Dr. Tamás Koltai is a Professor and Dean at the Faculty of Economics and Social Sciences of Budapest University of Technology and Economics (BME). He leads the doctoral school's Specialization Group in Production Management. His roles include overseeing academic programs and research in production management, operations research, and efficiency analysis. Education: Doctor of the Hungarian Academy of Sciences (2016) Dr. habil. (2000), Budapest University of Technology and Economics Candidate of Technical Sciences (1987), Hungarian Academy of Sciences M.Sc. in Mechanical Engineering (1983), BME Faculty of Mechanical Engineering Research Interests: Dr. Koltai focuses on production management optimization, including the application of Data Envelopment Analysis (DEA), sensitivity analysis in mathematical models, and the integration of robotics in assembly lines. His work bridges theoretical models (e.g., MILP/CP optimization) with practical industrial challenges, particularly in healthcare efficiency and educational management. Notable Awards: IEOM Society Teaching Excellence Award (2021) BME GTK Faculty Memorial Medal (2016) János Susánszki Award (2013) Széchenyi Professorship Scholarship (1999–) Teaching & Leadership: He has held visiting roles at the University of Seville (1990–1992) and the University of Michigan (1988/89). His teaching excellence is recognized through awards and his contributions to business simulation education. His research often collaborates with industry partners to address real-world operational challenges. Labs/Teams: Leads the Production Management Specialization Group and contributes to interdisciplinary teams focusing on manufacturing efficiency and healthcare operations within BME.
Dr. Wei David Dai is an Assistant Professor of Computer Science at Purdue University Northwest and Director of the Advanced Intelligence Software (AIS) Lab. His research focuses on robust deep learning, data quality, and public safety technologies like gunshot detection systems. He previously worked at IBM China as a senior engineer and served in Arkansas state government as a data scientist. Education: Ph.D. in Computer and Information Sciences (University of Arkansas at Little Rock, USA, 2020) M.S. in Information Science (University of Arkansas at Little Rock, USA, 2016) M.S. in Software Engineering (South China University of Technology, China, 2013) B.S. in Computer Science (Central South University, China, 2007) Research Interests: His work spans robust deep learning models, distributed computing systems, and privacy-preserving technologies. Notable projects include public safety innovations such as acoustic gunshot detection and AI-driven campus security systems. Articles Trends: Recent publications emphasize public safety applications (e.g., mass school shooting simulations) and deep learning robustness evaluation (e.g., the Accuracy-Stability Index metric). Earlier works address cloud computing optimization and data quality frameworks. Awards: Recipient of the 2024 Excellence in Research Award and multiple IBM honors for technical excellence and instruction. Grants & Advising: Leads the Indiana Space Grant Consortium-funded satellite imaging project and Purdue Provost Grant for gunshot detection. Advises doctoral and master’s students on AI ethics, distributed systems, and public safety. Labs: The AIS Lab develops AI tools for public safety, equipped with GPU resources for audio and image analysis.
Wolf Ketter is a Full Professor of Next Generation Information Systems at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University, and Chaired Professor of Information Systems at the University of Cologne. He serves as Director of the Institute of Energy Economics (EWI) in Cologne and leads the Erasmus Centre for Future Energy Business in Rotterdam. He is a leading figure in designing sustainable smart markets using advanced computing and simulation techniques. His research focuses on Information Systems , Machine Learning , Energy Economics , and Sustainable Smart Markets . He pioneered the use of Competitive Benchmarking through simulation platforms like Power TAC to tackle complex sustainability challenges. His work bridges computer science, economics, and business to design intelligent systems for energy, transportation, and resource allocation. The recent articles highlight a strong trend toward real-time decision-making in sustainable systems—such as electric bus operations, shared electric vehicles, traffic signal control via reinforcement learning, and local energy markets. These reflect his focus on AI-driven optimization , smart market design , and urban sustainability . Scientific Awards: INFORMS ISS Design Science Award (2012) Runner-up for Best European IS Research Paper (2013) ERIM Top Article Award (2013) ERIM Impact Award (2014) He has supervised over 10 PhD students and secured significant research impact through grants and collaborative projects. His editorial roles include serving on the boards of Information Systems Research and MIS Quarterly , the top journals in the IS field. He has chaired over 20 international conferences and workshops, advancing global discourse in trading agents and sustainable systems. Wolf Ketter founded and leads the Learning Agents Group at Erasmus University and chairs the annual Erasmus Energy Forum . His labs and teams focus on building simulation environments and AI agents to model and improve real-world sustainable markets, particularly in energy and mobility.
