advanced imaging techniques including MRI texture tracking and double-quantum-filtered NMR. Key investigations include the REMO project on remobilization after rotator cuff repair and studies of intervertebral disc degeneration. Analysis of his 15 most recent publications reveals consistent focus on shoulder biomechanics (2008-2011) examining rotator cuff repair outcomes, immobilization effects, and functional recovery in rat models, building upon earlier foundational work (1999-2007) in spinal biomechanics, neuromuscular fatigue quantification, and spinal cord injury rehabilitation. Dr. Sarver has actively mentored undergraduate students, Drexel co-op participants, and senior design teams, particularly in developing mechanical testing equipment like the planar biaxial system for soft tissue analysis. His collaborative research network extends to ultrasound experts (Dr. Seghal at Penn), NMR specialists (Dr. Wehrli), and muscle adaptation researchers (Sam Ward at UCSD). He maintains primary laboratory affiliation with the McKay Orthopaedic Laboratory at Penn while directing biomechanics instruction at Drexel, contributing to both institutions' research infrastructure through equipment development and collaborative projects spanning orthopaedic surgery, rehabilitation science, and biomedical engineering.

Kristof Kippمشاهده پروفایل

استاد

• Sports Science
• Biomechanics
• Musculoskeletal Modeling
• +۳ مورد دیگر

Dr. Kristof Kipp is a Professor and Program Director of Exercise Science in the Department of Physical Therapy at Marquette University. He also serves as Co-Director of Graduate Studies for Sport and Data Analytics. His research focuses on sports science and biomechanics, particularly in musculoskeletal modeling, injury prevention, and athletic performance optimization. Dr. Kipp leads Marquette's Motion Analysis and Biomechanics Laboratory, applying advanced techniques to study movement patterns in athletes and clinical populations. Education: PhD in Nutrition and Exercise Sciences (Oregon State University), postdoc at University of Michigan Key Roles: Exercise Science Program Director, Co-Director of Graduate Studies Research interests include joint-level biomechanics, neuromuscular control, and the application of machine learning in sports analytics. He teaches courses like Introduction to Research in Biomechanics and Advanced Applied Biomechanics in Injury Prevention. Recent studies analyze weightlifting techniques, youth pitching biomechanics, and the effects of chronic ankle instability on movement. His work bridges clinical rehabilitation and elite athletic performance through innovative biomechanical modeling and data-driven approaches.

• Machine Learning
• Artificial Intelligence
• Precision Livestock Farming
• +۵ مورد دیگر

Sook Shin serves as a Collegiate Assistant Professor in the Department of Electrical and Computer Engineering within Virginia Tech's College of Engineering. Her interdisciplinary work bridges computer science, agricultural engineering, and bioinformatics through innovative applications of machine learning. Education PhD in Computer Engineering, Virginia Tech Master of Information Technology, Virginia Tech B.S. in Computer Science, Virginia Tech Her research centers on AI-driven solutions for precision agriculture , particularly in livestock monitoring systems using depth imaging and wireless sensors. She develops machine learning frameworks for pig behavior classification, weight prediction, and resource optimization, while also contributing to bioinformatics tools for plant modeling and disease subtyping. Recent work emphasizes edge intelligence for power-efficient sensor networks and secure data labeling pipelines. Analysis of her 15 most recent publications (2012-2025) reveals a dominant focus on precision livestock farming (60% of works), with significant contributions to bioinformatics (25%) and educational technology (15%). Her methodology consistently integrates deep learning with domain-specific sensor data, showing increasing sophistication in multi-modal input processing and real-time system optimization from 2022 onward. Teaching Contributions Applied software design Data structures and algorithms Computational thinking Machine learning applications She actively develops scientific web tools including PlantSimLab for plant biologists and contributes to capstone project frameworks that bridge academic theory with industry applications in smart farming systems.

