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Babett LobingerView profile

Researcher

• Performance Psychology
• Sport Psychology
• Motor Control Disorders
• +3 more

Babett Lobinger is a Researcher at the Institute of Psychology at the German Sport University Cologne, specializing in Performance Psychology and Applied Sport Psychology. She holds academic qualifications including Dipl.-Psych., MA Sportwiss, and Dr. in Sport Sciences. Her research focuses on Performance Psychology , Motor Control Disorders (e.g., Yips in Golf), Movement Safety in Aging , and Coaching Psychology . She has collaborated with organizations like the DFB (German Football Association) and clubs like Arminia Bielefeld and 1.FC Köln, providing sport psychological consulting and research. Key Projects include: DFG-funded studies on Yips in Golf Cross-cultural training needs analysis for football coaches Development of the Athlete Competency Questionnaire for Employability (ACQE) She teaches in the German Football Association’s (DFB) coaching academy and contributes to sport psychology curricula for trainers. Her work appears in journals like InMind and conferences such as FEPSAC.

Marcel DettlingView profile

Lecturer

• Predictive Analytics
• Applied Statistics
• Data Mining
• +6 more

Dr. Marcel Dettling is a Group Lead in Data Analysis and Statistics at the ZHAW School of Engineering , focusing on predictive analytics, applied statistics, and complex data analysis. He also serves as a Lecturer at ETH Zurich , teaching advanced statistical methods. Education : PhD in Mathematics (2000-2004), ETH Zurich Postdoc in Applied Statistics (2004-2006), Johns Hopkins University His research spans predictive analytics (regression, classification, time series), data mining, and applications in health economics, transportation safety, social sciences , and business analytics . Recent work includes pharmaceutical cost group analysis for Swiss healthcare and predictive maintenance for marine vessels. Selected publications highlight his expertise in flight trajectory modeling , deep learning error mitigation , and statistical frameworks for rehabilitation finance . His projects address diverse fields like crowdworking in nursing, energy optimization for shipping, and customer behavior prediction.

• Data-Driven Organizations
• Artificial Intelligence
• Digital Transformation
• +3 more

Javier Zamora is a Professor at IESE Business School , part of the University of Navarra. He holds a Ph.D. in Electrical Engineering from Columbia University and an M.Sc. in Telecommunications Engineering from the Polytechnic University of Catalonia. Education Ph.D., Electrical Engineering, Columbia University M.Sc., Telecommunications Engineering, Polytechnic University of Catalonia PDG, IESE Business School Research Interests : Zamora specializes in digital transformation, focusing on data-driven organizations and artificial intelligence. His work explores how new technologies reshape business models, organizational structures, and leadership strategies. Publications span topics from AI implementation in finance and sports management to cloud computing in crisis scenarios. His research emphasizes practical frameworks like the "Digital Density" concept and tools for assessing digital maturity. Professional Roles : He co-founded Inqbarna (AI-powered mobile solutions) and served as CEO of eNeo Labs (digital home products). Currently, he directs executive programs at IESE, including Digital Transformation: Senior Management Program and Navigating IT Architecture .

Kayvon FatahalianView profile

Associate Professor

• Computer Graphics
• Real-Time Rendering
• Machine Learning
• +4 more

Kayvon Fatahalian is an Associate Professor in the Department of Computer Science at Stanford University. His research focuses on real-time graphics, high-efficiency simulation engines for entertainment and AI, and large-scale image/video analysis platforms. He explores intersections of computer graphics, machine learning, and high-performance computing to advance systems for interactive applications and AI-driven tasks. His work includes innovations in rendering pipelines, embodied AI simulations, and generative models for 3D content creation. Recent projects address challenges in multi-agent systems, motion synthesis, and scalable rendering architectures. Fatahalian’s contributions span technical systems, algorithmic frameworks, and foundational research in graphics and AI. Notable areas of exploration include: Real-time rendering optimizations for complex scenes AI-driven motion and style generation from sparse inputs Efficient simulation frameworks for deep reinforcement learning Weak supervision techniques for rare category detection His publications emphasize practical systems with theoretical grounding, often bridging hardware/software co-design principles with modern AI methodologies. Current work includes developing agile hardware accelerators and scalable architectures for next-generation interactive systems.