Kari Lappalainen is an Assistant Professor in the Department of Electrical Engineering at Tampere University, affiliated with the Faculty of Information Technology and Communication Sciences. His research focuses on photovoltaic power systems, energy storage technologies, and renewable energy integration. He leads studies on photovoltaic module aging, parameter identification, and energy storage system optimization for power smoothing and ramp rate control. Key research interests include: Photovoltaic module diagnostics and performance analysis Energy storage system design for hybrid renewable plants Impact of environmental factors (e.g., temperature, cloud cover) on PV efficiency Advanced modeling techniques for photovoltaic systems Recent work emphasizes real-time monitoring of PV degradation via current-voltage curve analysis and optimization of energy storage configurations to mitigate power fluctuations. Over 50 peer-reviewed publications demonstrate sustained contributions to renewable energy systems research. Notably absent are awards or formal advisee listings, though collaboration with institutions like EU PVSEC and frequent conference participation indicate active academic engagement.
Prof. Marc Fischer is a Professor of Marketing Science and Analytics at the University of Cologne, holding the Morrison Faculty Fellowship at UCLA Anderson School of Management. His research focuses on marketing performance management, analytics, and brand strategy. He has held academic roles at institutions including the University of Technology Sydney and the University of Passau. His work bridges theoretical and applied marketing, with contributions to firm value optimization, dynamic pricing, and healthcare marketing. Education and Career: 2011–current: Full Professor at University of Cologne 2014–2020: Senior International Faculty at UTS Business School 2007–2010: Professor at University of Passau 2003–2007: Assistant/Associate Professor at Christian-Albrechts-University Kiel 2002–2003: Visiting Scholar at UCLA 2001–2002: Consultant at McKinsey & Company Research Interests: Prof. Fischer explores how marketing strategies impact firm value and brand equity. His work emphasizes marketing analytics, including econometric modeling of brand performance, advertising effectiveness, and cross-country marketing dynamics. He also investigates healthcare marketing, particularly in prescription drug markets and physician-patient interactions. Key Contributions: His research has been recognized with awards such as the VHB Best Paper Award and multiple nominations for the Paul E. Green Award. Notable articles include studies on brand leverage potential (Management Science, 2024) and corporate social irresponsibility (Journal of Marketing, 2020). Service and Leadership: Co-leads the Key Research Initiative “Analytics and Transformation” at Cologne CEMS Academic Director (global alliance of 34 business schools) Member of the Rector’s Advisory Commission on Bonus Systems, University of Cologne Advisory Board Member of Analyx GmbH and the Marketing Accountability Standards Board (MASB) Labs and Collaborations: Active in interdisciplinary projects like the HPDnet Emerging Group (healthcare networks for pediatric care), funded by the DFG. Collaborates with institutions such as UCLA, the University of Bonn, and multinational corporations through CEMS.
Cong Liu is an Associate Professor of Computer Science at The University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He joined UT Dallas in 2012 as an Assistant Professor and was promoted to his current rank. His research focuses on real-time and embedded systems, cyber-physical systems, and energy-efficient heterogeneous computing. Liu earned his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2013), M.S. from Auburn University (2007), and B.E. from Wuhan University of Technology (2005). His research interests include real-time operating systems, cluster/cloud computing, and autonomous systems. He received the NSF CAREER Award in 2017 to develop algorithmic solutions for real-time data processing in autonomous vehicles and robotics. His work emphasizes GPU-accelerated embedded systems that enable autonomous decision-making in resource-constrained environments. Liu has held roles such as TPC member for IEEE RTAS and reviewer for multiple journals/conferences, including IEEE Transactions on Computers and Journal of Parallel and Distributed Computing. His publications address critical challenges in real-time scheduling, heterogeneous computing, and energy efficiency. He leads research on data-induced challenges in embedded systems, aiming to make autonomous driving systems predictable and controllable. Liu’s contributions bridge theoretical foundations with practical implementations in automotive and robotics domains.
