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Balint LaczkoView profile

Research Fellow

• Music Technology
• Sonification
• 3D Audio
• +6 more

Balint Laczko is a Doctoral Research Fellow at the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, affiliated with the Faculty of Humanities at the University of Oslo. His research focuses on image sonification and interdisciplinary studies in autophagy, combining expertise in music technology, machine learning, and computer vision. Education: Master's degrees in Classical Composition (Liszt Academy of Music, Budapest, 2017) and Performance Technology & Electroacoustic Composition (Norwegian Academy of Music, Oslo, 2021). Research interests include 3D audio, audiovisual analysis, and the development of tools for musical gesture analysis. His work bridges artistic and technical domains, with publications in conferences like ICAD and ACM. Key projects: AUTORHYTHM (biological-music tech collaboration), Sonification Pilot (bioRITMO).

Alessandro OrsoView profile

Professor

• Software Engineering
• Software Testing
• Program Analysis
• +3 more

Alessandro (Alex) Orso is a Professor in the School of Computer Science and Interim Dean of the College of Computing at Georgia Institute of Technology. He holds an M.S. in Electrical Engineering (1995) and a Ph.D. in Computer Science (1999) from Politecnico di Milano, Italy. Since 2000, he has been a faculty member at Georgia Tech. Affiliations: School of Computer Science, Scientific Software Engineering Center, Center for Experimental Research in Computer Systems (CERCS), and Online Master of Science Computer Science (OMSCS). Research Focus: Software engineering with emphasis on testing, program analysis, and improving software reliability/security through formal methods and tools. His research has been funded by DARPA, NSF, IBM, and Microsoft, among others. He co-founded the Scientific Software Engineering Center to advance methodologies for high-performance scientific software. Orso is a Distinguished Member of the ACM and an IEEE Fellow. Key contributions include developing techniques for automated REST API testing, program debloating, and cross-browser web application testing. His work bridges theory and practice, emphasizing real-world system validation. Awards: Four impact awards: ISSTA (2017, 2021), ASE (2020), IBM Haifa (2013) Editorial roles: ACM TOSEM, IEEE TSE Program chairs: ISSTA 2010, FSE 2014, ICSE 2017 Advising & Grants: Supervised over 40 students (PhD, Master's, undergrad). Secured funding from government/industry partners. Tools developed include AutoRestTest, Barista, and X-PERT. Labs/Teams: Leads the Arktos Research Group, focusing on software testing, analysis, and tool development. Collaborates with industry and government on applied research projects.

• Scientific Visualization
• Data Analysis
• Medical Applications
• +6 more

Ingrid Hotz is a Professor in Scientific Visualization at Linköping University, affiliated with the Department of Science and Technology (ITN) and the Center for Medical Image Science and Visualization (CMIV). She holds a Master's in Theoretical Physics from Ludwig Maximilian University (Munich) and a PhD in Computer Science from the University of Kaiserslautern. Her research focuses on data analysis and scientific visualization, spanning applications in fluid dynamics, medical imaging, and large-scale simulations. She has led research groups at the Zuse Institute Berlin (2006–2013) and the German Aerospace Center (DLR, 2013–2015). Her work integrates methods from computer graphics, computational geometry, and topology. Key research areas include multi-field visualization, topological data analysis, and scalable systems for ocean data exploration. She has contributed to software tools like VIAMD and pyParaOcean. Notable collaborations include material science research (e.g., beryllonitrene synthesis) and large-scale conference organization (Eurographics 2020, attracting 23,000 participants). Her research bridges theoretical foundations with practical applications in medicine, engineering, and environmental science. Publications highlight advancements in visualization techniques for molecular dynamics, medical imaging, and climate modeling. She actively participates in interdisciplinary projects, such as predicting liver steatosis dynamics and developing frameworks for analyzing brain activity via fMRI data. Her work emphasizes bridging gaps between computational methods and real-world scientific challenges.

• Climate Science
• Environmental Data Management
• Geographic Information Systems (GIS)
• +3 more

