Prof. Dr. Stephan Schiemann is a faculty member at Leuphana University of Lüneburg specializing in Sports Science and Health Sciences . With over 122 publications and active research in physical education, strength training, and rehabilitation, his work focuses on biomechanics, muscle adaptation, and digital health interventions. Key Research Areas: Strength training, flexibility protocols, youth athlete development, inclusive sports, and digital health applications Projects: KITA GUT & GESUND, RoBaTaS (Rollstuhlbasketball), HeaLinGo (health-language integration) Research Trends Recent publications analyze: Strength-performance correlations across sports (basketball, cross-country skiing) Long-term stretching effects on muscle hypertrophy Measurement error differentiation in ultrasound diagnostics Comparative training methods for plantar flexors His work bridges theoretical development with practical applications in school sports and rehabilitation.
Ina Fichtner is a Professor at the Faculty of Digital Transformation of University of Applied Sciences HTWK Leipzig since 2022. Previously, she led the MINT department at the Institute for Applied Training Science (IAT) in Leipzig for 13 years (2009–2022), focusing on integrating mathematics, informatics, and natural sciences into sports research. Her work bridges computer science , biomechanics , and sports informatics , with extensive projects on athlete movement analysis, data systems (IDA), and digital tools for elite sports. PhD in Computer Science (2007) from TU Dresden and Leipzig University Diplom in Mathematics and Computer Science (2002) from Jena, Dresden, and Sheffield Her research spans data science , sports technology , and applied informatics , particularly in ski jumping , dive analysis , and athlete biomechanics . She has co-authored numerous publications in theoretical computer science and applied sports informatics , including studies on 3D body scanning , inertial sensors , and force-velocity profiling . She served as Alumni Representative and Treasurer of the Friends' Association at HTWK Leipzig, with memberships in German Mathematical Society and German Sports Science Association .
Janet S. Dufek, Ph.D., is a Professor at the University of Nevada, Las Vegas (UNLV) in the Department of Kinesiology and Nutrition Sciences . She also serves as Vice Provost for Faculty Affairs and holds adjunct appointments at the University of Nebraska at Omaha and Rocky Mountain University of Health Professions . Her career spans leadership roles including Associate Dean of the School of Integrated Health Sciences and Director of the Interdisciplinary Health Sciences Ph.D. Program . Education: Ph.D. in Biomechanics (University of Oregon, 1988) M.S. in Scientific Foundations of Kinesiology (Illinois State, 1982) B.S. (Summa Cum Laude) in Physical Education (University of Wisconsin-Superior, 1981) Research Interests focus on biomechanical mechanisms of locomotion , injury prevention , and clinical gait assessment . She specializes in jump-landing dynamics , movement variability , and performance enhancement for clinical populations , advocating for interdisciplinary approaches to solve complex health science problems. Her 15 most recent publications (2019-2024) reflect trends in concussion biomechanics , autism spectrum disorder gait analysis , machine learning applications in diabetes progression , and advanced sensor technology for movement studies . Articles explore topics from head acceleration effects on lower extremity function to weighted vest interventions in autism therapy . Scientific Awards include: Fellow, American College of Sports Medicine UW-Superior Hall of Fame (Scholar-Athlete, 2007) Membership in Phi Kappa Phi and Sigma Xi honor societies As a dedicated mentor , she supervises graduate research projects and advises on interdisciplinary health sciences . Her lab ( REBEL Research Group ) pioneers work in biomechanical injury prevention and gait variability assessment , utilizing pressure-measuring insoles and wearable inertial sensors.
Christopher D. Azzara is the Eisenhart Professor of Music Teaching & Learning at the Eastman School of Music, University of Rochester. He holds affiliate roles in Jazz Studies & Contemporary Media and Woodwinds, Brass & Percussion. His research focuses on creativity, improvisation, and music pedagogy. Azzara earned a B.M. from George Mason University (1981), M.M. (1988), and Ph.D. (1992) from Eastman. Previously, he taught at The Hartt School (1991–2002) before joining Eastman's faculty in 2002, later serving as Chair of Music Teaching & Learning (2010–2018). He has received prestigious awards, including the Edward Peck Curtis Award (2022) and the Eisenhart Professorship (2023). His academic work emphasizes the integration of listening, creating, improvising, and composing in music education. Key publications include Developing Musicianship through Improvisation and Jump Right In: The Instrumental Series . Azzara’s arrangements are published by GIA and Oxford University Press. He performs with the Chris Azzara Trio and collaborates with Eastman faculty and the Rochester Philharmonic Orchestra. Internationally recognized, Azzara has conducted workshops in over 20 countries, including TEDxRochester and Carnegie Hall. His engagements in 2024–2026 include teaching clinics in Germany, the U.S., and Australia, emphasizing creativity-driven music education. His research appears in journals such as the Journal of Research in Music Education and Oxford Handbooks Online . Azzara advocates for innovative teaching methods, blending academic rigor with practical performance experiences.
Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.
Charith Mendis is an Assistant Professor in the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign, with joint appointments in the Department of Computer Science, Electrical and Computer Engineering, and the Coordinated Science Lab. His research focuses on the intersection of compilers, program optimization, and machine learning systems. Dr. Mendis received his educational background from prestigious institutions: Ph.D. in Computer Science from Massachusetts Institute of Technology (2020) S.M. in Computer Science from Massachusetts Institute of Technology (2015) B.Sc. in Electronics and Telecommunication Engineering from University of Moratuwa (2013) His primary research interests center around compiler technology and machine learning systems. Mendis leads the ADAPT lab at UIUC, where his team works on creating high-performance ML optimization techniques and automated compiler construction using machine learning and formal methods. His work bridges the gap between traditional compiler design and modern machine learning approaches, with applications in tensor compilers, graph neural networks, and sparse computation. He has developed novel frameworks for optimizing deep learning workloads, verification of compiler transformations, and performance modeling for emerging hardware architectures. Mendis has established himself as a leading researcher in compiler optimization for machine learning systems, with a particular focus on tensor compilers, graph neural networks, and performance modeling. His recent publications demonstrate increasing sophistication in combining formal methods with machine learning techniques to solve challenging problems in compiler optimization and verification, with multiple papers accepted at top-tier conferences including OOPSLA, PLDI, POPL, and SIGMOD. His notable scientific achievements include: Google ML and Systems Junior Faculty Award (2025) DARPA Young Faculty Award (2024) NSF CAREER Award (2024) Distinguished Paper Award at POPL (2025) William A. Martin Thesis Award for Outstanding SM thesis, MIT (2015) Multiple teaching excellence awards at UIUC (2021-2023) Dr. Mendis actively mentors students through the ADAPT lab, offering research opportunities for undergraduates, master's students, and PhD candidates interested in compiler technology and machine learning systems. His research is supported by significant funding from the ACE center (part of JUMP 2.0), National Science Foundation (NSF), DARPA, IIDAI, and industry partners including Google, Intel, Amazon, and Qualcomm. He teaches advanced courses in compiler construction and machine learning for compilers. He leads the ADAPT lab at UIUC, which focuses on developing advanced compiler technologies for modern machine learning workloads. The lab maintains active collaborations with industry partners and has established itself as a leading research group in compiler optimization for AI systems. Current projects include tensor compilers, graph neural network optimization, and automated verification of deep learning systems.
Dr. Kamil Michalik serves as a Lecturer at Wroclaw University of Health and Sport Sciences within the Faculty of Physical Education and Sports, Department of Sports Didactics. He holds the important roles of Supervisor for the Student Scientific Club Sport Performance and Rector's Representative for the Student Scientific Society. With expertise spanning Exercise Physiology, Sports Science, and Exercise Testing, Dr. Michalik has published 74 scientific papers that have garnered 248 citations. His research focuses on physiological responses to training protocols, performance assessment methodologies, and sport-specific adaptations across various athletic disciplines. Analysis of his recent publications reveals a strong emphasis on performance metrics in cycling, speedway riding, ice hockey, and swimming. His work frequently investigates how respiratory physiology, muscle function, and training protocols influence athletic outcomes. He has developed significant expertise in exercise testing reliability, verification protocols for maximal oxygen uptake, and the application of novel training methods like hypercapnic warm-up techniques. Through the Student Scientific Club Sport Performance, Dr. Michalik mentors students on research topics including interval training effects, physical performance assessment, motor skills development, and respiratory adaptations. His consultation hours for the winter semester 2025/2026 are available both in person (room 241) and via Zoom by appointment. Dr. Michalik maintains an active research presence through his ResearchGate profile (https://www.researchgate.net/profile/Kamil-Michalik) and ORCID identifier (0000-0002-1296-0434), facilitating international collaboration and research dissemination within the sports science community.