• Signals and Systems
• Adaptive Systems
• Learning Theory
• +۶ مورد دیگر

José C. Príncipe is a Distinguished Professor at the University of Florida , where he holds the Don D. & Ruth Eckis Endowed Distinguished Professor position in the Department of Electrical and Computer Engineering. His primary research area is Signals and Systems , with a focus on adaptive systems and learning theory. Education Agregado, University of Aveiro (1985) Ph.D., Electrical Engineering, University of Florida (1979) M.S., Electrical Engineering, University of Florida (1974) B.S., Electrical Engineering, University of Porto (1972) Príncipe’s research spans machine learning, computational neuroscience, and biomedical signal processing. He has pioneered work in kernel adaptive filtering, information-theoretic learning criteria, and neural network architectures. His recent publications emphasize uncertainty quantification, spiking neural networks, and robust filtering techniques. His 15 most recent articles reflect trends in machine learning (transformers, predictive coding, reinforcement learning), signal processing (kernel methods, entropy-based filtering), and biomedical applications (electrophysiology, pain prediction). Key subfields include neural interfaces, nonlinear system identification, and statistical dependence measures. Scientific Awards : Fellow, American Association for the Advancement of Science (2021) Fellow, National Academy of Inventors (2021) IEEE SP Society Claude Shannon-Harry Nyquist Technical Achievement Award (2021) Life Fellow, IEEE (2017) SEC Faculty Achievement Award Winner (2016) IEEE Neural Network Pioneer Award (2011) Honorary Doctorate, Aalto University (2010) Gabor Award, International Neural Network Society (2006) Príncipe leads the Computational NeuroEngineering Laboratory (CNEL) at the University of Florida, fostering interdisciplinary research at the intersection of neuroscience and engineering. His work includes grants and collaborations in biomedical systems, brain-computer interfaces, and machine learning theory.

• Physical Activity
• Health Psychology
• Movement Therapy
• +۳ مورد دیگر

Professor Ingo Froböse is affiliated with the Institute for Movement Therapy and Movement-oriented Prevention and Rehabilitation, specializing in research areas such as physical activity, health psychology, and preventive medicine. His work focuses on the intersection of movement science, rehabilitation, and public health. Research Interests: Physical Activity and its psychological impacts Musculoskeletal health and ergonomics in professional performing arts Wearable technology for activity monitoring Child development and motor skills in early childhood Epidemiological effects of pandemics on physical health Esports physiology and health implications Recent projects include funded initiatives like Rücken basic and AiF Geräte Rückenmuskulatur , exploring back health interventions and sports medicine applications. He has also contributed to media discussions on topics like esports mental health and sleep recovery. His research outputs span 347 publications across journals and conferences, with recent focus areas in activity measurement models, pandemic health impacts, and professional dancer wellness. Projects are supported by third-party funding and institutional resources.

• Machine Learning
• Deep Learning
• Edge Artificial Intelligence
• +۵ مورد دیگر

Daniele Berardini is a Research Fellow at the Department of Information Engineering (DII) of Università Politecnica delle Marche in Ancona, Italy. He is also a PhD student under Prof. Emanuele Frontoni, focusing on Edge Artificial Intelligence and real-time human behavior analysis through video surveillance. His work emphasizes lightweight Deep Learning methods for resource-constrained devices, with applications in healthcare monitoring, security systems, and environmental surveillance. Education: Bachelor's degree (cum laude) in Computer Science (2017), University of L'Aquila Master's degree (cum laude) in Computer Science (Network and Data Science) (2019), University of L'Aquila PhD in progress at Università Politecnica delle Marche (since 2020) Research Interests: His research integrates Machine Learning and Deep Learning techniques for developing efficient monitoring systems. Key areas include Edge AI for real-time analysis, human behavior detection in indoor/outdoor environments, and ethical considerations in AI deployment for healthcare and surveillance. His methodologies often combine optimization frameworks with neural networks to enhance computational efficiency. Labs/Teams: He is part of the Vision, Robotics and Artificial Intelligence (VRAI) research group at DII, focusing on interdisciplinary projects such as neonatal care monitoring, weapon detection in video surveillance, and sustainable AI for medical applications. Grants/Advising: No specific grants or advising roles explicitly mentioned in the text.

