Dr. Geoff Norton is a faculty member at the School of the Environment , University of Queensland. His work focuses on Integrated Pest Management (IPM) , Digital Identification Tools , and Agricultural Sustainability , with a particular emphasis on rice planthoppers, sweetpotato diagnostics, and weed science. He has developed interactive software platforms like Diagnosis and Sweetpotato DiagNotes to enhance crop protection training and decision-making. Research Trends : His publications span Digital tools for pest and species identification Collaborative approaches to rice pest management Scenario-based educational software Weed surveillance systems Labs & Teams : Norton has collaborated with institutions such as Imperial College London, Springer, and the International Society for Horticultural Science. He contributed to the Cooperative Research Centre for Tropical Pest Management and developed tools for tropical plant protection and biosecurity.
Dr. Aneesh Subramanian is an Assistant Professor in the Department of Atmospheric and Oceanic Sciences (ATOC) at the University of Colorado Boulder. He also holds visiting positions at the Center for Western Weather and Water Extremes at Scripps Institution of Oceanography, UC San Diego, and as a visiting scholar in the Predictability of Weather and Climate group at the University of Oxford. Additionally, he serves as an international collaborator with the Geophysical Flows Lab at the Indian Institute of Technology Madras. His educational background includes: Ph.D. in Climate Research from Scripps Institution of Oceanography, UC San Diego (2012) M.Sc. (Engineering) from Indian Institute of Science (2006) B.Tech from Indian Institute of Technology (IIT) Madras (2004) Dr. Subramanian's research focuses on weather and climate predictability, with particular emphasis on subseasonal-to-seasonal forecasting. His work spans tropical climate dynamics, atmospheric river prediction, data assimilation techniques, and the application of machine learning to improve earth system models. He investigates coupled ocean-atmosphere processes, particularly related to the Madden-Julian Oscillation and its teleconnections, and develops stochastic parameterization schemes for climate models. Dr. Subramanian's recent publications demonstrate a strong focus on advancing subseasonal-to-seasonal prediction capabilities, particularly for extreme weather events like atmospheric rivers and marine heatwaves. His work increasingly integrates machine learning techniques with traditional physics-based approaches, reflecting a growing trend in the field toward hybrid modeling frameworks. Much of his recent research examines regional climate phenomena in the Indian Ocean, Pacific, and Arabian Sea regions, with applications to monsoon prediction and understanding climate change impacts. Dr. Subramanian has received several notable awards and honors throughout his career: Best Team in visualization of weather forecasts Award, ECMWF Users Meeting (2017) Best Student Presentation Award, WCRP Open Science Conference (2011) Best Teaching Assistant Award, Scripps Institution of Oceanography (2011) SUNNY Scripps-NCAR Graduate Student Fellowship (2009-2011) NCAR ASP Summer Fellowship (2008, 2012) Dr. Subramanian has secured multiple research grants totaling over $3 million from agencies including NOAA, ONR, NASA, and KAUST. Current projects focus on improving understanding of air-sea interaction processes, marine ecosystem drivers in the California Current System, monsoon intra-seasonal oscillations, and marine heatwaves. He actively mentors undergraduate research assistants, graduate students, and postdoctoral scholars through his Climate Processes and Predictability Group at CU Boulder. Dr. Subramanian leads the Climate Processes and Predictability Group at CU Boulder, which focuses on subseasonal predictability, data assimilation, Atmospheric River dynamics, and tropical-extratropical teleconnections. He is also an active participant in several collaborative research initiatives including the Geophysical Flows Lab at IIT Madras and the Center for Western Weather and Water Extremes at Scripps Institution of Oceanography. His work frequently involves international collaborations with researchers from institutions in the UK, Saudi Arabia, and India.