Rita E. Urquijo-Ruiz is a Professor at Trinity University in the Department of Modern Languages and Literatures. She is the first Latina faculty member to achieve full professorship at Trinity, specializing in Chicanx/Latinx and LGBTQ+ studies. Her work bridges Mexican, Chicanx, and Latinx literatures, theater, and gender studies. Ph.D. in Literature from UC San Diego Advocate for marginalized communities through interdisciplinary teaching Founder of Global Latinx Studies major and Latinx Leadership Institute Her research focuses on borderlands culture , queer narratives , and transnational Mexican studies . She has received Trinity’s highest service award and multiple Mellon research grants. Her publications and conferences emphasize LGBTQ+ Chicanx identity , undocumented experiences , and performance as activism . She mentors under McNair Scholars and Alvarez Internship programs, while leading committees for MALCS and AJAAS conferences. Key community roles include Board of Directors at Jump-Start Performance Company and Esperanza Peace Center collaborations.
Sam Allen is a Senior Lecturer in Sports Biomechanics at Loughborough University's School of Sport, Exercise, and Health Sciences. He is affiliated with the National Centre for Sport and Exercise Medicine (NCSEM) and specializes in biomechanical research related to sports performance and injury prevention. His academic journey includes a BSc from the University of Birmingham (2000), an MSc from Loughborough (2004), and a PhD in triple jump simulation (2009). Education: BSc Sport and Exercise Sciences, University of Birmingham, 2000 MSc Sports Biomechanics, Loughborough University, 2004 PhD in Computer Simulation of Triple Jump, Loughborough University, 2009 Research focuses on biomechanics of running, sprinting, and jumping, with an emphasis on injury mechanisms, muscle morphology, and performance optimization. Notable areas include sex differences in biomechanics, hamstring injury prevention, and neuromechanical adaptations during exercise. Publications highlight advanced topics like machine learning for injury prediction, force-velocity relationships in sprinting, and biomechanical modeling of prosthetic limbs. His work bridges theoretical simulations and practical athletic performance improvements. No scientific awards are explicitly mentioned. Advising and grants sections remain unreported in the provided text. He is associated with the Lifestyle for Health and Wellbeing and Sport Performance research groups. Labs/teams: Active contributor to NCSEM and biomechanics research teams at Loughborough University.
Dr. Mathijs Hofmijster is an Assistant Professor affiliated with the Faculty of Behavioural and Movement Sciences, Physiology Department at Vrije Universiteit Amsterdam, as well as the Amsterdam Movement Sciences (AMS) and the Institute for Brain and Behavior Amsterdam (IBBA). His research focuses on biomechanics and physiology in sports performance, particularly in rowing and cycling. Key areas include power output measurement, neuromuscular adaptations, and training optimization. He teaches courses such as 'Moving Matters in Health' and supervises graduate research in elite athlete performance. Research Interests: Rowing biomechanics and power output analysis Neuromuscular fatigue and training adaptations Para-cycling performance and adapted physical activity Instrumentation for sports performance monitoring Recent work highlights include a 2024 scoping review on elite para-cycling performance and advancements in blade force measurement techniques (2019). His articles explore topics ranging from muscle morphology in Olympic rowers (2018) to real-time feedback systems improving training compliance (2017). He has supervised one PhD thesis and maintains active collaborations in sports science, contributing to UN Sustainable Development Goals related to health and well-being.
Associate Professor Dr. Maria Violeta GUIMAN is affiliated with the Department of Mechanical Engineering at the Transilvania University of Brașov. Her research focuses on biomechanics, technical acoustics, composite materials, and material resistance. Key interests include acoustic properties of materials, noise insulation, and structural dynamics. She has authored works such as Acustică Tehnică: Îndrumar de Laborator (2017) and contributed to studies on violin acoustics, wood properties, and sports biomechanics. Her publications emphasize innovative applications of composite materials and coatings in acoustics and environmental contexts. Recent work explores tuning acoustic properties via coating systems, porous composites for noise reduction, and cellulose-based materials. She has also investigated biomechanical aspects of sports movements, such as long jump kinematics, and structural responses under dynamic loads. No specific awards or student advisees are listed. Her academic contributions include experimental and theoretical studies on vibration analysis and material characterization, as well as collaborations on biomechanical motion capture technologies.
Michał Krzysztofik is a Professor at the Academy of Physical Education in Katowice, specializing in sports science and exercise physiology. He holds a Master's degree (2014), PhD in Physical Culture Sciences (2018), and a post-doctoral habilitation in Medical and Health Sciences (2022). His research focuses on resistance training strategies, post-activation performance enhancement (PAPE), eccentric training, and blood flow restriction techniques. He collaborates with national sports associations like the Polish Athletic Association and Handball Association, providing scientific support to elite athletes. Notable awards include the Silesian Science Award (2021) and a Ministry of Education Scholarship (2022). Research interests emphasize optimizing athletic performance through biomechanical and physiological interventions. Key areas include sprint mechanics, muscle-tendon stiffness modulation, and training protocols for combat sports. His work integrates practical applications with elite athletes in volleyball, soccer, and track & field. Over 50 peer-reviewed articles since 2021 explore topics like PAPE repeatability, plyometric-isometric combinations, and sprint performance optimization. Personal athletic achievements include Vice-Champion of Poland in Bodybuilding (2017) and Wielkopolska Champion in Bodybuilding (2017). His studies often employ crossover trials and randomized controlled designs to evaluate acute and chronic adaptations in trained populations.
