Ikjot Saini is a Professor at the University of Windsor’s Faculty of Engineering, co-leading the SHIELD Automotive Cybersecurity Centre of Excellence, Canada’s first organization addressing threats in connected transportation. Her research focuses on automotive cybersecurity, vehicular networks, and privacy-preserving technologies. She has supervised doctoral students Shiva Nejati and Kunj Dhonde, and contributed to courses in the University’s Continuing Education program, specializing in cybersecurity education for professionals. Her work includes pioneering studies on blockchain-based security for connected autonomous vehicles (CAVs), machine learning-driven intrusion detection systems, and privacy-enhancing mechanisms like pseudonym-changing strategies. She has been recognized with the K.W. Michael Siu Award from the APMA Institute for Automotive Cybersecurity (2020). Saini’s research bridges theoretical advancements with real-world applications, ensuring vehicles and infrastructure remain secure against evolving cyber threats. Her contributions span academic publications, industry partnerships, and policy recommendations, positioning her as a leader in vehicular cybersecurity. Ongoing projects emphasize eco-efficiency in cybersecurity solutions and adversarial modeling for privacy evaluation.
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.
Professor Hing-Ho Tsang is the Chair in Civil and Structural Engineering at the University of Dundee, with over a decade of academic experience in Australia and Hong Kong. His research focuses on advancing sustainable infrastructure solutions, earthquake resilience, and green technologies to enhance building and infrastructure safety against natural disasters. He holds a Chartered Professional Engineer (CPEng) certification and advises governments and industries on building codes and seismic design guidelines. Tsang chairs the Global Network for Geotechnical Seismic Isolation (GSI) and serves as the Australian National Delegate to the International Association for Earthquake Engineering (IAEE). His expertise spans geotechnical seismic isolation, recycled materials in construction, and structural dynamics, contributing to UN Sustainable Development Goals (SDGs) like resilient infrastructure, circular economy, and climate action. With over 200 publications and a career-long impact ranking in Civil Engineering, Tsang has received prestigious awards including the R W Chapman Medal and Research Impact Award. Research Focus: Seismic design, sustainable construction, bio-inspired materials, and geotechnical isolation systems. Awards: Top Cited Article (2021–2022), Teaching Excellence Award (2022), and multiple international recognitions. Leadership Roles: Editorial board member for Geosynthetics International , organizer of the 18th World Conference on Earthquake Engineering technical session. His work emphasizes equity-driven engineering solutions, fostering inclusive and disaster-resilient communities. Current projects include innovative modular building systems and AI-driven seismic response models.
Andreas Grothey is a Senior Lecturer in the School of Mathematics at The University of Edinburgh, a position he has held since 2011. He completed his MSc in Numerical Algebra and Mathematical Computing at the University of Dundee (1995) and his PhD in Optimization at the University of Edinburgh (2001), supervised by Ken McKinnon. His research focuses on stochastic programming, interior point methods, decomposition approaches, high-performance computing, and energy systems optimization. He has contributed to energy planning, power grid reliability, and emergency response strategies for power networks. Grothey has advised seven PhD students, including work on unit commitment, top-percentile traffic routing, and power flow optimization. His projects include the OOPS solver, CESI energy integration center, and the Structured Modelling Language (SML). Recent work addresses pandemic policy optimization and exascale computational challenges. Education: MSc in Numerical Algebra and Mathematical Computing (University of Dundee, 1995) PhD in Optimization (University of Edinburgh, 2001) Research Interests: Stochastic Programming Interior Point Methods Decomposition Methods High-Performance Computing Energy Systems Optimization Advising & Projects: PhD Supervision (7 students, 2007–2022) OOPS Parallel Solver Development CESI Energy Systems Integration SML Structured Modelling Language Labs/Teams: Member of the Edinburgh Research Group on Optimization, leading projects in power grid stability and energy planning.
Glaucio H. Paulino holds the Margareta Engman Augustine Professorship in Civil and Environmental Engineering at Princeton University, where he also serves as a Professor at the Princeton Institute for the Science and Technology of Materials (PRISM). His work bridges computational mechanics, topology optimization, and materials science. Paulino leads a research group focused on advancing structural design methodologies, fracture mechanics, and functionally graded materials. His team has pioneered polygonal finite elements and multiresolution topology optimization techniques, addressing challenges in mesh bias and computational efficiency. He has published over 240 peer-reviewed articles and mentored 19 PhD and 11 MS students. Notable contributions include the PPR cohesive model for fracture analysis and adaptive mesh refinement for dynamic simulations. Paulino's research extends to practical applications such as high-rise building design and sustainable construction materials. Awards include election to the European Academy of Sciences and Arts and ASME’s Melville Medal. Current projects involve functionally graded cement-based materials, extrusion processing, and digital image correlation for material characterization. His lab collaborates with industry partners like Skidmore, Owings & Merrill LLP to translate topology optimization into real-world engineering solutions. Paulino’s interdisciplinary approach integrates computational modeling with experimental validation, fostering innovations in civil infrastructure resilience.
