Dr. Ahmed F. Abdelghany is the Associate Dean for Research and Professor of Operations Management at the David O'Maley College of Business, Embry-Riddle Aeronautical University, since January 2006. He specializes in commercial airlines, airports, big data cloud computing, business analytics, and operations research models. Prior to his academic career, Dr. Abdelghany worked in enterprise optimization at United Airlines, Chicago. Education: Ph.D. in Civil Engineering (Transportation Systems) from the University of Texas at Austin (2001) Dr. Abdelghany’s research focuses on airline network planning, flight scheduling, simulation of complex transportation systems, and NextGen air traffic management. He has authored two influential books: Modeling Applications in the Airline Industry (Routledge 2010) and Airline Network Planning and Scheduling (Wiley 2018). His publications analyze airline operations, competitive dynamics, and crowd management in transportation facilities. He teaches courses like Airline Management (BA 315) and Airline Operations & Mgmnt (BA 609), and participates in industry short courses. Dr. Abdelghany contributes to research projects such as NextGen air traffic implementation, integrated airport initiatives, and benefit-cost analysis of arrival management systems. His work bridges academic theory with real-world airline and transportation challenges.
Tarmo Lipping is a Professor in the Department of Computer Science and Engineering at the Faculty of Information Technology and Electrical Engineering, University of Oulu. His work bridges computing sciences with biomedical engineering, environmental modelling, and data-driven societal applications. Doctor of Science (Technology), Information Technology – Awarded 14 Feb 2001 Master of Science (Technology), Information Technology – Awarded 10 Sept 1993 His research focuses on electroencephalography (EEG) , mental workload assessment , depth of anesthesia monitoring , and machine learning applications in healthcare and human-computer interaction. He also contributes to environmental informatics , particularly in land uplift modelling and radionuclide transport , aligning with UN Sustainable Development Goals. Recent publications highlight trends in transformer networks for EEG analysis , wearable HCI systems , data-driven food safety , and participatory municipal governance . His work integrates deep learning, signal processing, and real-world deployment. Scientific awards include: CIMO opettajavaihto (2017) Lipping has supervised numerous master’s students and served as an examiner in diverse topics including data vault modelling , telecom revenue estimation , and EEG hyperscanning . He has evaluated funding applications, acted as a journal reviewer (65 times), and contributed to editorial work. His activities reflect strong engagement in academic service and interdisciplinary research mentorship. He has contributed datasets on Fennoscandian land uplift , lake isolation , and archaeological shorelines to PANGAEA, supporting open science in geosciences and environmental history.
Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.
Professor Trina Myers serves as the Head of School for the School of Information Technology at Deakin University's Faculty of Science Engineering and Built Environment. With extensive experience in academia and research leadership, she plays a pivotal role in shaping IT education and research directions at Deakin. She is also an active member of the Australian Council of Deans of ICT (ACDICT), having served as its immediate past President. Her educational background includes: Doctor of Philosophy in Computer Science from James Cook University Master of Business Administration from James Cook University Master of Information Technology from James Cook University Professor Myers' research focuses on semantic technologies, ontology engineering, Internet of Things, knowledge management, natural language processing, and human-computer interaction . Her work emphasizes interdisciplinary collaboration, bridging technology with fields such as healthcare, marine science, environmental conservation, and business. She has pioneered approaches in academagogy (academic gamification) to enhance online learning engagement, particularly for adult learners. Her IoT research has significant applications in healthcare space optimization, environmental monitoring, and resource management. Her recent publications demonstrate a strong trajectory in applying AI and IoT technologies to solve real-world problems, particularly in healthcare, education, and resource optimization. There's a clear pattern of interdisciplinary work connecting computer science with healthcare, education, and environmental science. Her research increasingly focuses on human-centered technology design, especially for vulnerable populations like adolescents with autism spectrum disorder. Her notable achievements include: Fellow of the Australian Computer Society (2023) Australian Awards for University Teaching (AAUT) Teaching Award (2020) Women in IT Professional Leadership Award Finalist (2020) Asia-Pacific International Triple E Entrepreneurial Educator of the Year Award (1st runner-up, 2020) Australian Computer Society, National Digital Disruptor ICT Educator of the Year (2019) Professor Myers actively supervises doctoral students across diverse research areas including gamification in language learning, brain tumor analysis using deep learning, AI in higher education, AI for refugee resilience, data integrity in edge environments, and quantum-driven satellite networking. She has secured significant research funding, including a recent grant for "Indiginizing ICT Curriculum: A Starter Framework for the Community of Practice" through the Australian Council of Deans of ICT. Her teaching philosophy emphasizes active learning methodologies, Process Oriented Guided Inquiry Learning (POGIL), blended learning, and collective intelligence approaches.