Professor Stephen Bird is a renowned performance scientist and strength and conditioning expert at the University of Southern Queensland (USQ), leading the School of Health and Medical Sciences. He holds the title of Professor (Sport and Exercise Science) and directs the High-Performance Sport program. His roles include Editor-in-Chief of the International Journal of Strength and Conditioning and advisor to organizations like the Australian Strength and Conditioning Association. Education: BHumMov(ExSc), BHumMov(Hons), and PhD from Charles Sturt University. Research Focus: Strength and conditioning methodologies, nutritional supplementation, athlete recovery, and technology-driven performance optimization. Key Projects: '2 WIN 2032' student-athlete empowerment initiative, NBA sleep health studies, and blood flow restriction (BFR) training for muscle/bone health in space travel. Affiliations: Institute for Resilient Regions (IRR), National Health and Medical Research Council (NHMRC) peer review, and collaborations with Flinders University, University of Gloucestershire. Research interests span elite athlete performance (basketball, rugby, hockey), female athlete health, and applications of pupillometry and wearable tech for fatigue monitoring. Awards include the prestigious ESSA Medal (2006) and Life Membership (Western Region Academy of Sport). Teaching includes courses on strength training, sports nutrition, and athlete workload monitoring. He has supervised over 20 doctoral and master’s students, contributing to >40 research outputs annually. Grants include a $832k Quantum wearable sensor project (2024) and $240k AI-driven motion capture initiative. His work bridges academia and elite sport, advising teams like the Brisbane Bullets (NBL) and GB Women’s Basketball. Recent trends in publications emphasize NBA performance metrics, sleep science, and interdisciplinary solutions for athlete resilience.
Yohan PETETIN is an Associate Professor at Telecom SudParis (Institut polytechnique de Paris) in the CITI Department. His research focuses on Bayesian filtering, Monte Carlo methods, hidden Markov models, and multi-object tracking. He has authored over 20 peer-reviewed articles since 2011, with notable contributions in IEEE Transactions on Signal Processing and other top venues. His work bridges statistical signal processing with machine learning applications. PhD: Algorithmes de restauration bayésienne mono- et multi-objets dans des modèles Markoviens (2013, Telecom SudParis) HDR: Generative models for time series data (2023, Institut polytechnique de Paris) Research interests emphasize sequential Monte Carlo algorithms, particle filtering optimizations, and deep learning integration for time-series analysis. Recent work explores expressivity comparisons between recurrent neural networks and hidden Markov models. Teaching includes courses on probabilistic graphical models, Bayesian filtering, and deep learning across undergraduate and graduate programs at Telecom SudParis and affiliated institutions.
Somayeh Moazeni is an Associate Professor at the School of Business, Stevens Institute of Technology. She holds a PhD in Computer Science from the University of Waterloo and has held academic appointments including Visiting Associate Professor at Northwestern University and Postdoctoral Research Associate at Princeton University. Her research focuses on Reinforcement Learning, Stochastic Dynamic Optimization, and applications in Energy Markets, Inventory Management, and Algorithmic Trading. She has authored over 30 peer-reviewed articles and serves as an associate editor for INFOR and PLOS One . Education: PhD (Computer Science, 2012), University of Waterloo; Postdoc (Operations Research, 2012-2014), Princeton University Industry Experience: Senior Risk Analyst at RBC (2011-2012), Risk Analyst at BMO (2010) Awards: IEEE Senior Member (2019), Anita Borg Institute GHC Faculty Scholar (2017), MITACS Poster Competition First Place (2009) Her research spans Bayesian Optimization , Resilient Network Design , and Energy Efficiency . Current funded projects include PSEG Foundation grants for energy resilience and NSF funding for distributed energy resource controls. She advises PhD students in Operations Research and Energy Systems and teaches graduate courses in Reinforcement Learning and Financial Engineering. Key Contributions: Developed stochastic optimization frameworks for energy storage, contact center reliability modeling, and risk-aware trading strategies. Her work on sequential learning for consumer-driven demand response programs has advanced smart grid applications.
