Tom Mitchell is a Professor of Audio and Music Interaction at the University of the West of England (UWE), Bristol . As leader of the Creative Technologies Laboratory , his research focuses on interactive technologies for creative expression, blending computer science, music, and artificial intelligence. He is the principal investigator for the UKRI Future Leaders Fellowship project "Sensing Music Interactions from the Outside-In" and co-investigator for the Bridge , a £3M creative technology facility. His research spans digital musical instrument design , GPU-accelerated audio processing , and sonification of scientific data . Recent work includes accessibility improvements in virtual environments, AI-driven DMI development, and interdisciplinary collaborations like the MiMU Gloves with Imogen Heap. He also contributes to robotics teleoperation through auditory feedback systems. Selected publications highlight trends in GPU acceleration for audio , generative AI in musical contexts , and human-robot collaboration via sonification. As a software developer , he specializes in C++ and the Juce library , with applications in live performance systems and scientific visualization projects like Soma and danceroom Spectroscopy . UKRI Future Leaders Fellow Active in AHRC and WECA-funded projects Best paper nominations at EvoMUSART and International Faust Conference Mitchell collaborates with institutions including the Bristol Robotics Laboratory , Computer Science Research Centre , and Pervasive Media Studio . His work bridges academic research with commercial applications through ventures like May Productions and x-io Technologies.
Rune Strandberg is an Associate Professor at the Department of Engineering Sciences, University of Agder. He holds a PhD in solar cell physics from NTNU and specializes in photovoltaic materials, solar cell physics, and energy conversion. His research focuses on advanced solar cell concepts including tandem cells, intermediate band solar cells, and thermoradiative energy harvesters. Education: Master of Technology (2005) and PhD (2010) in solar cell physics from NTNU. Pedagogical training includes Uniped courses (2014-2015) and PhD supervision qualification. Current teaching: Renewable Energy, Solar Energy Systems, Electromagnetism, Advanced Photovoltaics Prior roles: PhD student at NTNU (2005-2009), Senior Researcher at Teknova AS (2010-2013) Research areas: New photovoltaic concepts, characterization of photovoltaic cells, solar cell physics, emissive energy harvesters His recent publications analyze band gap optimization, radiative coupling in multi-junction cells, temperature sensitivity, and theoretical efficiency limits across multiple high-impact journals. Collaborators include Anne Gerd Imenes, Alfredo Sanchez Garcia, and Sissel Tind Kristensen. Key contributions include development of analytical models for solar cell performance, field testing of PV modules in Norway, and studies on temperature effects in multicrystalline silicon wafers.
Dr. Sumanta Das is an Associate Professor and Graduate Director in the Department of Civil and Environmental Engineering at the University of Rhode Island. His research focuses on sustainable infrastructure materials, with particular expertise in cementitious materials, composite structures, and advanced computational modeling techniques. He directs a vibrant research group that bridges experimental mechanics with computational modeling and machine learning approaches to address challenges in infrastructure durability and performance. Dr. Das received his educational training from prestigious institutions: Ph.D. in Materials and Structures from Arizona State University (2015) M.Tech. in Structural Engineering from Indian Institute of Technology, Kanpur (2012) B.E. in Civil Engineering from Jadavpur University (2010) His research interests center around developing sustainable and durable infrastructure materials through innovative design approaches. Dr. Das investigates microstructure-property relationships in cementitious systems, with special focus on materials containing microencapsulated phase change materials for freeze-thaw durability, fiber-reinforced composites, and smart cementitious materials with self-sensing capabilities. His work integrates advanced experimental techniques like nanoindentation with computational modeling approaches including finite element analysis, molecular dynamics simulations, and machine learning algorithms to predict material behavior and optimize performance. Dr. Das's recent publications demonstrate a clear trajectory toward integrating machine learning with traditional materials science approaches. His research group has made significant contributions to understanding the behavior of cementitious composites under extreme conditions, developing multifunctional composites with embedded sensing capabilities, and creating computational frameworks that bridge multiple scales from molecular to structural levels. The work shows increasing sophistication in combining experimental validation with predictive modeling. Dr. Das has