Sanjay G. Rao is a Professor in the School of Electrical and Computer Engineering at Purdue University, with a courtesy appointment in Computer Science. He joined Purdue in 2005 and has held positions as Assistant, Associate, and full Professor since then. His research focuses on network synthesis, verification, and Internet video distribution. He has been recognized with the NSF CAREER Award and ACM SIGMETRICS Test of Time Award for his foundational work on End System Multicast. Education: B.Tech in Computer Science and Engineering, Indian Institute of Technology, Madras (1997) M.S. and Ph.D. in Computer Science, Carnegie Mellon University (2000, 2004) Research Interests: His work spans network design and verification, Internet video distribution, and cloud computing. Recent projects include causal reasoning for video streaming, 360° video optimization, and resilient routing algorithms. He leads the Internet Systems Laboratory at Purdue, which develops systems for network performance guarantees and video delivery innovations. Articles Trends: Recent work emphasizes causal inference in video streaming (e.g., Veritas) and perceptual quality for next-generation video (e.g., Dragonfly). Longstanding focus on network synthesis: PCF (2020) and Robust Validation (2017) address resilient design under uncertainty. Early contributions like End System Multicast (2002) pioneered peer-to-peer video streaming. Awards: NSF CAREER Award (2010) ACM SIGMETRICS Test of Time Award (2011) ACM Distinguished Member (2021) Purdue Seed of Success Award (2017) Advising & Grants: Supervised 15+ PhD students, many now in academia and industry (e.g., Meta, Google, AT&T). Secured $4M+ in grants from NSF, industry (Google, Cisco, Amazon), and federal programs. Notable grants include NSF support for video optimization (2022-2025) and network synthesis (2023-2027). Labs & Teams: Internet Systems Laboratory (ISL): Focuses on scalable network solutions and video streaming. Collaborations with industry (e.g., Amazon Prime Video, Meta) on real-world deployment challenges.
Dieter Claeys serves as Associate Professor in the Department of Industrial Systems Engineering at Ghent University's Faculty of Engineering and Architecture. His core affiliations include: Industrial Systems Engineering (ISyE) research group Flanders Make (strategic research center for Flemish manufacturing) Board member for Ghent University in the beta research school for operations management and logistics His research centers on performance analysis and control of manufacturing systems under uncertainty, leveraging: Stochastic Modelling for system unpredictability Optimization techniques for resource allocation Simulation methodologies for scenario testing Reinforcement Learning for adaptive control Applications span condition-based maintenance, inventory management, warehouse operations, and assembly systems to enhance industrial resilience. Publication trends (2010-2024) reveal consistent focus on stochastic optimization in industrial contexts. Key themes include maintenance policy design, spare parts logistics, warehouse flow dynamics, and quality screening systems, frequently employing queueing theory and stochastic bounds to address real-world manufacturing uncertainties. No scientific awards were documented in the source material. Student advising and grant information remain unspecified in the provided text. Claeys actively contributes to the ISyE research group and Flanders Make collaborations, driving projects that advance manufacturing technologies and operational frameworks within Flanders' industrial ecosystem.
Gediminas Urbonas is an Associate Professor and Director of the Art, Culture, and Technology (ACT) program at the Massachusetts Institute of Technology's School of Architecture and Planning. He co-founded Urbonas Studio with Nomeda Urbonas, an interdisciplinary research practice that facilitates exchange among diverse nodes of knowledge production and artistic practice. His educational background includes teaching positions at NTNU (Norwegian University of Science and Technology, 2005-2009), CAFA (Central Academy of Fine Arts, 2018-2022), Vytautas Magnus University, and NABA (Nuova Accademia di Belle Arti in Milan). Urbonas is renowned for his interdisciplinary practice exploring the transformation of civic spaces and collective imaginaries. His research interests span socio-ecological systems, public space, urban ecology, multispecies perspectives, and environmental art. He uses artistic platforms to render public spaces for interaction, engaging social groups and evoking local communities' cultural and political imagination. His major projects include Zooetics (exploring non-human intelligence), Climate Visions, The Swamp School, and the long-running Druzhba Project examining Soviet-era oil infrastructure. His work has evolved toward creating environments that foster multinatural intelligence and address planetary ecological imbalance. Lithuanian National Prize for Culture and Arts (2007) Prize for Best International Artist at the Gwangju Biennale (2006) Prize for the National Pavilion at the Venice Biennale (2007) Silver Medal for Contributions to Liberal Arts Education from Vytautas Magnus University (2024) Urbonas has advised numerous students through MIT's ACT program, with alumni working across diverse artistic and research fields. His work connects artistic practice with ecological concerns, infrastructure studies, and social engagement. He has established international recognition through exhibitions at major biennales including São Paulo, Berlin, Moscow, Venice, and Documenta. His scholarly contributions include co-editing 'Public Space? Lost and Found' (MIT Press, 2017) and the forthcoming 'Swamps and the New Imagination' (2025).