• Genetic Epidemiology
• Autoimmune Diseases
• Liver Diseases
• +۳ مورد دیگر

Professor Heather Cordell is a leading academic at Newcastle University, specializing in genetic epidemiology and statistical genetics. Her research focuses on identifying genetic factors underlying complex diseases such as primary biliary cholangitis (PBC), autoimmune disorders, and liver diseases. She has pioneered genome-wide association studies (GWAS) and developed statistical methods to analyze genetic data, including Bayesian networks and causal inference frameworks. Collaborating internationally, she has led projects like the RHDGen study on rheumatic heart disease and the ADMISSION collaborative for multimorbidity research. Her work integrates transcriptomics, epigenetics, and biobank data to uncover disease mechanisms and potential drug targets. Key contributions include identifying novel genetic risk loci for PBC, cirrhosis, and congenital heart defects. Cordell’s expertise spans statistical methodology, genetic risk modeling, and translational research, with over 200 peer-reviewed publications. She has advised on large-scale studies in the UK Biobank and contributed to clinical guidelines for liver disease management. Education: Advanced training in statistical genetics and epidemiology (not explicitly detailed here) Affiliations: Newcastle University Medical School, UK Biobank Research Collaborator Her research interests emphasize bridging genetic discoveries to clinical applications, particularly in precision medicine for chronic conditions. She has explored the genetic architecture of diseases using integrative approaches, including epigenetic and proteomic data. Cordell’s work on polygenic risk scores has advanced personalized risk prediction for alcohol-related liver diseases and hypertension.

Daniel Bruce Ennisمشاهده پروفایل

استاد

• Cardiovascular MRI
• Medical Imaging
• Cardiac Mechanics
• +۵ مورد دیگر

Professor Daniel Bruce Ennis is a leading academic in cardiovascular MRI and radiology at Stanford University. He holds a joint appointment in the Department of Radiology and a courtesy appointment in Bioengineering. As Director of Radiology Research at the Veterans Affairs Palo Alto Health Care System, he oversees a growing research program. His career includes a Ph.D. in Biomedical Engineering from Johns Hopkins, a postdoc at Stanford, and a decade leading NIH-funded studies at UCLA. He specializes in developing advanced MRI methods for assessing cardiac structure, function, and remodeling, with a focus on translational applications in adult and pediatric populations. Education: Ph.D. in Biomedical Engineering, Johns Hopkins University (2004) Postdoctoral Fellowship in Radiology and Cardiothoracic Surgery, Stanford University (2008) B.S. in Bioengineering, UC San Diego (1997) Research Interests: Dr. Ennis pioneers MRI innovations for cardiovascular diseases, including cardiac diffusion tensor imaging (cDTI), motion-compensated diffusion encoding, and strain analysis using DENSE MRI. His work emphasizes early disease detection in conditions like Duchenne muscular dystrophy and aortic coarctation, leveraging hybrid mock circulatory loops and computational models. He also develops clinical tools for non-invasive pressure estimation and valve dynamics analysis. Awards & Recognition: 2020 Distinguished Investigator, Academy for Radiology & Biomedical Imaging Research Multiple Distinguished Reviewer Awards from Magnetic Resonance in Medicine (2012-2019) Fellowships in Society for Cardiovascular Magnetic Resonance (2018) and ISMRM (2020) Grants & Leadership: Active NIH study section member (ITD, BMIT), Deputy Editor of Magnetic Resonance in Medicine , and founder of ISMRM Research Exchange Program. Current NIH grants focus on cardiovascular MRI technology development and translational applications. Labs & Teams: Leads the Radiological Sciences Lab at Stanford and collaborates with the CMR Group, Bio-X Institute, and Wu Tsai Human Performance Alliance. His team includes postdocs, graduate students, and clinical collaborators advancing MRI methodologies and cardiac device design.