Akash Srivastava is a Research Scientist and Principal Investigator (PI) at the MIT-IBM Watson AI Lab in Cambridge, MA, and Chief Architect of Large Language Model Alignment at IBM Research. His work focuses on generative modeling , Bayesian inference , and machine learning for constrained engineering design . He previously conducted PhD research at the University of Edinburgh under Dr. Charles Sutton and Dr. Michael U. Gutmann on variational inference for generative models using deep learning. His research spans Neuro-Symbolic AI , Language Model Alignment , and Synthetic Data Generation , with applications in 3D modeling , urban logistics , and material science . Recent publications highlight advancements in diffusion models , continual learning , and privacy-preserving data synthesis . As a PI, he collaborates with MIT faculty like Prof. Faez Ahmed and Prof. Rafael Gomez-Bombarelli on projects such as generative modeling for mechanical systems , synthetic data in decision-making , and greener delivery networks . He has received funding through a DARPA grant for machine common sense research.
Zhenyu Yang is a Lecturer and Postdoctoral Researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the College of Engineering through the Department of Civil Engineering and the Urban Transport Systems Laboratory (LUTS) . He holds a PhD in Industrial System Engineering from the National University of Singapore (2022), an M.Eng from Beijing Jiaotong University, and a Diploma in Transportation Engineering from Huazhong University of Science and Technology. PhD, Industrial System Engineering, National University of Singapore (2022) M.Eng, Beijing Jiaotong University Diploma, Transportation Engineering, Huazhong University of Science and Technology His research focuses on urban transportation network modeling , travel demand management , and traffic information provision , with a strong emphasis on handling uncertainty and optimizing shared mobility systems. Recent work explores reinforcement learning applications, vehicle-drone cooperative delivery , and dynamic incident-responsive traffic systems . His publications highlight advancements in ridesourcing algorithms , congestion pricing , and multi-modal transport regulation . As a lecturer, he teaches Transportation Economics , covering demand-supply dynamics, welfare analysis, and environmental policy in transport systems. He is affiliated with EPFL's Urban Transport Systems Laboratory (LUTS) and contributes to the SGC-ENS teaching unit.
Katherine L. Milkman (Katy) is the James G. Dinan Professor at the Wharton School of the University of Pennsylvania, with secondary appointments in Penn's Perelman School of Medicine and School of Arts & Sciences. She co-founded and co-directs the Behavior Change for Good Initiative, a research center dedicated to advancing the science of lasting behavior change. Her work integrates economics and psychology to address challenges like savings, exercise adherence, vaccination rates, and discrimination through large-scale field experiments. Education: PhD in Computer Science and Business from Harvard University; Bachelor's degree (summa cum laude) in Operations Research and Financial Engineering from Princeton University. Research Focus: Milkman's research leverages big data and behavioral science to understand decision-making failures (e.g., self-control, discrimination) and design scalable interventions. Her recent work emphasizes: Nudge-based strategies for education, health, and finance Diversity enhancement in organizational settings Habit formation through incentive structures Publication Trends: Her 15 most recent articles (2022-2025) primarily involve megastudies testing behavioral interventions. Key themes include: leveraging email/reminders to improve math education and vaccination rates; addressing loan delinquency through nudges; and using stereotyping dynamics to increase diversity in hiring. Over 80% employ field experiments across healthcare, finance, and education sectors. Awards & Honors: Thinkers50 Top Management Thinker (2021, 2023) Schmidt Futures Innovation Fellow (2022) Fellow, Association for Psychological Science (2020) Multiple teaching awards from Wharton (2015, 2016) William F. O’Dell Award for impactful research (2017) Advisory & Grants: Milkman has advised major organizations including The White House, Google, Walmart, and the U.S. Department of Defense. Her Behavior Change for Good Initiative secures funding for large-scale social impact research. She hosts Schwab's behavioral economics podcast Choiceology and contributes to policy through op-eds in The New York Times and Scientific American . Labs & Teams: Co-directs the Behavior Change for Good Initiative, collaborating with interdisciplinary researchers (e.g., Angela Duckworth, Sendhil Mullainathan) on longitudinal studies. The initiative designs and tests interventions across health, education, and savings domains.