successfully secured numerous research grants as PI or Co-PI from diverse funding sources including the Office of Naval Research, Department of Defense, US Department of Transportation, and industry partners like Goetz Composites. His research portfolio spans infrastructure durability, composite materials for marine applications, and smart sensing technologies for structural health monitoring. As an educator and mentor, Dr. Das has supervised multiple doctoral and master's students who have completed theses on topics including: Multiscale simulation and machine learning-assisted performance prediction for cementitious composites Performance-based multiscale tuning of inclusion-modified and 3D printed composites Enhancing freeze-thaw durability of cementitious composites through innovative materials design Underwater explosion response of composite structures Implosion pulse mitigation using additively manufactured filler profiles
Ayden Mccarthy is a Lecturer at the Department of Health Sciences within Macquarie University's Faculty of Medicine, Health and Human Sciences. His research focuses on biomechanics, military science, and wearable technology integration for physical performance assessment. Ph.D. in Health Sciences Specializes in predictive modeling and biomechanical validation Active in military ergonomics and wearable sensor research His work applies machine learning to military manual handling and load carriage biomechanics , with recent studies examining 3D body scanning accuracy and joint angle measurement systems under armor conditions. Publications emphasize physical fitness assessment and gender-specific performance metrics in tactical mobility tasks. Article trends show specialization in military ergonomics , biomechanical modeling , and wearable technology validation , with interdisciplinary connections to computer science and health informatics . Collaborations span Medicine , Sports Science , and Engineering domains. Scientific Awards: Best Student Presentation, ABC Sydney (2023) Correspondence available via ayden.mccarthy@mq.edu.au or ayden.mccarthy@hdr.mq.edu.au .
Steven Y. Liang , Regents' Professor at the Georgia Institute of Technology 's Woodruff School of Mechanical Engineering, focuses on precision manufacturing , additive manufacturing , and materials-driven process optimization . His research program bridges materials science and computational mechanics to develop predictive models for advanced manufacturing systems. Ph.D., University of California, Berkeley (1987) M.S., Michigan State University (1984) B.S., National Cheng-Kung University, Taiwan (1980) Dr. Liang's work emphasizes physics-based modeling of thermal-mechanical interactions in machining and additive manufacturing, particularly for Ti6Al4V and Inconel 718 alloys. Recent publications highlight tool wear prediction , laser-assisted micro-milling , and residual stress modeling using machine learning and analytical mechanics. His research has been recognized with the ASME Milton C. Shaw Manufacturing Research Medal (2016) , SME Gold Medal (2021) , and Outstanding Lifetime Service Award of NAMRI/SME (2021) , among others. Funded by federal agencies and aerospace/automotive industries, his work provides scientific foundations for process planning and optimization.
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 .
Hilde Stokvold Gundersen serves as an Associate Professor in the Department of Sport, Food and Natural Sciences at Western Norway University of Applied Sciences (HVL). Her academic position is based at the Bergen KRONSTAD campus where her office is located in room L215. She maintains an active research profile with multiple publications in 2024 across various sports science domains. Dr. Gundersen's research interests span multiple critical areas in sports science, with particular focus on adolescent development in athletic contexts, strength training methodologies, and aquatic safety education. Her work bridges theoretical sports science with practical applications in educational settings, especially in primary school physical education programs. She demonstrates expertise in examining physiological development markers like bone age and their relationship to athletic performance metrics. Analysis of her 2024 publications reveals a strong emphasis on practical applications of sports science research. Her work addresses gender-specific training considerations, developmental physiology in youth athletes, and safety education in aquatic environments. The publications appear in both Norwegian-language educational resources and international scientific journals including the Journal of Applied Physiology and Frontiers in Sports and Active Living, indicating both national and international scholarly impact. While specific awards are not mentioned in the available information, her publication record demonstrates active scholarly contribution to the field of sports science. Her collaborative work with researchers across different institutions suggests integration within broader research networks in exercise physiology and sports pedagogy.