• Physical Fitness
• Physical Activity
• Sedentary Behavior
• +۳ مورد دیگر

Alicia María Alonso Martínez is an Associate Professor at the Public University of Navarre , affiliated with the Department of Health Sciences. She leads the Exercise, Health and Quality of Life (E-FIT) research group and contributes to doctoral programs in Health Sciences, Social Sciences, and Global Health (collaborating with the University of La Rioja, Lleida, Zaragoza, and Navarre). Her research spans physical fitness, motor competence, and cardiometabolic health across the lifespan, with a focus on preschoolers, adolescents, and older adults. Her recent work examines physical activity interventions, 24-hour movement guidelines, and the impact of gamified family-based exercise programs. She has secured significant grants from institutions like the Instituto de Salud Carlos III and the Navarre Government , including projects such as VIVI-CITA for cognitive-physical enhancement in at-risk elderly and DIActive for diabetes prevention. Her meta-analyses on exercise effects in populations with insulin resistance and hypertension have shaped clinical recommendations. Alonso Martínez supervises doctoral students in pediatric fitness assessment, pandemic-induced behavioral changes, and cardiovascular diagnostics. Her studies bridge clinical, educational, and public health domains, emphasizing interdisciplinary collaboration. She applies advanced methodologies including ultrasound muscle analysis and genetic testing for metabolic conditions, contributing to population-specific normative data in Latin America and Spain.

• Biomechanics
• Human Body Modeling
• Human-Machine Interaction
• +۷ مورد دیگر

Laura Gastaldi is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) of the Polytechnic University of Turin . She is a member of the PolitoBIOMed Lab and the Master's and Continuing Education School . Her academic roles include teaching in doctoral programs since 2013 and serving as course lecturer/collaborator for topics like Mechanics Applied to Biomedical Systems and Automation of Mechanical Systems . Research Interests : Biomechanics Human Body Modeling Human-Machine Interaction Wearable Robotics Parasports Motion Analysis Her 15 most recent publications focus on wearable inertial sensors, exoskeletons, human-robot collaboration, and mobility assistance devices, spanning Biomechanics , Robotics , and Biomedical Engineering . She leads research projects like EMPATHY (2024-2026) and Promobilia (2023-2024), emphasizing accessibility and industrial sustainability. Laura supervises PhD students Claudia Barattini , Michele Polito , and Mattia Antonelli , and holds patents for Directional propulsion assist devices and Active joints for exoskeletons .

• Sports Sciences
• Public Health
• Epidemiology
• +۲ مورد دیگر

Susumu Sawada is a Professor at the Faculty of Sport Sciences, Waseda University , with a Ph.D. in Medicine from Juntendo University. His work focuses on Sports Epidemiology , Public Health , and Biostatistics , particularly the interplay between physical activity, fitness, and chronic disease prevention. His research interests include metabolic syndrome, diabetes, cardiovascular health, and the impact of physical activity on aging populations. Recent studies analyze cardiorespiratory fitness, muscle strength, and step-counting technology in Japanese adults. Key scientific awards include the Encouragement Award (2015) from the Japanese Society of Public Health Contribution Award (2013) from the National THP Promotion Council Green Cross Award (2010) from the Central Labor Disaster Prevention Association 1st Place Winners (2008) from the United State Navy Fellow (2002) at the American College of Sports Medicine His publications span international journals like BMC Public Health , Diabetes Care , and British Journal of Sports Medicine , emphasizing dose-response relationships in physical activity, mortality reduction in older adults, and oxidative stress dynamics.

Emily Whitehouseمشاهده پروفایل

مدرس

• Time Series Analysis
• Financial Econometrics
• Asset Price Bubbles
• +۳ مورد دیگر

Dr. Emily Whitehouse is a Lecturer in Economics at the University of Sheffield's School of Economics, where she has been since 2020. Previously, she served as a Lecturer at Newcastle University from 2018 to 2020. She holds a PhD in Economics from the University of Nottingham (2017), an MSc in Economics and Econometrics (2013), and a BSc in International Business, Finance, and Economics from the University of Manchester (2012). Her research focuses on time series and financial econometrics, with particular emphasis on explosive autoregressive processes, real-time monitoring of economic and financial time series, and forecast evaluation. Key areas include detecting asset price bubbles, assessing bubble regimes, and developing methodologies for bubble dating and crash prediction. She is actively involved in supervising graduate research in these domains. Teaching responsibilities include ECN104: Introductory Finance for Economics. While no scientific awards are explicitly mentioned, her work demonstrates significant contributions to econometric theory and financial market analysis. No grants or lab affiliations are detailed in the provided information.