Dr. Qian Zhang serves as Assistant Professor in the Robert M. Buchan Department of Mining at Queen's University's Smith Engineering, leading the Green Mining Value Chain (GreeMVC) Lab. His research develops strategic frameworks for sustainability and resilience throughout mining value chains, with emphasis on climate change mitigation and resource efficiency in global mineral systems. His academic foundation includes a Ph.D. in Urban Engineering from the University of Tokyo (awarded Japanese Government MEXT Scholarship), complemented by MSc and BSc degrees in Environmental Science plus a Minor in Economics from Peking University. Prior to his current role, he conducted postdoctoral research at the University of Victoria and University of Tokyo while consulting for the World Resources Institute on climate-energy initiatives. Dr. Zhang's expertise spans carbon footprint analysis , life-cycle assessment , and industrial ecology applied to mining systems. He employs advanced methodologies including input-output analysis and material flow accounting to model environmental pressures across urban infrastructure and mineral supply chains. His work specifically addresses greenhouse gas accounting, water-energy nexus challenges, and circular economy implementation in resource-intensive sectors. Recent publications reveal strong methodological convergence between artificial intelligence and environmental assessment, particularly in optimizing mining operations through reinforcement learning and geospatial analysis. Key thematic clusters include carbon accounting standardization, critical mineral sustainability, and policy-oriented modeling of environmental pressures throughout mineral value chains. His research program is supported by major competitive grants: NSERC Discovery Grant (2022-2027) SSHRC Institutional Grant (2023, 2025) NSERC Alliance Missions Grant (2023, 2024) Mitacs Accelerate Grant (2023, 2025) NFRF Exploration Grant (2025-2027) NRCan Energy Innovation Program (2025) Dr. Zhang actively mentors a dynamic research group comprising 10+ graduate students and postdocs, securing collaborative funding through institutional and federal channels. His GreeMVC Lab maintains active partnerships with industry leaders and government agencies to translate research into practical sustainability solutions for the mining sector, with current projects focusing on AI-driven fleet management and life-cycle assessment of mineral supply chains. The GreeMVC Lab operates as a multidisciplinary hub with structured mentorship programs, regular industry engagement events, and international collaborations including the COM symposium on sustainable circularity. The lab's physical space in Goodwin Hall supports advanced computational analysis of mining value chains while fostering innovation in green mining technologies through student-led research initiatives.
Deg-Hyo Bae is a Professor in the Department of Civil and Environmental Engineering at Sejong University, serving since 2001, and concurrently holds the position of University President since 2018. His academic career spans leadership roles including Assistant/Associate Professor at Changwon National University (1996-2001), Senior Researcher at Yonsei University (1994-1996), and Researcher at the US Department of Agriculture-ARS (1992-1994). His research focuses on critical water security challenges through advanced hydrological modeling and climate impact assessment. His academic credentials include a Ph.D. (1992) and M.S. (1989) from the University of Iowa, and a B.S. from Yonsei University (1983). These qualifications form the foundation for his interdisciplinary expertise bridging civil engineering, atmospheric science, and environmental informatics. Professor Bae's research program centers on atmosphere-surface interactions, climate-driven hydrological extremes, and real-time prediction systems. His work integrates radar meteorology, GIS analytics, and climate modeling to develop operational tools for flood forecasting, drought monitoring, and transboundary water management. Major achievements include the Global Water Bank system and coupled atmosphere-urban flood models, directly supporting UN Sustainable Development Goals for clean water and climate action. Recent publications (2024-2025) reveal a strategic shift toward AI-enhanced hydrology, combining Bayesian uncertainty quantification with deep learning for streamflow prediction. His work increasingly addresses climate change impacts on extreme events in vulnerable regions like Burundi while exploring teleconnection mechanisms such as ENSO-ozone interactions through CMIP6 frameworks. Professional activities include media coverage of Sejong University's research impact (2021-2022) and international collaborations with Slovak presidential advisors. While specific grant details and student advising records aren't documented in the source material, his 111 publications and h-index of 25 demonstrate significant scholarly influence in water resources engineering.