Adam Kelly serves as Associate Professor of Sport and Exercise and Course Leader for the Professional Doctorate in Sport (DSport) at Birmingham City University's Faculty of Health, Education and Life Sciences. He directs the BCU Research for Athlete and Youth Sport Development (RAYSD) Lab and holds accreditations as Senior Fellow of the Higher Education Academy (SFHEA), BASES CSci, and FA UEFA A Licenced Coach. His educational foundation includes a PhD from the University of Exeter, built upon seven years as Head of Academy Sport Science at Exeter City Football Club following his non-league playing career. Professor Kelly's research critically examines organizational structures in youth sport to optimize athlete development pathways and foster inclusive environments. His work spans cricket, rugby, soccer, squash, and swimming, with emphasis on talent identification systems, relative age effects, and equity in sport. International collaborations with partners like Queen's University (Canada) and global sports organizations drive practical applications for evidence-based policies. Analysis of his 100+ publications reveals sustained focus on relative age effects across sports (2022-2025), evolving toward actionable interventions like birthday-banding and flexible chronological approaches. Recent work increasingly addresses inclusivity for underrepresented groups in cricket/soccer and post-pandemic adaptation strategies. His scientific recognition includes: Senior Fellow of the Higher Education Academy (SFHEA) Professor Kelly mentors four embedded PhD students (Shanmugaratnam, Lux, Shafi, Green) within FIFA/ECB/KNVB projects while having graduated five PhDs now in prominent roles. His £1m+ research funding supports industry-academia partnerships that transform talent development practices globally. The RAYSD Lab under his leadership facilitates transnational knowledge exchange through initiatives like the HELS Go Abroad Scheme, connecting UK students with Canadian researchers while driving real-world impact through projects like the BESTA Cricket Partnership and KNVB Relative Age Solutions.
Professor Joseph Wood is a Professor of Visual Analytics at City St George's, University of London, where he serves as a founding member of the giCentre. His academic career spans over three decades, with continuous contributions to Geographic Information Science and visualization since 1990. He previously served as Head of Department for Computer Science at City University between 2014 and 2017. Professor Wood's educational background includes a PhD in Geographical Information Science from the University of Leicester (1996), an MSc in the same field from the University of Leicester (1990), and a BSc in Physical Geography & Geology from the University of Sheffield (1989). His academic progression shows steady advancement from Research Scholar at the University of Leicester (1990-1992) through various lecturer and senior positions to his current professorship. His research interests center on visual analytics and data visualization, with particular expertise in geographic information science and terrain analysis. Professor Wood has developed innovative methods bridging GI Science, Data Visualization, and education domains. His specific interests include narrative of visual analytic design, computational thinking in pedagogy, and novel visualization design for geographic data. His work demonstrates a consistent focus on making complex spatial data understandable through innovative visualization techniques. Analysis of Professor Wood's recent publications reveals a strong emphasis on practical applications of visualization techniques across diverse domains including transportation, epidemiology, sports analytics, and historical migration patterns. His work shows an evolution from foundational geographic information science toward broader applications in visual analytics, with increasing focus on narrative structures, responsive design, and accessibility considerations in visualization. The interdisciplinary nature of his research is evident in collaborations spanning computer science, geography, urban planning, and public health domains. Professor Wood has been actively involved in the academic community, serving on organizing and program committees for major international conferences including IEEE Infovis and VAST, Eurovis, GIScience, Spatial Accuracy, and Geomorphometry. His contributions to the field have been recognized through invitations to deliver keynote talks at prestigious venues ranging from GeoComputation to TEDx, where he presented on topics such as visualizing movement behavior of cyclists. As an advisor, Professor Wood has supervised numerous PhD and Master's students, with current supervision of Julia Crossley (Student conceptualisation of abstraction in computer science) and Jude Nzemeke (Understanding student misconception in recursive algorithmic thinking). His extensive supervision history includes completed PhDs on topics ranging from cycling behavior to spatio-social relations in photographic archives. His academic leadership extends to software development, with contributions to tools like litvis, elm-vega/el-vegalite, giCentre Utils, handy, and LandSerf GIS. Professor Wood is an active member of professional organizations including IEEE (2007-present), Association of Computing Machinery (ACM) (2007-present), and Association of Geographic Information (AGI) (1997-present), demonstrating his commitment to interdisciplinary collaboration across computer science and geographic information domains.