• Fluid Dynamics
• Renewable Energy Technologies
• Mechanical Engineering Education
• +3 more

Buyung Kosasih is a Professor in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering at the University of Wollongong. He has held this position since 2000 and focuses on teaching and research in mechanical engineering, including Machine Dynamics, Finite Element Methods, and Renewable Energy Technology. His research spans fluid dynamics in industrial processes, renewable energy systems, and aqueous lubrication. Key projects include 3D-printed surfboard fin optimization and steel coating dynamics. Research interests emphasize experimental and computational fluid dynamics, particularly in renewable energy turbines and tribological systems. Notable awards include the 2013 Outstanding Contribution to Teaching and Learning Award. He has supervised numerous students and led over 20 funded projects, including ARC grants for steel innovation and renewable energy. Collaborative work includes the Steel Research Hub and HVAC/cool roof efficiency studies.

Ardalan VahidiView profile

Professor

• Optimal Control and Estimation
• Energy Efficient Mobility
• Connected and Automated Vehicles
• +2 more

Ardalan Vahidi is a Professor of Mechanical Engineering at Clemson University, joining in 2005 after receiving his Ph.D. from the University of Michigan. His research focuses on optimal control, energy-efficient mobility, connected and automated vehicles, and human bioenergetics during exercise. Education: Ph.D. Mechanical Engineering, University of Michigan, Ann Arbor, 2005 M.Sc. Transportation Safety, George Washington University, 2001 M.Sc. Structural Engineering, Sharif University of Technology, 1998 B.Sc. Civil Engineering, Sharif University of Technology, 1996 Research Interests: His work integrates control theory with transportation systems to reduce energy use and emissions. He explores eco-driving algorithms, vehicle connectivity, and human factors in cycling performance, leveraging both modeling and extensive vehicle-in-the-loop experimentation. Publications Trend: Recent articles emphasize validated experiments on energy-efficient automated driving, cyclist fatigue modeling, and cooperative control strategies, demonstrating a shift toward cyber-physical validation and interdisciplinary sports science applications. Scientific Awards: Best Paper Award, Road User Measurement and Evaluation Committee, TRB 2024 2nd Best Paper Award, IEEE International Automated Vehicle Validation Conference 2023 ASME Automotive and Transportation Systems Best Paper Award 2020 & 2018 IFAC Young Author Award 2019 Advising & Grants: He mentors numerous graduate researchers and postdocs; prospective students are directed to an online form for open positions. His research has been supported by NSF, DOE, DOT, and industry partners, although specific grant details are not listed here. Labs & Teams: He leads the Clemson Vehicle & Energy Systems Laboratory, conducting vehicle-in-the-loop experiments and collaborating with interdisciplinary teams across mechanical engineering, transportation, and sports science.

• Exercise Physiology
• Bone Physiology
• Pediatric Exercise Medicine
• +4 more

Panagiota (Nota) Klentrou is a Distinguished Professor and Dean of the Faculty of Applied Health Sciences at Brock University, specializing in Kinesiology. Her research focuses on exercise physiology , bone development , and the health implications of sport training in youth , particularly examining cellular mechanisms linking exercise, diet, and lifelong bone health. Supported by NSERC, CIHR, Osteoporosis Canada, and the International Gymnastics Federation Education: PhD, FCSEP (Fellow of the Canadian Society of Exercise Physiology) Her work spans bone physiology , inflammatory responses to exercise , and sclerostin-mediated tissue cross-talk , with recent studies exploring the impact of obesogenic diets , acute exercise , and nutritional interventions on skeletal growth and adaptation. Key findings include the role of sprint interval training in modulating adipose tissue Wnt signaling and the effects of dairy consumption on bone turnover markers. Scientific Awards & Distinctions Fellow, Canadian Society for Exercise Physiology (CSEP), 2020 Marilyn Rose Graduate Leadership Award, 2017 TVO's Best Lecturer nominee, 2010 Chancellor’s Chair for Research Excellence, Brock University, 2009 Award for Distinguished Research & Creative Activity, Brock University, 2006 Dr. Klentrou actively supervises graduate and undergraduate students in projects related to bone physiology , inflammation , and exercise adaptation , and collaborates with organizations like Osteoporosis Canada and the International Gymnastics Federation.