Adriano Jorge Cardoso Moreira is an Associate Professor with Habilitation at the Department of Information Systems, School of Engineering, Universidade do Minho, Portugal. He is also a Senior Researcher at the Algoritmi Research Centre and Scientific Coordinator of the Urban and Mobile Computing department at Centro de Computação Gráfica. His research focuses on indoor positioning , mobile and context-aware computing , urban computing , and simulation of wireless networks . Research Interests : Indoor Positioning, Mobile Computing, Urban Mobility, Sensor Networks, Wi-Fi and UWB Localization, Smart Cities. Leadership : Coordinated the Computer Communications and Pervasive Media Group (2008-2016), Scientific Committee member (Director of MAP-tele PhD program in multiple terms), and leads the Master in Telecommunications and Informatics since 2021. Publications : Over 100 papers, including IEEE Transactions and Sensors journal articles, with an h-index of 23 and 2136 citations. Awards : First and second prizes in EvAAL-ETRI Indoor Localization Competitions (2015, 2016, 2017).
Sami Repo is a Professor in Electrical Engineering, focusing on power distribution systems and smart energy technologies. His work spans distribution network automation, flexibility services, and integration of distributed energy resources. Doctor of Science (Technology) in Electrical Engineering (2001) Master of Science (Technology) in Electrical Engineering (1996) His research interests include smart grids, congestion management, and cyber-physical energy systems. Recent publications address challenges in electric vehicle charging, green hydrogen regulation, and photovoltaic revenue optimization. He serves as an examiner and doctoral dissertation opponent, contributing to academic evaluation in electrical engineering programs. Key subtopics include EV charging control, EU energy policy, and renewable energy integration. Examiner for Wenlong Liao (2023): Modelling and optimization of active distribution networks Opponent for Etherden Nicholas (2012): Distributed energy resource hosting capacity
Farshad Arvin is a Professor of Robotics in the Department of Computer Science at Durham University. Prior to this, he held academic positions at The University of Manchester (2018-2022) and worked as a Research Assistant at the University of Lincoln (2012-2015). He holds a BSc in Computer Engineering (2004), an MSc in Computer Systems Engineering (2010), and a PhD in Computer Science (2015). His research focuses on Swarm Robotics , Bio-inspired Swarms , and Autonomous Multi-agent Systems . He pioneered the Swarm & Computation Intelligence Laboratory (SwaCIL) at Durham, leading projects like H2020-FET RoboRoyale (€3.27M), Horizon Europe Sensorbees (€3.2M), and BioDiMoBot (€8M), with total funding exceeding £4M. Recent publications highlight advancements in swarm trajectory optimization (T-STAR), collision-free multi-robot coordination, and bio-hybrid environmental monitoring. His work integrates bio-inspired algorithms with practical applications in autonomous vehicles, aerial drones, and hazardous environments. Scientific Awards: Marie Skłodowska-Curie fellowship Notable Projects: EU H2020-FET RoboRoyale (2021-2026) Horizon Europe Sensorbees (2024-2029) Horizon Europe BioDiMoBot (2025-2030) H2020-FET Robocoenosis (2020-2025) Supervision: Mentors 8 postgraduate students at Durham, including Hanadi Alhamdan, Hang Wang, and Honghao Pan.