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 .
Francine Battaglia is a Professor and Chair of the Department of Mechanical and Aerospace Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. She directs the Advanced Simulations for Computing ENergy Transport (ASCENT) Laboratory. Her research focuses on computational fluid dynamics (CFD) applications in building energy systems, renewable energy, turbulent multiphase flows, and combustion. She holds a PhD in Mechanical Engineering from Pennsylvania State University (1997), and MS/BS degrees from SUNY Buffalo (1992, 1991). Research interests include CFD modeling for HVAC optimization, natural ventilation design, pathogen dispersion mitigation, and biomimetic aerodynamics inspired by insect flight. Her work bridges engineering, biology, and environmental science, addressing challenges in energy efficiency, public health, and sustainable architecture. Key contributions include developing predictive models for hydroplaning safety, solar chimney systems, and microbial fuel cells. She has received accolades such as the ASME Fellow distinction (2009), MAC Academic Leadership Fellowship (2019-2020), and Virginia Tech’s Teaching Excellence Award (2016). Her articles span CFD advancements in fluidization, combustion, and ventilation strategies, emphasizing practical applications in energy systems and public health. The ASCENT Lab collaborates on adaptive HVAC technologies and eco-friendly building designs, reflecting her dedication to interdisciplinary innovation. Awards: MAC Leadership Fellow, ASTFE Fellow, ASME Dedicated Service Award Education: PhD (Penn State), MS/BS (SUNY Buffalo) Labs: ASCENT Lab (focusing on CFD and energy transport)
Emanuele Naboni is an Associate Professor in the Department of Engineering and Architecture at the University of Parma, Italy. He teaches in the Second Cycle Degree program in Architecture and City Sustainability, offering courses such as Architectural Technologies for the Built Environment , Environmental and Outdoor Comfort Assessment , and Innovative Technologies for Sustainable Design from academic year 2019/2020 through 2025/2026. His research focuses on sustainable and climate-responsive architecture, with particular emphasis on urban microclimates, passive design strategies, and building performance optimization in Mediterranean environments. Key areas include facade engineering, thermal comfort, and computational simulation of localized climate impacts. The recent publications (2024–2025) highlight a strong trend in climate change adaptation through architectural and urban interventions. Topics span from simulating hyperlocal temperature variations to optimizing courtyard microclimates using evaporative cooling and adaptive shading, as well as retrofitting modernist urban forms for improved climate resilience. These works reflect interdisciplinary engagement with urban climatology, building physics, and environmental design. Scientific Awards: No awards mentioned in the provided text. Prof. Naboni is actively engaged in teaching and research. There is no mention of formal advising roles, grants, or leadership in labs or research teams within the available information. His scholarly output demonstrates consistent collaboration with researchers such as Marcello Turrini, Barbara Gherri, Carlos Alberto Rivera Gómez, and Carmen Galán-Marín. He contributes to advancing sustainable design practices through empirical and simulation-based studies, particularly focused on urban and architectural responses to climate change in Southern Europe.
Agustín Zaballos Diego is an Assistant Professor in the Department of Computer Engineering at University Ramon Llull (URL), Barcelona, Spain, since 1999. He serves as Research Coordinator in the Department of Engineering at La Salle Campus Barcelona and leads the R&D Networking and Security Area since 2002. His academic background includes a PhD in Data Networks and Internet Technologies (2012), an International MBA (2014), and an M.S. in Electronic Engineering (2000). University: University Ramon Llull (URL) Department: Department of Computer Engineering Research Group: GRITS Research Focus: Real-time QoS-aware routing protocols in Smart Grids, Ubiquitous Sensor Networks, and IoT communications. His work bridges telecommunications, computer science, and energy systems through projects like OPERA (FP6), INTEGRIS (FP7), and FINESCE (FP7). Publication Trends: Recent articles highlight advancements in HF communications for Antarctic research, hybrid genetic algorithms for traffic engineering, IPv6 testing, and Industry 4.0-related networking solutions. Keywords span Smart Grids, IoT, Sensor Networks, and QoS optimization. Collaborative Projects: Key initiatives include the Antarctica Project , ATHIKA (ICT in healthcare), ENVISERA (environmental sensor networks), HOTSUP (online teaching innovation), PLANET4 (AI/ML in industry), and XIoT (IoT scalability challenges).