Kyprianos Papadimitriou is a Researcher at the Microprocessor and Hardware Laboratory within the School of Electrical and Computer Engineering at the Technical University of Crete . He holds a PhD in Electronic and Computer Engineering (2012) and has been involved in teaching laboratory courses such as Logic Design , Computer Architecture , and VLSI/ASIC Circuit Design . Research Areas : His work spans Reconfigurable Systems , Hardware Design , Computer Architecture , RFID Systems , and Real-Time Systems . He has developed innovative approaches in FPGA-based dynamic reconfiguration, MPSoC security, and 3D stereo vision for surveillance. Key Trends : Runtime reconfiguration for FPGAs Security frameworks for NoC-based MPSoCs Low-cost embedded vision systems Optimization of reconfiguration overhead Hardware task scheduling methodologies Genetic algorithm implementations on FPGAs Scientific Contributions : 1 USA patent (2005) Co-author of VLSI-SoC 2013 paper nominated for 1st Prize Active member of scientific committees (FPL, ReConFig) Peer reviewer for IEEE, Elsevier, and Springer journals Session chair at IEEE CNS and HPCC conferences Grants & Projects : Participated in competitive European and national programs, serving as scientific manager, coordinator, and technical coordinator. Developed spin-off company (2003-2005) to commercialize master's thesis research. Laboratory & Teaching : Affiliated with the Microprocessor and Hardware Laboratory , focusing on practical training in digital systems, processor-based systems, and VLSI design.
Aida Jebali is a Professor of Operations and Supply Chain Management at SKEMA Business School's Digitalization Academy. She holds a PhD and Habilitation (HDR) from Grenoble Institute of Technology and has held faculty positions at ESIEE Paris, University of Sharjah, Masdar Institute, and Prince Sultan University. Her research focuses on supply chain resilience, pandemic planning, healthcare operations, and maritime logistics. Education: 2023: HDR in Industrial Engineering, Université Grenoble Alpes 2004: PhD in Industrial Engineering, Grenoble INP 2000: Master of Science in Industrial Engineering, Grenoble INP 1999: National Engineer Diploma, Ecole Nationale d'Ingénieurs de Tunis Research Interests: Pandemic resilience in supply chains Maritime logistics and quay crane optimization Emergency medical service design Healthcare operations and operating room scheduling Environmental sustainability in supply chains Recent Contributions: Her work addresses critical challenges such as pandemic-induced disruptions, ambulance relocation systems, and carbon-efficient supply chains. Recent studies include optimizing production under pandemic conditions and resilience strategies for food supply chains. Awards: High Level Scientific Stay (French Ministry of Foreign Affairs, 2009 & 2007) PhD Scholarship Award (French Ministry of Foreign Affairs, 2000) PhD Supervision: Co-director: G. Pinto, H. NOUIRA, R. BOUJEMAA Jury Member: L. WANG Research Affiliations: Senior Editor of IMA Journal of Management Mathematics and active reviewer for top journals such as International Journal of Production Economics .
Dr. Terje Haukaas is a Professor of Structural & Earthquake Engineering at the University of British Columbia (UBC), Department of Civil Engineering, Faculty of Applied Science. He holds a PhD and Master's from UC Berkeley (2003, 1999) and a bachelor's from the Norwegian University of Science and Technology (1996). His research focuses on probabilistic modeling, structural reliability, and earthquake engineering, with contributions to software development (e.g., FERUM, OpenSees). He teaches courses like Structural Analysis, Nonlinear Analysis, and Reliability & Safety. Education: PhD in Civil Engineering, UC Berkeley, 2003 Master's in Civil Engineering, UC Berkeley, 1999 Bachelor's in Civil Engineering, NTNU, Trondheim, 1996 Engineering Degree (Stavanger University College, 1994) and Technician Degree (Stavanger Technical College, 1992) Research Interests: Probabilistic mechanics and reliability analysis Seismic vulnerability and risk assessment Software tools for finite element analysis (FERUM, OpenSees) Timber engineering and structural optimization Awards & Recognition: UBC Killam Teaching Prize (2016) President of CERRA (2015–2019) Keynote/Semi-plenary speaker at major conferences (ICASP12, COMPDYN 2017) Student Appreciation Awards (Top Professor rankings) Grants & Labs: Recipient of grants supporting seismic risk research Developed computational frameworks for structural analysis
Professor Anna Korre is a leading academic in Environmental Engineering at Imperial College London's Faculty of Engineering. She serves as Associate Provost (Sustainability) and held the role of Co-Director of Energy Futures Lab (2018-2024). Her primary affiliation is with the Department of Earth Science & Engineering, where she leads the Minerals, Energy and Environmental Engineering Research Group. Her research focuses on risk modeling, environmental impact assessments, and engineering solutions for sustainable resource production and decarbonization. Key areas include carbon capture and storage (CCS), geothermal energy, and life cycle analysis of industrial systems. Affiliations: Energy Futures Lab, Institute for Molecular Science & Engineering, Minerals, Energy and Environmental Engineering Group Committee Roles: Chair of Earth Science & Engineering Sustainability Committee, member of University Sustainability Strategy Committee Her work integrates computational modeling, artificial intelligence, and multi-disciplinary collaboration to address global energy challenges. Over 150+ peer-reviewed publications and high-impact projects funded by UKRI, EU, and industry partners demonstrate her leadership in advancing sustainable technologies. She has appeared in media including BBC's The Life Scientific podcast discussing carbon capture innovations. Research highlights include optimizing CO2 storage networks, assessing geothermal reservoir risks, and evaluating lithium production sustainability. She champions industry-academia partnerships to translate research into real-world decarbonization solutions.