Dr. Sueda Saylan is an Assistant Professor at the Faculty of Engineering, Özyeğin University, since 2024. Her academic journey includes a Ph.D. in Interdisciplinary Engineering (2016) from Masdar Institute (now Khalifa University), postdoctoral research at Khalifa University (2016-2022), and an MSCA Postdoctoral Fellowship at Bilkent University (2022-2024). She has also held visiting researcher positions at MIT (2014) and the University of Tokyo (2016). Education Doctorate: Interdisciplinary Engineering, Masdar Institute of Science and Technology (2016) Master's: Microelectronic Manufacturing Engineering, Rochester Institute of Technology (2004) Bachelor's: Mechanical Engineering, Middle East Technical University (2002) Dr. Saylan's research focuses on memristive devices , photovoltaics , and light-matter interactions at micro/nanoscale . Her work bridges materials science and electronic engineering, with recent publications on memristor-based sensors, spectral filtering in silicon, and machine learning integration for biomedical diagnostics. Key trends from her 15 most recent articles (2013-2025) include: Advancing memristor technology for radiation sensing and vacuum monitoring Optimizing photovoltaic efficiency through light management and antireflection coatings Developing compact, low-power diagnostic devices for pathogen detection Exploring nanoscale electrode materials and switching mechanisms Applying Fourier transforms and interferometry in optical systems Scientific Awards Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship (2022-2024) Dr. Saylan has received research support from prestigious programs and has contributed to interdisciplinary projects involving semiconductor physics, optical engineering, and biomedical diagnostics. Her collaborations span institutions like Khalifa University, MIT, and the University of Tokyo.
Professor Oliver Johnson is a faculty member at the School of Mathematics, University of Bristol, UK, where he serves as Head of School and holds the Professor of Information Theory position. His research bridges information theory, probability, and statistics, focusing on entropy convergence, group testing, and fundamental limits in data analysis. Current PhD students: Kieran Morris, Conor Crilly Ex-PhD students: Matt Aldridge, Leonardo Baldassini, Dan Cowley, Vaia Kalokidou, Tom Kealy, Jennifer Chakravarty, Zichen Gui, Chrys Paschou Ex-postdoc: Erwan Hillion His work includes ORCiD profile and collaborations across information theory, cybersecurity, and ecological modeling.
Dr. Cory Smith is an Assistant Professor in the Department of Health, Human Performance, and Recreation at Baylor University, where he directs the Human & Environmental Physiology Laboratory. His applied physiology research focuses on neurophysiological assessment methodologies, extreme environment adaptations, and sensor-based physiological monitoring systems. Current projects examine neuromuscular disease diagnostics, warfighter performance optimization, and cognitive-physiological responses in austere environments through translational research approaches. Primary research interests include: Aerospace/environmental physiology : Investigating human responses to hypoxia, cold, and gravitational stressors Neurophysiological monitoring : Developing fNIRS/EMG methodologies for clinical and tactical applications Sensor data fusion : Integrating multimodal physiological signals for performance assessment Muscle fatigue mechanisms : Studying neuromuscular adaptations during exertion under environmental constraints Analysis of recent publications (2022-2025) reveals dominant themes in neurophysiological monitoring techniques (particularly fNIRS applications), environmental stressor impacts on human performance, and rehabilitation physiology. Research consistently bridges clinical applications (neuromuscular diseases, cerebral palsy) with tactical performance optimization (marksmanship, combat fitness). Methodological innovations in EMG signal processing and hypoxia protocols form significant technical throughlines. Dr. Smith leads a research team collaborating with clinical practitioners to translate physiological insights into practical interventions for military personnel, occupational workers, and clinical populations.
