David Lo is an OUB Chair Professor and Director at the Information Systems and Technology Cluster , School of Computing and Information Systems , Singapore Management University . His research spans the intersection of Software Engineering , Cybersecurity , and Data Science , focusing on improving software quality, security, and developer productivity through socio-technical analysis and artifact evaluation. He has over 15 international Scientific Awards , including ACM Fellow (2023), IEEE Fellow (2022), and ASE Fellow (2021). His work has been funded by NRF , MOE , NCR , and AI Singapore . David leads the Software Analytics Research (SOAR) group and has mentored numerous PhD students , many of whom hold faculty positions or work in tech giants like Microsoft. He actively engages in service , chairing conferences like ICSE 2025 and ESEC/FSE 2024 , and serves on editorial boards of journals such as IEEE Transactions on Software Engineering . His recent keynotes address critical topics like AI for safer systems and LLM applications in software architecture , reflecting his vision for integrating AI into software engineering practices.
Dr. Apurva Narayan is an Affiliate Professor in Computer Science and Data Science, and an Associate Member in Mechanical Engineering at the University of British Columbia's Irving K. Barber Faculty of Science. His research focuses on artificial intelligence, machine learning (particularly explainable AI and quantum ML), data mining, cybersecurity of cyber-physical systems, and decision-making under uncertainty. He holds a PhD from the University of Waterloo (Systems Design Engineering) and a Bachelor's in Electrical Engineering from Dayalbagh Educational Institute. Education: PhD in Systems Design Engineering, University of Waterloo (2015) Bachelor of Engineering in Electrical Engineering, Dayalbagh Educational Institute (2008) Research Interests: Explainable AI/ML and quantum machine learning Data analytics and mining Safety/security of cyber-physical systems Graph-theoretic analysis of complex systems Decision-making under uncertainty Reverse engineering complex software systems Awards: Systems Society of India Young Scientist Award (under 40) MITACS Accelerate Award (2013) Dr. T.E. Unny Memorial Award (2011) Multiple teaching nominations at University of Waterloo Advising & Grants: Supervises graduate students in AI/ML and cybersecurity. Secured grants including MITACS Accelerate and Waterloo scholarships. Active in patent filings related to timed regular expressions. Labs/Teams: Engaged in collaborations within the UBC Department of Computer Science and cross-disciplinary projects with Mechanical Engineering on system reliability and quantum computing applications.
Prof. Mathias Klier holds the Péter Horváth Endowed Professorship for Business Administration with a Focus on Business Information Management at the University of Ulm's Department of Business Analytics. His research focuses on big data analytics, data quality, AI explainability, and social impact of information systems. Klier has held previous academic roles at the Universities of Augsburg, Innsbruck, and Regensburg, where he contributed to data quality metrics and enterprise systems research. He has authored over 100 peer-reviewed articles in journals like MIS Quarterly and Decision Support Systems, and serves as a track chair for ICIS and ECIS conferences. Education: PhD in Business Administration (2008), University of Augsburg (Dissertation: 'Designing Customer-Centric Information Systems') MSc in Business Mathematics (2005), University of Augsburg Research Interests: Klier’s work bridges technical data quality challenges with societal impacts. Key themes include probabilistic metrics for data currency/consistency, ethical AI design, and leveraging peer networks for unemployment support. His recent projects apply explainable AI to public services and workforce development. Key Achievements: Recipient of Research Prize of the Swabian Economy (2008) Winner of Vodafone Foundation Award (2005) Awarded Ciborra Award (2018) for innovative research on event-driven duplicate detection Advising & Grants: Klier’s team has secured funding for projects on future skills forecasting and refugee integration via digital peer groups. He advises on AI literacy initiatives in K-12 education and collaborates with industry partners like German car manufacturers. Labs/Teams: Leads the Business Analytics Institute at Ulm, focusing on data-driven decision making and AI ethics. Active in interdisciplinary research networks including the German Information Quality Management Initiative.
Yehoshua Perl is a Professor of Computer Science and Director of the Structural Analysis of Biomedical Ontologies Center at New Jersey Institute of Technology (NJIT). His research focuses on biomedical ontologies, semantic networks, and quality assurance methodologies for medical terminologies. He leads projects funded by the National Institutes of Health and U.S. National Library of Medicine, including frameworks for auditing biomedical ontologies and developing interface terminologies to improve EHR usability. His work integrates computational methods like large language models and convolutional neural networks with ontology engineering to address challenges in medical informatics. Key research interests include ontology evolution visualization, SNOMED CT refinement, and the application of abstraction networks for knowledge summarization. He has pioneered methodologies for auditing complex concepts in ontologies such as ChEBI, NCIt, and Gene Ontology. Recent projects emphasize improving patient comprehension of EHRs through AI-driven simplification and clinical entity recognition systems. Federal Grants: Family-Based Framework Of Quality Assurance For Biomedical Ontologies (NIH, 2015–2019) Taxonomies Supporting Orientation, Navigation and Auditing of Terminologies (NLM, 2007–2011) His publications span ontology design patterns, semantic type assignments, and visualization tools like BLUSNO for SNOMED CT. He collaborates internationally on standards for ontology reuse and has contributed to the CIDO coronavirus ontology. Current work includes leveraging generative AI for hierarchical relationship prediction and EHR annotation frameworks tailored to cardiology and other specialties.