Professor Denis Doorly is a Professor of Fluid Mechanics in the Department of Aeronautics at Imperial College London's Faculty of Engineering. His research focuses on biomedical fluid mechanics, particularly respiratory and cardiovascular systems, with expertise in computational fluid dynamics (CFD) and aerosol transport. He has published extensively on nasal airflow modeling, cardiovascular MRI simulations, and aerosol dynamics in medical contexts. Key contributions include CFD cohort studies on nasal decongestion effects, benchmarking models for SARS-CoV-2 transmission, and ventilator strategies during the pandemic. Research interests span biological fluid mechanics, biomedical flows, and medical device design. His work integrates computational modeling with clinical applications, addressing issues like tracheal compression, myocardial perfusion, and aerosol extraction during surgeries. Collaborations include studies on isolated heart models and particle deposition in respiratory systems. Affiliations include the Biological Fluid Mechanics and Biomedical Flows groups at Imperial. His publications (139+ articles) highlight interdisciplinary applications of fluid mechanics to healthcare challenges.
Barbara Linke is a Professor in the Department of Mechanical and Aerospace Engineering at the University of California Davis, affiliated with the College of Engineering. She leads the Laboratory for Manufacturing and Sustainable Technologies Research (MASTeR) and serves as Principal Investigator at the Advanced Highway Maintenance and Construction Technology (AHMCT) Research Center. Her research focuses on sustainable manufacturing processes, abrasive machining, and smart manufacturing technologies, with applications in aerospace, biomedical, and automotive sectors. Dr. Linke holds a Dr.-Ing. habil. and has been recognized with the UC Davis Chancellor’s Fellow (2021-2022) and the Outstanding Junior Faculty Award from the College of Engineering. She advises the UC Davis Student Chapter of the Society of Manufacturing Engineers (SME) and the Women Machinists’ Club. She collaborates with the Fire Research Group at UC Berkeley and the Wildfires Research Working Group at UC Davis, integrating sustainability into wildfire-related infrastructure projects. Her research interests include energy-efficient manufacturing systems, lifecycle assessments, and the integration of Industry 4.0 technologies. Notable contributions include developing frameworks for sustainable additive and subtractive manufacturing, analyzing residual stresses in aluminum alloys, and advancing mobile 3D printing for disaster response. Her work bridges engineering education with cutting-edge research, emphasizing hands-on projects like the Shigley Hauler design competition. Dr. Linke’s labs and affiliations include the Materials Decarbonization and Sustainability Center and the UC Davis AI Center in Engineering, reflecting her commitment to interdisciplinary innovation. She has authored over 50 peer-reviewed articles, with recent focus on smart manufacturing systems, renewable energy integration in machining, and sustainable biomedical implant production.
Dr. Ihab Hijazi is a researcher at the Chair of Geoinformatics , Technical University of Munich, specializing in 3D geospatial modeling and BIM-GIS integration . He teaches courses such as CAFM - Facility Management and GIS and contributes to advancing CityGML standards and urban digital twins . Research Focus : Hijazi’s work bridges Building Information Modeling (BIM) and Geographic Information Systems (GIS) , emphasizing interoperability , semantic transformation , and smart city infrastructures . His projects include the Smart Sustainable Districts (SSD) and Smart District Data Infrastructure , focusing on urban energy systems and data harmonization. Publications highlight his contributions to CityGML utility networks , urban growth simulations , and semantic modeling frameworks. He actively develops 3DCityDB and participates in standardization initiatives like the DIN Spec 91607 Digital Twin for Cities .