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Jake M. Yang is a Lecturer in Physical Chemistry at the School of Chemistry, University of Leicester, where he leads an interdisciplinary research group focused on electrochemistry and sustainable material processing. He holds a DPhil and MChem from the University of Oxford and was awarded an EPSRC Doctoral Prize in 2020 for developing electrochemical sensors to monitor oceanic 'blue carbon'. His research integrates operando electrochemistry with spectroscopic and fluorescent imaging to investigate chemical reactions at electrode interfaces and their environmental applications. He is particularly known for pioneering green recycling methods for lithium-ion batteries and fuel cell membranes. Electroanalysis and Sensor Instrumentation Operando opto/spectro-electrochemical instrumentation Recycling of Technological Critical Materials Monitoring Microplastics and Ocean Ecosystems Fundamental electrochemistry Finite difference simulations The recent publications highlight a strong trend toward sustainability-driven electrochemistry, with a focus on recycling technologies using ultrasound and vegetable oil nanoemulsions. These works bridge fundamental science with industrial applications, particularly in the circular economy of electronics and energy systems. Award Highlights: EPSRC Doctoral Prize Award RSC Horizon Prize 2024 (Faraday Institute ReLIB project) University of Leicester Chemistry Image of Research Competition, 1st Prize Jake actively mentors students and offers funded PhD opportunities. His work is supported by institutional and industry-aligned grants, particularly in sustainable battery and fuel cell recycling. He collaborates across disciplines, including Earth Sciences and engineering, and promotes knowledge transfer through public engagement and media outreach. He is a key member of the Centre for Sustainable Material Processing and leads research on techno-economic analysis of recycling processes, ensuring scientific innovation meets real-world industrial and environmental needs.
Dr. Keivan Ahmadi is an Associate Professor in the Department of Mechanical Engineering at the University of Victoria (UVic), serving as Graduate Program Director. He holds a PhD from the University of Waterloo (2012), followed by postdoctoral positions at UBC and Pratt & Whitney Canada. His research focuses on dynamics and vibrations in machining processes, robotic manufacturing, and advanced manufacturing systems. Education: BSc (Tehran Polytechnic), MSc (IUST), PhD (Waterloo) Affiliations: Dynamics and Digital Manufacturing Lab (DDML), UVic Mechanical Engineering Research interests include vibration suppression in machining, chatter prediction, robotic milling dynamics, and high-speed manufacturing systems. His work combines experimental modal analysis, Bayesian modeling, and data-driven approaches to enhance manufacturing precision and sustainability. Key projects include vibration compensation in 3D printing, dynamic modeling of robotic arms for milling, and optimization of thin-walled structure machining. Over 20 peer-reviewed articles showcase his contributions to machining stability, FRF estimation, and additive manufacturing. Advised 19 graduate students (9 alumni, 10 current) Collaborations with industries like GM, Linamar, and CanEV Labs/Teams: Leads the Dynamics and Digital Manufacturing Lab (DDML), focused on sustainable manufacturing through dynamic systems innovation. Hosts a diverse team prioritizing underrepresented groups in engineering.
Martin Berzins is a Professor of Computer Science at the University of Utah, affiliated with the School of Computing and the Scientific Computing and Imaging (SCI) Institute. His research focuses on parallel scientific computing, numerical methods for partial differential equations, and high-performance computing frameworks. He is a leading developer of the Uintah framework, a scalable simulation tool used for large-scale engineering and scientific problems. Research Interests : Parallel algorithms, adaptive mesh refinement, material point method (MPM), exascale computing, computational fluid dynamics, and performance portability. His work emphasizes scalable software solutions for complex multiscale and multiphysics simulations, with applications in environmental modeling, explosive detonation analysis, and computational mechanics. Recent articles highlight advancements in Uintah's portability to exascale systems, error estimation in MPM, and high-order numerical methods. Berzins has contributed significantly to the development of task-based parallelism strategies and heterogeneous computing optimizations. His research bridges theoretical numerical analysis with practical large-scale computational challenges. Collaborations include DOE projects on hazard analysis and exascale computing. He has pioneered the integration of runtime systems like Hedgehog with Uintah to enhance scalability on modern architectures. His work ensures computational frameworks remain viable for emerging hardware trends, emphasizing both algorithmic innovation and software engineering rigor.
Eduardo Alonso Pérez de Agreda is a faculty member at the Universitat Politècnica de Catalunya in the Departament d'Enginyeria del Terreny, Cartogràfica i Geofísica . He leads research in geotechnical engineering and rock mechanics, particularly focusing on landslides, tunneling in expansive rocks, and multiphase soil interactions. Research Highlights Analyzing soil saturation dynamics using digital imaging Modeling tunnel lining in anhydritic claystones Studying mineral precipitation impacts on infrastructure Recent Article Trends Over 15 articles (2021–2025) on landslides, tunneling, soil liquefaction, and multiphase interactions Keywords span geotechnical engineering, computational methods, rock mechanics, and material science Subfields include stress-dilatancy, material heterogeneity, swelling rocks, and landslide triggering mechanisms Awards Baker Medal (2017) Telford Gold Medal (2019) Advising Advised PhD students: G. Di Carluccio (2020), C. Alvarado (2017), M. Alvarado (2021) Co-advised: L. Tapias, Y. Salami, R. Fuentes Labs & Collaborations Active in the MSR - Mecànica del Sòls i de les Roques and GGMM - Grup de Geotècnia i Mecànica de Materials research groups Collaborated with institutions in Spain, Italy, and China