Jon Blower is an academic affiliated with the University of Reading's Department of Geography and Environmental Science. His work focuses on climate data management, environmental data visualization, and geospatial technologies. He has contributed to projects like the C3S ECEM climate service, the CHARMe metadata initiative, and the GODIVA2 web mapping system. His research spans cloud computing applications in environmental science, oceanographic data dissemination, and urban density analysis. He has authored over 40 peer-reviewed publications and technical reports, including foundational work on Climate Forecast metadata conventions and cloud-based GIS systems. Blower has led interdisciplinary efforts in integrating environmental data quality frameworks and developing open-source tools for geospatial analysis. Education & Background: While specific educational details are not explicitly stated, his extensive contributions to environmental science and computing imply advanced training in these fields. His work often bridges computer science and environmental applications, suggesting a multidisciplinary academic background. Research Focus: Key areas include: Data interoperability standards (e.g., CF metadata conventions) Climate service development for energy policy Interactive environmental data visualization systems Cloud computing for large-scale environmental datasets Oceanographic data synthesis and quality frameworks Recent Trends in Publications: Recent work emphasizes urban systems analysis (2023), renewable energy-climate integration (2018), and cloud infrastructure for environmental science (2014/2016). Earlier contributions focused on ocean data systems (2009-2012) and grid computing for climate modeling (2006-2009). Awards & Grants: No specific awards listed, but his sustained contributions to major projects like GODAE and MELODIES reflect institutional recognition. Active in grant-funded initiatives related to environmental data infrastructure. Labs/Teams: Collaborates with teams at the National Oceanography Centre, NASA, and European climate initiatives. Core contributor to projects managed by organizations like ESA and the UK's Natural Environment Research Council (NERC).

Sarah HarrisView profile

Professor

• Computer Architecture
• FPGA Design
• RISC-V Systems
• +3 more

Sarah Harris is Professor and Undergraduate Coordinator in the Department of Electrical and Computer Engineering at University of Nevada, Las Vegas. Her research focuses on computer architecture education, FPGA-based systems, and hardware implementations of neural networks. Research areas include: RISC-V architecture education tools FPGA-based hardware design Embedded AI systems Computer engineering pedagogy Her publication portfolio shows strong focus on educational innovation with 7 publications (2021-2024) on RISC-V teaching tools and MOOCs, alongside hardware implementations of neural networks and contributions to bioinformatics tools. Earlier work includes digital design fundamentals and memory systems.

• Musical Artificial Intelligence
• Algorithmic Composition
• Music Information Retrieval (MIR)
• +4 more

Professor Nick Collins is a Professor in the Department of Music at Durham University. His research focuses on live computer music, musical artificial intelligence, and computational musicology. He is also an active performer as a composer-programmer-pianist, engaging in algorave and electronic chamber music performances. His academic contributions include co-editing The Cambridge Companion to Electronic Music (2007/2017) and The SuperCollider Book (2011/2024), as well as authoring Introduction to Computer Music (2009). His work bridges theoretical research and practical innovation, emphasizing interdisciplinary approaches to music technology. Key research areas include AI-driven composition, algorithmic music analysis, and live coding practices. Notable projects involve creating AI voice model choirs, analyzing music corpora (e.g., Radiohead), and developing open-source tools for MIR (Music Information Retrieval). His recent work explores the ethical and creative implications of AI in contemporary music production. Supervised student: Andrew Brown Key publications span journals like Royal Society Open Science , Computer Music Journal , and conferences like International Computer Music Conference. Cross-cutting themes include historical electronic music analysis, algorithmic creativity, and the intersection of mathematics and sound art.

Timothy DrysdaleView profile

Professor

• Remote Laboratories
• Engineering Education
• Electromagnetics
• +2 more

Timothy Drysdale is Professor and Chair in Technology Enhanced Science Education at the University of Edinburgh, where he directs the Remote Laboratories group and serves as Director of Strategic Digital Education. His practable.io platform revolutionizes laboratory education through aesthetically-designed remote experiments installed in campus foyers, saving physical space while enhancing accessibility. Research develops novel remote labs based on experiments likened to "science museum exhibits," integrating real-time equipment access via web interfaces. Additional work explores orbital angular momentum in radio communications. His £3M openEngineering Laboratory project received multiple honors including the Queen's Anniversary Prize and THE Digital Innovation Award. Global Online Laboratories Consortium Award (2024, 2018) Queen's Anniversary Prize (2024) Jisc Digital Transformation Award (2023) Guardian Teaching Excellence Award (2018) Teaches across undergraduate engineering programs and supervises doctoral projects in digital education innovation. Advocates for assessment transformation and generative AI integration in education.