Professor Jing Meng is a leading academic at University College London's Bartlett School of Sustainable Construction, holding the position since 2023 after progressing from Lecturer (2019-2021) to Associate Professor (2021-2023). She concurrently serves as a fellow at the Cambridge Centre for Environment, Energy and Natural Resource Governance and maintains active editorial roles as Executive Editor of the Journal of Cleaner Production and Associate Editor for Journal of Geophysical Research: Atmospheres. Her research spans three interconnected domains: Energy Transitions and Technology Innovation (examining cost forecasts and structural emission declines in China), Climate Change Policies (analyzing South-South trade effects and multinational enterprise emissions), and Emission-Health-Socioeconomics Nexus (assessing air pollution impacts and integrated co-mitigation strategies). This interdisciplinary approach is reflected in her publication record across Nature family journals and PNAS. Analysis of her recent publications reveals a consistent focus on global carbon accounting methodologies, with increasing attention to subnational (city-level) analyses, health co-benefits of climate policies, and technological innovation pathways for hard-to-abate sectors. Her work frequently employs multi-regional input-output modeling to trace emissions through complex supply chains. AGU Global Environmental Change Early Career Award (2023) MIT Technology Review Innovators Under 35 Asia Pacific (2022) Clarivate Highly Cited Researcher (2020-2024) Nature Communications Top 50 Earth Sciences Article (2018) MDPI Emerging Sustainability Leader Award (2020) Environmental Research Letters Best Early Career Article (2017) Professor Meng has secured substantial funding from diverse sources including NERC, the British Council, Quadrature Climate Foundation, The Royal Society, and UCL internal grants. She leads an interdisciplinary research group focused on technology innovation and climate policy, with particular emphasis on China's role in global emissions systems. Her work directly supports Sustainable Development Goal 13 (Climate Action) through actionable policy insights.
Dr. Ken Ferens is an Assistant Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba. He serves as the Computer Engineering Champion in the Centre for Engineering Professional Practice and Engineering Education and directs the Applied Cognitive Intelligence (ACI) Research Group. Dr. Ferens is a senior member of the Institute of Electrical & Electronics Engineers (IEEE), Chair of the EduManCom Chapter of the IEEE, Vice-Chair of the Computer and Computational Intelligence Chapter of the IEEE, and Chair of the Industry, Teaching Assistants, and Student Forums for Engineering Curriculum Review and Improvement. Ph.D. (Computer Engineering), University of Manitoba, 1996 M.Sc. (Computer Engineering), University of Manitoba, 1991 B.Sc. (Electrical Engineering), University of Manitoba, 1989 Dr. Ferens has over 33 years of research experience in computational intelligence, focusing on cognitive machine learning, artificial intelligence, cognitive computational intelligence, chaos theory applications, agent-based models, and various optimization algorithms including simulated annealing, genetic algorithms, artificial neural networks, and particle swarm optimization. His research applies these techniques to develop software and hardware intrusion detection systems for cybersecurity applications. He teaches graduate-level courses on Computer Network Security and Applied Computational Intelligence, providing students with theoretical background and hands-on experience in state-of-the-art security methods. Analysis of Dr. Ferens' recent publications reveals a strong focus on applying cognitive and chaotic computational techniques to cybersecurity challenges, particularly malware detection and network intrusion detection. His work increasingly integrates complexity theory, fractal analysis, and hybrid optimization approaches to enhance security systems' effectiveness. There's a clear progression toward more sophisticated machine learning architectures applied to increasingly complex security scenarios, with growing emphasis on real-world IoT and network security applications. Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2022) Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2015) Best Journal Paper Award for 2013 (Journal of ICT Research and Applications) Best Poster Award at 12th International Conference on e-Health Networking, Application & Services (2010) Best Paper Award at IASTED International Conference on Computer, Electronics, Control, and Communication (1991) Dr. Ferens collaborates with national and international industry partners including the Department of Advanced Information Management, Content Technology Canadian Tire Corporation (CTC), and Magellan Aerospace. His research group has received funding supporting the Cyber-security Research Program, developing practical applications of computational intelligence for security systems. He has supervised numerous graduate students in the Electrical and Computer Engineering department, focusing on research at the intersection of machine learning and cybersecurity. Dr. Ferens leads the Applied Cognitive Intelligence (ACI) Research Group within the Department of Electrical and Computer Engineering, which focuses on applying cognitive, chaotic, and computationally intelligent algorithms to build intrusion detection systems. The group collaborates with industry partners to develop practical security solutions while providing students with hands-on research experience in cutting-edge security technologies. Their work spans both theoretical algorithm development and practical hardware implementation for real-world security applications.