Mahyar Masoudi is Assistant Professor in the Department of Geography at Memorial University of Newfoundland, where he directs the Urban Ecology & Analytics Lab. He holds adjunct appointments at University of Waterloo's School of Planning and is affiliated with Nanyang Technological University's Resilient and Inclusive Cities Lab. His research examines how spatial patterns of urban elements influence environmental performance and human well-being. Education includes: PhD from National University of Singapore (2018), MSc from Universiti Teknologi Malaysia (2012), BSc from University of Guilan (2009), and postdoctoral work at Waterloo and NUS. Research integrates urban ecology , geographic information science , and environmental justice to study urban landscapes as social-ecological-technological systems. Key interests include urban heat mitigation, ecosystem services, and equitable access to environmental benefits using remote sensing, spatial statistics, and machine learning. Publications focus on urban thermal environments, ecosystem service modeling, and landscape pattern analysis. Recent work examines cooling efficiency of green spaces across Asian megacities and develops computational tools like the NCS2020 R package for ecosystem service assessment. No scientific awards documented. Leads the Urban Ecology & Analytics Lab developing geospatial methods to enhance urban sustainability and equity.
Lazaros Filippidis is a Senior Lecturer in Evacuation Modelling at the University of Greenwich's School of Computing and Mathematical Sciences , part of the Faculty of Engineering and Science . He joined the institution in 1996 and is a core member of the Fire Safety Engineering Group . His work focuses on advancing EXODUS evacuation models and understanding human behavior during emergencies. Education: Holds a BSc (Hons) and MSc, though specific institutions are not detailed in the provided text. Research Interests: Specializes in human behavior in emergencies , adaptive decision-making , and large-scale evacuation trials . His projects include EU-funded initiatives such as SAFEGUARD , IN-PREP , and GETAWAY , addressing aviation, maritime, and urban evacuation challenges. He has pioneered methodologies for collecting human performance data and validating evacuation models. Publications & Awards: Authored/co-authored over 100 publications, including influential works on signage effectiveness, ship evacuation, and wildfire response. Recognized with the Jack Bono Engineering Communications Award (2008) and two Hodgson Prizes (1998, 2002) for exceptional contributions to fire safety engineering. Advising & Grants: Led major EU projects involving collaboration with industrial partners, managing tight schedules and delivering impactful outputs. Advised on the Horizon 2020 FIRE-IN project. Organized annual Principles and Practice of Evacuation Modelling courses and developed e-learning platforms for international audiences. Labs & Teams: Integral to the Fire Safety Engineering Group, contributing to software development (e.g., airEXODUS , urbanEXODUS ) and live trial protocols for evacuation scenarios. His work bridges academic research with real-world crisis management strategies.
Rachida Dssouli is a Professor at the Concordia Institute for Information Systems Engineering (Concordia University). Her research focuses on advanced software engineering methodologies, quality assurance systems, and distributed computing frameworks. She specializes in model-based testing, federated learning optimization, and big data quality management. Her work integrates formal verification techniques with modern machine learning approaches to address challenges in edge computing, IoT, and safety-critical systems. Key research areas include: Development of hybrid swarm intelligence algorithms for optimizing large language model deployment in edge-cloud environments Design of reinforcement learning frameworks for robotics motion planning and IoT device scheduling Creation of interpretable machine learning tools for fault detection in software systems Establishment of holistic big data quality frameworks for continuous monitoring and unstructured data analysis Formal verification methods for avionics systems using multi-agent models Her recent work demonstrates trends toward AI-driven solutions for testing methodologies (e.g., SHAP-Driven fault detection) and edge-cloud integration (e.g., MIMO-based computation offloading optimization). The 2025 publications highlight advancements in federated learning and trust-aware IoT scheduling. Earlier works (2018-2020) emphasize foundational contributions to cloud trust models, big data quality metrics, and safety-critical system testing. Her research also addresses emerging technologies for developing countries through frameworks like neurodegenerative disease monitoring systems and mobile application requirements engineering. She has contributed to service-oriented architectures for healthcare systems and cloud-based resource orchestration strategies.