Young Jin LeeView profile

Professor

• Mass Spectrometry Imaging
• Metabolomics
• Forensic Science
• +3 more

Young Jin Lee is a Professor of Chemistry at Iowa State University , Ames, IA. His research focuses on advancing mass spectrometry imaging (MSI) technologies, particularly matrix-assisted laser desorption/ionization (MALDI), to address biological and forensic challenges. Key areas include spatial metabolomics, on-tissue chemical derivatization (OTCD), in vivo isotope labeling, and applications in plant systems and clinical diagnostics. Research interests span plant metabolomics , forensic fingerprint analysis , and rapid antibiotic resistance testing . Notable methodologies include OzMALDI for double-bond assignment and multiplex MALDI-MS imaging for latent fingerprint profiling. His lab develops novel instrumentation, such as mobilized electrospray devices and nanoparticle-based substrates, to enhance analytical sensitivity and spatial resolution. Forensic applications highlight predicting fingerprint age via ozonolysis kinetics and linking triacylglycerol profiles to individual lifestyle markers. In plant biology, studies investigate galactolipid biosynthesis in duckweed and maize root metabolism using isotopic tracing. The group also explores 3D MALDI-MSI for single-cell metabolomics in plant and zebrafish embryos. Instrumentation innovations include high-resolution MALDI-MS systems and open-source tools like rMSIcleanup for matrix peak annotation. Collaborative work extends to microbiome metabolomics and pyrolysis analysis of biomass. Labs/Teams: Lee Laboratory (Iowa State University). Research is supported by grants focusing on analytical chemistry, forensic science, and plant biology applications.

• Energy-Efficient Computing
• Hardware Acceleration
• Machine Learning
• +3 more

Dr. David Boland is a Senior Lecturer at the School of Electrical and Computer Engineering, University of Sydney. He holds an MEng and PhD from Imperial College London. His research focuses on energy-efficient hardware acceleration, particularly using FPGAs and application-specific integrated circuits (ASICs), to optimize computational efficiency in domains like machine learning and optical communications. He has contributed to projects involving custom hardware accelerators, federated learning for edge computing, and real-time signal processing. Education: MEng, Imperial College London, 2007 PhD, Imperial College London, 2012 Research Interests: Dr. Boland’s work emphasizes reducing computational overhead through customized hardware solutions. He explores techniques for minimizing unnecessary computations while maintaining accuracy, leveraging FPGA-based designs for parallelism and energy efficiency. Key areas include: Hardware acceleration for machine learning FPGA optimization for neural networks Energy-efficient algorithms for edge computing Online arithmetic and latency-accuracy trade-offs Grants & Collaborations: 2022: On-Board Federated Learning in Orbital Edge Computing (NSW Department of Industry) 2017: Fast Automated Anomaly Detection in Communication Networks (Defence Science & Technology Group) Affiliations: Member of the Net Zero Institute, collaborating on sustainable computing solutions.

Sarah King-HeleView profile

Research Fellow

• Social Sciences
• Survey Analysis
• Data Science
• +3 more

Sarah King-Hele is a Research Fellow at the Cathie Marsh Institute for Social Research , part of the University of Manchester. Since 2011, she has worked with the UK Data Service, focusing on user support, training, and developing educational materials for survey data analysis. Her expertise spans Social Sciences, Survey Analysis, and Data Science, with contributions to frameworks integrating AI and machine learning in social research. Education: PhD in Sociology (2011): The Dynamics of Religious Change: A comparative study of five western countries , supervised by David Voas and Matthew Elliot. Research Interests: Large-scale survey data methodologies. Census and macro-level aggregate data analysis. Applications of AI in social science research. Longitudinal and cross-sectional data analysis techniques. Projects: Principal Investigator for the Data Skills and Training Research Group (2019–2022), focusing on data synthesis, research training, and social science methodologies. Labs/Teams: Active contributor to the Cathie Marsh Institute's Digital Futures initiative, advancing data-driven social research.

Chris ArrellView profile

Associate Professor

• Composition
• Music Theory
• Sound Synthesis
• +3 more

Chris Arrell is an Associate Professor of Music and Director of the Laptop Ensemble Federation (H-CLEF) at the College of the Holy Cross. His expertise spans composition, music theory, sound synthesis, and computer music. He founded H-CLEF in 2015, fostering experimental music performance through technology. Education: D.M.A. in Music from Cornell University. Research focuses on blending acoustic and electronic elements, with works commissioned by institutions like the Fromm Foundation and Alte Schmiede. Notable honors include the Ettelson Composer’s Award and residencies at MacDowell Colony. Key works include Diptych (prepared piano duo), Breathless (piano trio), and Of Three Minds (soprano/piano/computer). His music frequently explores algorithmic processes and live electronics. Awards and recognition highlight his contributions to contemporary music, including commissions from NEXTET and the Pellegrini Festival. His collaborations, such as Walking in Altamira , reflect interdisciplinary innovation supported by the Ditson Foundation.