Miloš Racković serves as a full Professor in the Department of Mathematics and Informatics at the University of Novi Sad, Serbia. He maintains active academic engagement through the Laboratory for the development of information systems, with his office located in the Information technologies and systems office (DMI&DF) on the second floor, room 49. Contact is available via telephone (485)-2868 or email rackovic@dmi.uns.ac.rs, and his personal website (http://www.is.pmf.uns.ac.rs/rackovicm/) provides additional resources. His research spans foundational and applied computer science, with seminal contributions in fuzzy database systems including PFSQL query language development and prioritized fuzzy logic for relational databases and XML. He has pioneered deep learning methodologies through innovative classification techniques using negative and missing features in convolutional neural networks. Additional expertise includes high-performance computing implementations of Lattice Boltzmann methods using OpenCL, robotics (symbolic modeling and trajectory planning), and blockchain applications for Industry 4.0 production processes. His sports analytics work applies neural networks to basketball player and referee movement analysis. Analysis of his 2012-2025 publications reveals a strategic evolution toward interdisciplinary applications, particularly in industrial transformation (blockchain-enabled traceability) and sports analytics. His work consistently bridges theoretical computer science with practical implementations, demonstrating increasing focus on real-world problem solving while maintaining strong foundations in database theory and computational methods. Professor Racković leads the Laboratory for the development of information systems, which focuses on advancing information system methodologies through formal modeling extensions (including Petri net innovations) and practical implementations for uncertainty management. The laboratory's work spans from foundational research in fuzzy logic systems to applied projects in high-performance computing and blockchain integration, fostering innovation in information technology development.
Prof. Dr. Stefan Huber is a Full Professor (W3) at the Faculty of Chemistry and Biochemistry , Ruhr-Universität Bochum , Germany. His research focuses on non-covalent interactions in organocatalysis , particularly halogen bonding , chalcogen bonding , and cyclopropenium derivatives for applications in molecular recognition , crystal engineering , and radical stabilization . Full Professor since 01/2022 Associate Professor (W2) 2014-2021 Independent Researcher at TU Munich 2009-2013 Research Interests include: Design of halogen/chalcogen bond donors for catalysis Supramolecular chemistry in solution and solid phases Quantum chemical modeling of transition states and binding strengths His work bridges experimental synthesis (NMR, X-ray, ITC) with computational methods , supported by the ERC Starting Grant (2015-2020) and collaborations within the RESOLV Cluster . Scientific Awards : Hoechst Dozentenpreis (2016) Robert-Sauer-Preis (2014) Hans-Fischer-Gedächtnispreis (2013) Ernst-Otto-Fischer-Lehrpreis (2012) Thieme Chemistry Journals Award (2010) Students : Over 20 Ph.D. and Master’s students, including Dominik Reinhard, Tim Steinke, Raffaella Papagna, and Julian Stoesser. The group maintains modern synthesis labs and collaborates with institutions like the University of Geneva and TU Munich .
Xuming He is an Associate Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, where he leads the PLUS Lab. His research spans computer vision and machine learning with a focus on developing algorithms that operate effectively under limited supervision and evolving data conditions. His core research interests include weakly-supervised and few-shot learning for scenarios with sparse annotations, continual learning frameworks for knowledge retention during sequential task acquisition, semantic segmentation techniques for scene understanding, and multimodal vision-language representations. He emphasizes interpretable machine learning to build transparent AI systems capable of human-understandable reasoning, addressing critical challenges in model trustworthiness and deployment reliability. Recent publications reveal strong trends toward novel class discovery in long-tailed recognition scenarios, physics-informed generative modeling for scientific applications, and robust segmentation under distribution shifts. His work increasingly integrates large language models for multimodal reasoning while maintaining focus on efficiency in resource-constrained environments like robotic grasping and medical imaging analysis. He actively mentors students, having supervised Qian He to PhD completion and Chuanyang Hu to Master's degree in 2023. He welcomes prospective graduate students through ShanghaiTech's Computer Science & Technology program and offers undergraduate research projects requiring minimum six-month commitments. The PLUS Lab under his direction drives innovation in learning under supervision constraints, with recent work spanning medical tumor analysis, cross-view geolocation, photonic computing, and semiconductor design verification. The lab's research bridges theoretical advances with practical applications across healthcare, robotics, and scientific discovery domains.