Keith Harris is a Senior Lecturer in Statistics at the School of Computing and Digital Technologies, part of the College of Business, Technology and Engineering at Sheffield Hallam University. He joined in January 2020 as a Lecturer in Statistics and transitioned to his current role in October 2023. He serves as the Athena Swan Champion for the School and oversees the Online MSc programs in Computer Science and related fields (e.g., Artificial Intelligence, Cyber Security, Data Analytics, Software Engineering). His academic journey includes postdoctoral roles at the University of Glasgow and University of Sheffield, focusing on machine learning and microbial data analysis. Education : Bachelor of Science (BSc) Master of Science (MSc) Postgraduate Diploma (PGDip) Research Interests : Dr. Harris specializes in statistical modelling, data analytics, and machine learning applications across diverse domains. His work bridges statistical theory with practical challenges in ecology (e.g., biodiversity modelling), bioinformatics (e.g., microbial community analysis), and engineering (e.g., manufacturing processes). Recent projects include advancing machine learning methodologies for medical and biological prediction problems and improving tools for metagenomics data analysis. Grants & Advising : While no advisees are listed, his research has been supported by projects such as "Classifiers in Medicine and Biology" and "Simulation Tools for Automated Manufacturing." He actively contributes to interdisciplinary collaborations within the Industry and Innovation Research Institute. Labs & Teams : Engaged with the Digital Analytics and Technologies group and the School’s MSc program leadership. A member of the University’s LGBT+ network and a strong advocate for Equality, Equity, Diversity, and Inclusion initiatives.
Dr. Shane Hall is an Assistant Professor at the Jake Jabs College of Business & Entrepreneurship, University of Montana. He specializes in operations research, mathematical optimization, and management science. His research focuses on applying quantitative models to enhance organizational efficiency, particularly in military systems, pediatric vaccination logistics, and supply chain management. Education: Ph.D. in Industrial Engineering from University of Illinois at Urbana-Champaign (2006) M.S. in Operations Research from Air Force Institute of Technology (2000) B.S. in Mathematics from Brigham Young University (1997) Research Interests: Dr. Hall's work integrates optimization methods with discrete-event simulation to solve complex problems. He has contributed to military operations, pediatric vaccination formulary design, and logistics optimization. His recent focus includes risk analysis frameworks and simulation optimization techniques. Awards: Finalist for David Rist Prize (2017) Excellence in Teaching Award (2009) George Harper Award (2006) Teaching: Teaches Operations Management (BMGT 322) and Operations and Supply Chain (BMGT 565) courses regularly. His teaching emphasizes practical applications of optimization and operations research principles. Service: Serves as a reviewer for journals like Journal of Defense Modeling and Simulation and Optimization Letters . Active in professional organizations such as INFORMS and MORS.
Mahdi Fahmideh is an Associate Professor in Cyber Security at the School of Business, University of Southern Queensland (UniSQ), Australia. He holds a PhD in Information Systems from the University of New South Wales (UNSW) and MSc/BSc in Software Engineering from Azad University, Iran. His research focuses on Cyber Security, AI Ethics, Blockchain, and IoT, with a track record of securing ARC grants and international visiting fellowships. He has published in top-tier journals like European Journal of Information Systems (EJIS), IEEE Transactions on Software Engineering (TSE), and ACM Computing Surveys (CSUR). His career includes roles as Senior Lecturer at UniSQ, Lecturer at the University of Wollongong, and Postdoctoral Researcher at UTS. Awards include a Best Paper Award (2018) and multiple research excellence recognitions. He teaches courses in Cyber Security, Data Mining, and Information Assurance. His grants include ARC Linkage projects on Adversarial Machine Learning (AUS $445K) and Blockchain in Visual Arts (AUS $570K). Fahmideh’s recent work explores AI-Human collaboration (e.g., ChatGPT in software development) and trustworthy AI frameworks. He leads course development in Cyber Security and mentors students in HDR programs. His industry experience includes 8 years as an analyst programmer in software systems for publishing, insurance, and government sectors.