Brent FurneauxView profile

Associate Professor

• Information System Obsolescence
• Technological Innovation Sustainability
• Financial Technologies
• +3 more

Brent Furneaux is an Associate Professor in the Management Science area at the Odette School of Business, University of Windsor, and serves as Academic Director for the Master of Management program. He holds a Ph.D. from York University’s Schulich School of Business, an MBA from the University of Toronto Rotman School of Management, and a B.Sc. in Chemistry from the University of Western Ontario. His research focuses on information system obsolescence, discontinuance, and sustainability of technological innovations. He also explores financial technologies in the financial services industry and business data analytics applications. His work has been published in journals like MIS Quarterly, Journal of Management Information Systems, and International Journal of Electronic Commerce. Furneaux has received grants including SSHRC funding for IS discontinuance research and Odette School of Business grants. He has held roles at institutions such as Maastricht University School of Business and Economics and Sheridan College. Professional memberships include the Institute of Electrical and Electronics Engineers (IEEE) and Association for Computing Machinery (ACM).

• Intercultural Communication
• Acculturation Theories
• Immigrants' Well-being
• +3 more

Seokhoon Ahn is an Assistant Professor in the Department of Communication Studies at Central Washington University. He holds a PhD from the University of Wisconsin-Milwaukee (2017) and previously taught at Saint Cloud University and Texas State University. His research focuses on intercultural communication dynamics, particularly acculturation processes and immigrants' well-being, with comparative studies between Eastern and Western health communication contexts. Dr. Ahn has published 13 peer-reviewed articles and two book chapters, actively theorizing acculturation frameworks and applying them to diverse populations. He integrates research into teaching, emphasizing cross-cultural communication skills development. His current projects explore situational acculturation variability and bridging gaps between acculturation theory and applied research. Research interests include acculturation strategies, cross-cultural health communication, digital media's role in migration, and educational equity in higher education settings. His work employs mixed methods, including qualitative studies of immigrant experiences and quantitative surveys on student adaptation. Key areas of recent scholarship include analyzing face negotiation theory across cultures, applying the Acculturation Intentions Model to international students, and evaluating digital textbook policies internationally. He also investigates health communication related to pregnancy complications and FDA stakeholder engagement mechanisms.

• Speech analysis
• Experimental phonetics
• Foreign accent
• +3 more

Lya Meister is a Research Fellow at Tallinn University of Technology's School of Information Technologies, Department of Software Science. She has held this position since 2017, continuing her career from the Institute of Cybernetics at TUT where she served as a Research Fellow (2009–2016) and Extraordinary Research Fellow (2005–2008). Her academic background includes a Doctor's Degree in 2011 (University of Tartu) and a Research Master's Degree in 2005 (Tallinn University). Education: PhD: University of Tartu, 2005–2011 Master's: Tallinn Pedagogical University, Estonian Philology, 2002–2005 Bachelor's: Tallinn Pedagogical University, Russian Philology, 1975–1979 Her research focuses on experimental phonetics, speech corpora analysis, and the acoustic characteristics of speech production. Notable projects include the Improving the intelligibility of sung text (2022–2026) and contributions to the Estonian Elderly Speech Corpus. She has organized major conferences like the Phonetics Symposium 2024 and served on international committees for speech technology initiatives. Her awards include the 2023 School of Information Technologies Paper of the Year and the 2012 Best Paper Award from the Institute of Cybernetics. Her work spans over 68 publications, with recent emphasis on plosive closure duration in singing, vowel-consonant intensity ratios, and developmental phonetic changes in adolescents.

Yann BezinView profile

Professor

• Railway Engineering
• Vehicle Dynamics
• Contact Mechanics
• +5 more

Yann Bezin is a Professor in the Department of Engineering at the School of Computing and Engineering, University of Huddersfield, where he serves as Head of Research at the Institute of Railway Research. His academic journey includes an honours degree in Mechanical Engineering from Manchester Metropolitan University and a PhD focused on integrating Flexible Track System Models within vehicle multibody dynamic software. His research spans: Railway dynamics and vehicle-track interaction Wheel-rail contact mechanics and degradation Track system design optimization Multibody simulation methodologies Railway infrastructure innovation Analysis of his recent publications reveals concentrated focus on railway switches and crossings, featuring advanced simulation techniques for dynamic force prediction, infrastructure cost modeling, and material fatigue analysis. His work consistently bridges theoretical mechanics with practical railway engineering challenges. Professor Bezin leads significant projects including CAPACITY4RAIL (EU infrastructure optimization), IN2RAIL (intelligent rail systems), DYNAFREIGHT (long freight train dynamics), and WRIST (rail welding innovations). He supervises PhD candidates and has established the Institute of Railway Research as a hub for railway dynamics expertise.