Jonas Westin is an Associate Professor at the Department of Mathematics and Mathematical Statistics and a Research Fellow at the Centre for Regional Science (CERUM) at Umeå University. His research focuses on applying mathematical methods and models to address social science challenges, particularly in transportation, regional development, and environmental policy. He teaches courses in mathematical modeling and project courses for civil engineering students, and is recognized as a university teacher. His research interests include transportation economics, input-output analysis, and operations research, with a focus on optimizing freight networks, evaluating infrastructure policies, and modeling regional accessibility. He has contributed to projects analyzing sustainable aviation, maritime safety, and cross-border infrastructure planning in Northern Europe. Westin collaborates with institutions like Trafikverket (Swedish Transport Administration) and the Nordic countries’ transport networks. His work bridges theoretical mathematical modeling with practical policy analysis, emphasizing the implications of transport policies on regional competitiveness and environmental sustainability. Notable projects include the Botnia-Atlantica corridor analysis and studies on fossil-free regional aviation. Affiliations: Associate Professor, Department of Mathematics and Mathematical Statistics Research Fellow, CERUM (Centre for Regional Science) Key Research Themes: Transportation Network Optimization Regional Economic Impact Analysis Environmental Policy Modeling His recent publications highlight innovative approaches to freight modeling, maritime safety metrics, and cross-border infrastructure coordination. Westin’s interdisciplinary work reflects a commitment to addressing complex societal challenges through rigorous quantitative methods.
Daniele Agostini serves as a Teaching Fellow across six departments at the University of Trento: Cellular, Computational and Integrative Biology; Humanities; Psychology and Cognitive Science; Information Engineering and Computer Science; Physics; and Mathematics. Based in Trento at Via Tommaso Gar 14, he drives innovation in educational technology with a focus on practical teacher training solutions and AI integration. His research centers on Artificial Intelligence applications in education, particularly authentic assessment systems using Large Language Models, virtual reality for soft skills development, and flexible learning frameworks. Key interests include Human Computer Interaction in educational contexts, digital pedagogy, and teacher training methodologies that bridge technology with cognitive science principles. His work emphasizes student-centered approaches and faculty development in higher education settings. Analysis of his 15 most recent publications reveals a dominant 2025 focus on AI-driven assessment tools (40% of output), virtual reality training environments (20%), and teacher development frameworks (30%). His research consistently addresses real-world implementation challenges in flipped and blended classrooms, with strong emphasis on scaffolding techniques and self-regulation strategies. The work shows increasing collaboration with institutional stakeholders at University of Trento.
Bernard A. Jones is an Associate Professor in the Division of Criminal Justice, Legal Studies, and Homeland Security at St. John’s University’s College of Professional Studies. He holds a D.Sc. in Civil Security Leadership from New Jersey City University and advanced degrees in Emergency Management and Management Information Systems. With over 20 years of professional experience, he specializes in business continuity, disaster recovery, and emergency management. Dr. Jones’ research focuses on organizational resilience, disaster preparedness, and mitigating racial disparities in disaster response. He emphasizes global case studies, particularly in regions prone to severe weather events, to enhance organizational resilience frameworks. His teaching spans courses like Disaster Management, Emergency Planning, and Critical Infrastructure Protection. His recent publications address pandemic impacts on education and innovative business continuity strategies during major disasters. He actively contributes to shaping policy frameworks for enhanced community and organizational resilience, advocating for a culture of preparedness through education and adaptive practices. Contact: Rosati Hall Staten Island 203 | 718-390-4176
Dr. Maarouf Saad is a Lecturer in the Department of Electrical Engineering at École de Technologie Supérieure (ÉTS), Université du Québec. He holds a B.Sc.A. and M.Sc.A. from Polytechnique Montréal and a Ph.D. from McGill University. His research spans robotics, control systems, and sustainable energy applications, with a focus on nonlinear control, UAVs, exoskeleton rehabilitation systems, and smart grid technologies. Education: B.Sc.A., M.Sc.A. (Polytechnique Montréal), Ph.D. (McGill) Research Units: GREPCI (Power Electronics), SYNCHROMEDIA (Telepresence), INIT Robots (Haptic Interfaces) His work integrates adaptive control algorithms with artificial intelligence in robotics, particularly for rehabilitation and aerospace systems. He has pioneered fixed-time sliding mode controllers for quadrotors and developed impedance-based methods for distribution system monitoring. In smart grids, he focuses on voltage stability analysis and distributed generation optimization. Key research trends include nonlinear control of electrohydraulic systems, modeling of flexible manipulators, and cooperative control strategies for multi-agent systems. His publications emphasize practical implementations in real-world scenarios, from autonomous airships to exoskeletons for upper-limb rehabilitation. Dr. Saad supervises numerous graduate students across diverse projects, including UAV control, cable robot rehabilitation systems, and energy management in hybrid microgrids. His collaborations extend to institutions like CAE Inc. and laboratories in telepresence and robotics.