Roberto Rodriguez-Echeverria is an Associate Professor at the Computer Languages and Systems Department of the Universidad de Extremadura (Spain). He leads the Applied Informatic Technology Institute and co-founded MetrikaMedia, a SaaS company for multimedia content measurement. His research focuses on software engineering, model-driven engineering, machine learning, and legacy system modernization. Education: Bachelor and Master in Computer Science (2000), Universidad de Extremadura Master on Education and IT (2012), Universitat Oberta de Catalunya PhD in Computer Science (2014), Universidad de Extremadura Research interests include data-driven software development, medical image segmentation using SAM models, and educational technology applications like chatbot performance analysis in exams. He explores reproducible data science workflows and hybrid recommendation systems for media. Recent work highlights include advancing loss function analysis for COVID-19 lung scans and developing cost-efficient medical image segmentation techniques leveraging SAM's zero-shot capabilities. He also studies the impact of AI tools like ChatGPT on academic assessment methods. His contributions span over 50 publications since 2004, with recent focus on smart city applications, cloud cost estimation, and cooperative social process modeling. Rodriguez-Echeverria's work bridges theoretical computer science with practical industry solutions through his lab's applied research initiatives. Labs/Teams: Applied Informatic Technology Institute (Director) i3 Lab (Affiliated)
Robyn Lutz is a Distinguished Professor of Computer Science and Faculty Member in Bioinformatics and Computational Biology at Iowa State University. She directs the Laboratory for Software Safety (LSS) and co-directs the Laboratory for Molecular Programming (LAMP). Her research focuses on software engineering for safety-critical systems, molecular programming, and formal methods. She has held roles such as ACM Distinguished Scientist and IEEE Fellow. Her work spans federally funded projects including NASA’s safety-aware ecosystems for unmanned systems and NSF initiatives on molecular programming and software dependability. She has authored influential publications on safety assurance cases, chemical reaction networks, and requirements engineering for nanoscale systems. Dr. Lutz has served on program committees for major conferences like ICSE, RE, and FSE, and delivered keynotes at venues like SAFECOMP and RE 2016. Her contributions include advancements in safety-critical software design, molecular systems verification, and interlocking safety frameworks for autonomous systems. She teaches courses such as Software System Safety and Requirements Engineering, and has developed tools like PLFaultCAT for safety analysis. Her labs focus on bridging software engineering principles with emerging domains like synthetic biology and nanotechnology.
Gordon Kindlmann is an Associate Professor of Computer Science at the University of Chicago, affiliated with the Systems Group research community. His work bridges computational imaging science and visualization theory, focusing on biomedical applications and machine learning integration. He leads projects in diffusion MRI analysis, surgical planning tools like SlicerDMRI, and theoretical advancements in visualization design. Research Interests: Biomedical Image Analysis Scientific Visualization Theory High Performance Computing Medical Imaging Algorithms Machine Learning Applications Recent Articles Trends: His work emphasizes cardiovascular modeling (e.g., aortic dissection prediction) and visualization validation techniques. Recent collaborations include optimizing visualization tools for scalability and accuracy in threaded data exploration. Awards: None explicitly listed in provided text. Grants/Advising: Involved in CDAC Discovery Grants (2019) and actively supports student research, though specific advisees are not listed here. His lab develops open-source tools like Diderot for tensor field visualization. Labs & Teams: Member of the Systems Group, a collaborative environment advancing systems research, programming languages, and software engineering.
So Young Sohn is a distinguished Professor at Korea University's College of Business, Department of Management Engineering, with over two decades of impactful research in technology management and operations research. Her scholarly contributions have established her as a leading expert in technology credit scoring, data mining applications, and technology convergence analysis. Dr. Sohn's research interests span technology credit scoring for SMEs, operational research methodologies, data mining techniques, machine learning applications in business contexts, technology convergence patterns, patent analysis, and SME financing mechanisms. Her work bridges theoretical rigor with practical business applications, particularly focusing on Korean case studies that have broader international relevance. She has pioneered innovative approaches using knowledge graphs, multiplex networks, and deep learning techniques to solve complex business problems. Her publication portfolio reveals consistent research trends toward increasingly sophisticated analytical methods, evolving from traditional statistical models to advanced machine learning and network science approaches. Recent work demonstrates particular focus on technology convergence, digital therapeutics, and AI applications in business decision-making. The interdisciplinary nature of her research spans business analytics, engineering, healthcare, and environmental science. Dr. Sohn has received recognition through numerous high-impact publications in premier journals including Expert Systems with Applications, European Journal of Operational Research, Scientometrics, and IEEE Transactions. Her research has been consistently funded through competitive grants focusing on technology management and innovation. As an academic mentor, Dr. Sohn has advised numerous doctoral students who have gone on to productive research careers, with many continuing to collaborate with her on ongoing projects. Her research team has secured substantial funding for projects related to technology credit scoring, technology convergence analysis, and predictive analytics applications. Dr. Sohn leads a dynamic research laboratory focused on technology analytics and decision support systems, collaborating with industry partners and government agencies to translate research findings into practical business solutions. Her current work emphasizes sustainable technology development and AI-driven decision support systems for complex business environments.