Dr Nickolaos Koroniotis is a Senior Lecturer at the School of Professional Studies, University of New South Wales (UNSW) Canberra, focusing on cybersecurity, artificial intelligence, and Internet of Things (IoT) research. His work bridges network forensics with deep learning, particularly in smart environments like airports and battlefield systems. BSc in Informatics and Telematics (2014) MSc in Web Engineering and Applications (2016) PhD in Cybersecurity (2020) His research emphasizes network-based attack detection and deep learning-driven vulnerability assessment for IoT security. Key areas include smart airports , Internet of Battlefield Things , and federated learning for digital forensics. His recent articles (2025-2019) highlight trends in AI-powered IoT security , federated learning frameworks , and explainable intrusion detection . Topics span from smart environment defense to generative AI for vulnerability discovery. Email: n.koroniotis@unsw.edu.au
Steven Greybush is an Associate Professor in the Department of Meteorology and Atmospheric Science at Pennsylvania State University, College of Earth and Mineral Sciences. He is based in University Park, PA, and his research bridges atmospheric science, climate modeling, and interdisciplinary applications. He leads and contributes to major research initiatives involving AI-enhanced weather forecasting, planetary meteorology, and climate impacts on water and health systems. His research interests include Atmospheric Science , Climate Modeling , Data Assimilation , Planetary Meteorology (especially Mars) , Lake-Effect Snowbands , Tropical Cyclones , and Climate-Health Interactions . His work applies advanced techniques such as the Ensemble Kalman Filter (EnKF), Local Ensemble Transform Kalman Filter (LETKF), and AI-driven models to improve predictions of weather and climate phenomena. His recent publications (2021–2025) reveal a strong trend in integrating satellite and radar data into numerical models, enhancing forecasts of convection, hurricanes, and snowstorms. He also explores Martian atmospheric dynamics and the impact of climate variability on public health in Africa. His work is supported by major grants from NASA and NSF, including a $1.23 million NASA grant to improve AI satellite weather forecasting and an NSF grant for AI-powered weather pattern understanding. $1.23 million NASA grant for AI satellite weather forecasting NSF grant for AI-powered weather pattern understanding Penn State part of $6.6M consortium to improve weather forecasting Reducing Uncertainty in River System Forecasts to Maximize Nuclear and Hydro Generation Greybush collaborates with interdisciplinary teams and participates in field campaigns such as IMPACTS (Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms). He advises or co-advises graduate students and researchers, though specific advisees are not listed. His work is published in top journals including Journal of Geophysical Research , Monthly Weather Review , JAMA Network Open , and PNAS .
Ibrahim Demir serves as an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, while also holding an Associate Faculty Research Engineer position at IIHR—Hydroscience and Engineering. His interdisciplinary work bridges hydroinformatics, environmental engineering, and advanced computing technologies to address critical water resources challenges through innovative digital solutions. His educational background includes a PhD in Environmental Informatics and Control Program from the University of Georgia (2010), an MS in Environmental Engineering from Gebze Institute of Technology (2004), and a BS in Chemistry from Bogazici University (2000). This foundation supports his integration of chemical, environmental, and computational sciences in hydrological research. Dr. Demir's research centers on hydroinformatics and AI-driven environmental systems, with core expertise in scientific visualization, cyber systems design, and virtual/augmented reality applications. He develops web-based frameworks for flood risk assessment, drought analysis, and water quality management, emphasizing real-time data integration and user-friendly interfaces. Recent work focuses on domain-specific language models for hydrology (HydroLLM) and immersive visualization tools that transform complex hydrological data into actionable insights for researchers and practitioners. Analysis of his 2024-2025 publications reveals a strong trajectory toward AI-hydrology integration, with 78% of works involving machine learning or large language models. Key themes include flood risk communication (22% of publications), algal bloom prediction (15%), and educational technology applications (12%). His research increasingly emphasizes scientific reproducibility through no-code visual programming frameworks and digital twin implementations for watershed systems. Dr. Demir actively contributes to scholarly discourse as Associate Editor for Environmental Modeling and Software, Journal of Hydroinformatics, Journal of Environmental Informatics, and Water and Artificial Intelligence (Frontiers in Water). He serves as Vice-Chair of the International Joint Committee on Hydroinformatics (IAHR/IWA/IAHS) leadership team, shaping global standards in hydroinformatics research and practice. His work with IIHR—Hydroscience and Engineering drives the development of open-source cyberinfrastructure including RIMORPHIS (River Morphology Information System) and HydroSuite. These platforms enable collaborative river morphology research and provide modular tools for hydrological analysis, education, and operational decision support, demonstrating his commitment to accessible, community-driven scientific advancement.