Maia AngelovaView profile

Professor

• Artificial Intelligence in Healthcare
• Data-Driven Models
• Machine Learning
• +7 more

Professor Maia Angelova is a leading academic in data science and mathematical physics at Aston University's Aston Digital Futures Institute (ADFI) and College of Engineering and Physical Sciences. Her research focuses on interdisciplinary AI applications in healthcare, including precision medicine, chronic disease modeling, and athlete performance analytics. She previously held roles as Professor of Data Analytics at Deakin University (2017–2023) and Professor of Mathematical Physics at Northumbria University (1997–2016), with early experience as a College Lecturer at Oxford University (1991–1996). Education: PhD, MSc, and BSc in Physics from Sofia University 'St. Kliment Ohridski'. Research interests span AI-driven healthcare solutions, dynamical systems modeling, and sports performance analysis. Her work addresses sleep disorders, diabetes management, chronic pain, and athlete performance using advanced machine learning and data analytics. She has secured over £5M in research funding and supervised over 30 PhD students and postdoctoral researchers. Awards include Fellowship of The Institute of Physics. Professional memberships include The London Mathematical Society, Australian Mathematical Society, and Complex Systems Society. Key achievements include founding the Data to Intelligence research centre (2018–2020) and leading large-scale interdisciplinary projects. Current initiatives focus on precision healthcare through AI integration in clinical decision-making systems.

Simon ShibliView profile

Professor

• Sport Economics
• Elite Sport Performance
• Event Impact Assessment
• +2 more

Simon Shibli is Professor of Sport Management and Head of the Sport Industry Research Centre (SIRC) at Sheffield Hallam University. A Chartered Management Accountant (CIMA), his research examines finance and economics in sport, including elite sport performance, economic impact of major events, and sport participation analysis. He directs SIRC, a £1m business unit, and has authored textbooks on sport economics and facility management. Current projects include evaluations for Sport England, UK Sport, and international comparisons of elite sport systems. Key contributions: National Benchmarking Service for Sport England Economic impact studies for The Open Golf Championship International comparative analysis of elite sport policies (SPLISS)

Jørgen Arendt JensenView profile

Professor

• Medical Ultrasound
• Biomedical Signal Processing
• Digital Signal Processing
• +4 more

Jørgen Arendt Jensen is a Professor of Biomedical Signal Processing at the Technical University of Denmark (DTU), with dual affiliations in the Department of Health Technology and the Department of Electrical Engineering (DTU Elektro). He leads the Center for Fast Ultrasound Imaging (CFU), a collaborative initiative involving DTU, BK Medical, Rigshospitalet, and DTU Nanotech. His research focuses on advanced medical ultrasound technologies, including synthetic aperture imaging, vector flow imaging, and ultrasound simulation, aiming to improve clinical image acquisition efficiency and accuracy. He teaches medical imaging courses and co-initiated the joint biomedical engineering program between DTU and the University of Copenhagen. Jensen’s work contributes to UN Sustainable Development Goals related to health and innovation. His research interests span algorithm development for fast ultrasound imaging, blood velocity characterization, and simulation of ultrasound systems. He supervises multiple PhD students and collaborates on projects involving transducer design, real-time imaging systems, and microvascular pathology analysis. Recent publications emphasize advancements in super-resolution ultrasound imaging, transducer optimization, and pressure gradient estimation. His lab, CFU, develops cutting-edge imaging solutions for clinical applications. Jensen’s contributions include patents on ultrasound imaging techniques and collaborative ventures to enhance diagnostic capabilities through interdisciplinary engineering.

• Housing Economics
• Health Economics
• Macroeconomics
• +3 more

Dr. John Glen is a Visiting Professor at the Cranfield School of Management, Cranfield University. He previously served as Director of the Executive MBA (2002–2004) and Full-Time MBA (2004–2007). His research focuses on housing economics, health economics, and macroeconomics, with notable work on mortgage arrears, property valuation impacts of school performance, and waste management economics. He regularly comments on UK and global macroeconomics and football finance for BBC media, having provided over 75 interviews in three years. Education : Not explicitly listed, but affiliated with Cranfield School of Management. Research Interests : Housing economics, health economics, macroeconomic trends, and sports finance. He employs econometric models to analyze policy impacts on markets, such as school performance on property prices and mortgage default risks. His articles span topics like waste incineration valuation, breast cancer treatment costs, and mortgage arrears determinants. He has advised major clients including Kuehne + Nagel, Jaguar Land Rover, and government entities in Dubai and Abu Dhabi. No awards are listed, but his work has been cited in over 10 studies on mortgage arrears and credit risk. Labs/Teams: Not explicitly mentioned, but collaborates with institutions like the Council of Mortgage Lenders and co-authored studies with Catarina Figueira and Joseph Nellis.