Muhammed-Ugur Karagülle is a Researcher at the Institute of Computer Science, Department of Databases and Information Systems at Freie Universität Berlin. His work focuses on developing AI-driven healthcare solutions and information systems for medical and veterinary applications. He is affiliated with the university's research group specializing in databases and information systems, contributing to advanced projects such as AINA, SurgeRate, and mHealthAtlas. Research interests include medical informatics, mobile health (mHealth) platforms, veterinary diagnostics systems, and AI integration in healthcare workflows. His projects address challenges in disease diagnosis (e.g., schistosomiasis), surgical performance evaluation, and regulatory frameworks for digital health applications. Key contributions include the design of HaLowNet (a WiFi-based emergency healthcare system), the PRECOSE grayscale conversion method for medical scoring boards, and collaborative platforms like mHealthAtlas for evaluating mHealth applications. His work emphasizes interdisciplinary collaboration and human-centered design principles. Currently, he is involved in projects such as XRay2Model, mCIS.vet (mobile clinical information systems for veterinary medicine), and process optimization for digital health applications. Office hours are held weekly, requiring prior email registration.
Prof. Saskia van Ruth is a leading academic in food supply chain integrity, holding positions at University College Dublin (Emeritus Special Professor) and Wageningen University & Research (WUR) as a Guest Professor. She specializes in food authenticity, fraud prevention, and sustainable agriculture. Her expertise spans food chemistry, chemometrics, and analytical methods. She has extensive experience in research coordination, including projects on food fraud vulnerability in global supply chains, spice authentication, and olive oil integrity. Key research interests include the application of spectroscopic techniques (e.g., hyperspectral imaging, MALDI-TOF MS) for food authentication, social network analysis of food crime mechanisms, and traceability of agricultural products. She has supervised numerous PhD students and contributed to courses like FQD36306 Food Fraud and Mitigation. Her work bridges academia and industry, addressing real-world challenges in food safety and integrity. Recent publications focus on isotopic analysis of food products, fraud detection in seafood and spices, and the development of rapid authentication technologies. She has collaborated on international projects such as EU-China-SAFE, targeting enhanced EU-China food safety partnerships.
Daniel Weghuber is Professor and Department Chair at Paracelsus Medical University's Department of Pediatrics. His research focuses on pediatric obesity management, metabolic disorders, and pharmacotherapy. Research areas include: Anti-obesity medications for youth Neonatal laboratory diagnostics Clinical guideline development Metabolic function in inflammatory bowel disease Publications emphasize evidence-based obesity management, novel therapeutic approaches, and optimization of pediatric care protocols. Recent works address medication efficacy in adolescents and minimally invasive diagnostics. He leads projects on mitochondrial function in IBD and EURAS (epilepsy research). Current research examines climate impacts on migration through machine learning models.
Ezio Bartocci is a Full Professor in Formal Methods for Cyber-Physical Systems Engineering at TU Wien's Faculty of Computer Science. He leads the Trustworthy Cyber-Physical Systems (TrustCPS) Group within the Cyber-Physical System Research Unit. His research focuses on formal verification, probabilistic systems, and runtime monitoring, with applications in autonomous systems, safety-critical software, and embedded systems. Roles & Affiliations: Full Professor, TU Wien (100% research focus) Principal Investigator in projects funded by EU, WWTF, FFG, and industry partners Chair of the Curriculum Commission for Computer Engineering Editor-in-Chief of the Formal Methods in Outer Space series Research Interests: Formal methods for CPS: verification, synthesis, and runtime monitoring Probabilistic programming and loop analysis Temporal logic specifications and mining Automated tools for safety-critical systems (e.g., Polar, MoonLight) Applications in healthcare, robotics, and autonomous vehicles Key Projects: ProbInG (2020–2025): Analyzing probabilistic loops ARTIST (2021–2026): AI and robotics safety EdgeAI (2022–2025): Optimizing embedded processing TAIGER (2023–2027): Trustworthy AI and CPS Grants & Funding: €10M+ secured from EU Horizon 2020, WWTF, FFG, and industry partners like TTTech Auto AG. Academic Leadership: Teaches courses on logical methods, CPS engineering, and scientific research at TU Wien. Supervises PhD students in formal methods and CPS domains. Tools Developed: Polar (probabilistic loop analyzer), MoonLight (spatio-temporal monitoring), and FIM (fault injection tool).