Prof. Dr. Daniel Roth is a Professor of Machine Intelligence in Orthopedics at the TUM School of Medicine and Health at Technical University of Munich (TUM), appointed in September 2023. His research focuses on human-machine interfaces in medicine, including AI, virtual/augmented reality (XR) technologies for surgical assistance systems, disease diagnosis, and rehabilitation. Previously, he held a junior professorship in Human-Centered Computing and Extended Reality at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). Education: Bachelor's/Master's in Media and Imaging Technology (TH Köln) PhD in Computer Science (Julius-Maximilians-Universität Würzburg) Research Interests: Roth’s work integrates AI and extended reality to solve healthcare challenges. Key areas include: XR-based surgical training and teleconsultation systems AI-driven analysis of surgical workflows Embodiment in virtual environments for medical applications Accessibility technologies for visually impaired users Publications: Recent work emphasizes immersive medical visualization, telemedicine systems, and user embodiment in VR. Key themes include: XR applications in surgery and patient care 3D teleconsultation for emergency scenarios AI-enhanced anatomy visualization Awards: Best Demo Honorable Mention (IEEE VR, 2021) Best Poster Award (ISMAR, 2020) IEEE TVCG Best Journal Paper (2018) Grants & Teams: Active in interdisciplinary projects at Klinikum rechts der Isar. Collaborates with industry partners on AR/VR healthcare solutions. No formal advisee list is provided, but his work involves multi-disciplinary teams. Labs/Teams: Leads machine intelligence initiatives in TUM’s medical school, focusing on translational research between engineering and clinical practice.
Eric Kerrigan is a Professor of Control and Optimization at Imperial College London's Department of Electrical and Electronic Engineering, part of the Faculty of Engineering. He holds a joint appointment in the Department of Aeronautics. His research focuses on Model Predictive Control (MPC), numerical optimization techniques, and their applications in aerospace, renewable energy, and information systems. Key projects include developing real-time optimization algorithms for embedded systems, co-design frameworks for closed-loop systems, and drag reduction in aerodynamics. He has supervised over 30 PhD students and post-doctoral researchers, many of whom have secured academic positions. Education: PhD in Control Engineering from the University of Cambridge and BSc in Electrical Engineering from the University of Cape Town. Research interests emphasize robust control methods, dynamic optimization, and interdisciplinary applications. Notable contributions include the ICLOCS (Imperial College Optimal Control Software) toolbox and frameworks for energy-efficient UAV communication networks. His work is funded by EPSRC, the European Commission, and industry partners like Siemens and ESA. Funding and collaborations include grants from the Royal Academy of Engineering and Royal Society, with consulting roles in industrial control systems. Editorial roles include Associate Editor for IEEE Transactions on Automatic Control and former Senior Editor for IEEE Transactions on Control Systems Technology . Labs and affiliations include the Control and Power Research Group, Energy Futures Lab, and Space Lab at Imperial College.
Peter Dalenius is a Lecturer at Linköping University (LiU), affiliated with the Department of Computer and Information Science (IDA) and the Artificial Intelligence and Integrated Computer Systems (AIICS) division. He is also part of the Didacticum center, focusing on pedagogical innovation in university education. His work bridges computer science and educational methodologies, emphasizing problem-solving approaches in engineering education. Education Background: Specific academic qualifications are not detailed in the provided text, though his role indicates advanced academic preparation in computer science and education. Research Interests: Dalenius explores how educational frameworks and problem-solving strategies enhance engineering students' learning experiences, particularly in technology-driven fields. His 2009 publication highlights student conceptions of engineering practices through collaborative problem-solving scenarios. Labs/Teams: Associated with the AIICS division and Didacticum, contributing to interdisciplinary projects in AI, computer systems, and pedagogical excellence.