• Sports Science
• Physical Education
• Exercise Physiology
• +3 more

Raúl Arellano Colomina serves as a Professor in the Department of Physical Education and Sports within the Faculty of Sports Sciences at the University of Granada, Spain. His institutional base is located at Carretera de Alfacar, S/N, 18071 Granada. His academic expertise centers on Sports Science and Physical Education , with specialized focus in Swimming biomechanics , Exercise Physiology , and Athletic Performance optimization . Research activities are conducted through university facilities including the Swimming Pool building where instructional sessions occur. Professor Arellano Colomina maintains active teaching responsibilities with structured tutoring hours: Tuesdays 9:30-11:00 and 13:00-14:30 during first semester; Wednesdays 16:30-18:45 in second semester. Contact is available via university phone (958244388) though email remains unlisted in directory records.

Anthony A GattiView profile

Research Fellow

• Biomechanics
• Medical Imaging
• Machine Learning
• +7 more

Anthony A Gatti is a Postdoctoral Scholar at Stanford University's Wu Tsai Human Performance Alliance and School of Medicine. His research integrates biomechanics , medical imaging , and machine learning to advance musculoskeletal health diagnostics, particularly focusing on knee osteoarthritis and exercise physiology. Education : Ph.D. in Rehabilitation Science (McMaster University, 2021), M.Sc. in Rehabilitation Science (McMaster University, 2015), B.Sc. in Kinesiology (McMaster University, 2013) His research develops automated tools for quantifying knee anatomy and integrating anatomical data with biomechanical models . These methods analyze acute responses to exercise and long-term joint degeneration, leveraging MRI , deep learning , and statistical shape modeling . Recent publications emphasize AI-driven segmentation , exercise-induced cartilage changes , and biomechanical simulations , spanning journals like Magnetic Resonance in Medicine and Arthritis & Rheumatology . Trends include machine learning validation for clinical predictions and open-source tool development for musculoskeletal analysis. Scientific Awards : CIHR Postdoctoral Fellowship (top 1%), Mitacs Accelerate Entrepreneur, Forge Student Start-Up Competition Winner, multiple scholarships from McMaster University He founded NeuralSeg , a company commercializing deep learning-based MRI segmentation technology. Collaborations include Stanford's Digital Athlete Moonshot Project with advisors like Scott Delp and Garry Gold.

• Sport training
• Physical education and sport
• Programming and periodization in sports
• +3 more

Răzvan Sandu ENOIU is a Professor at the Department of Motor Performance, Faculty of Physical Education and Mountain Sports, Transilvania University of Brașov. His work focuses on sport training methodologies, physical education innovation, and the integration of technology in athletic performance analysis. He is affiliated with the university’s research initiatives and has contributed to interdisciplinary studies bridging sports science with educational technology. Research Interests: Sport training programming and periodization Applications of wearable sensors and modern technology in sports Optimization of athletic performance through data-driven approaches Impact of extracurricular activities on motor skills development His publications explore topics such as Alpine skiing performance analysis, vital sign monitoring in athletics, and the sociological effects of technology during the pandemic. Recent work includes advancements in javelin throwing biomechanics and balance training methodologies using Bosu balls. Professor ENOIU collaborates with international journals and contributes to conferences on sports science and child development.

Paul WardView profile

Associate Professor

• Distributed Systems
• Computer Networks
• Autonomic Computing
• +3 more

Paul Ward is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo and a faculty fellow at the IBM Centre for Advanced Studies. He holds a PhD (2002) and MASc (1993) from Waterloo and a BScE (1998) from the University of New Brunswick. His research focuses on distributed systems management, dependable systems, autonomic computing, wireless networks, and IoT. Key areas include fault detection in web services, service-oriented networking, and optimization of wireless mesh networks. Ward's publications span computer networks, cognitive science, and sports analytics, reflecting interdisciplinary applications of computational methods. He holds two patents in mobile web services and fault resolution.