Dr. S. Madeh Piryonesi is an Assistant Professor in the Department of Civil Engineering at Toronto Metropolitan University. Her research focuses on data analytics, infrastructure asset management, construction management, and climate-resilient infrastructure. She holds a PhD from the University of Toronto (2019), an MEng from the University of Tehran (2014), and a BSc from the University of Tehran (2012). Education PhD, University of Toronto, 2019 MEng, University of Tehran, 2014 BSc, University of Tehran, 2012 Her research interests include leveraging machine learning for infrastructure resilience, optimizing construction processes, and predictive modeling of pavement conditions. She has received notable awards such as the CSCE/CRC Best Paper Award (2019) and First Place in the LTPP Data Analysis Contest (2018). Awards CSCE/CRC Best Paper Award, 2019 First Place in LTPP Data Analysis, 2018 CNAM Best Presentation Award (3rd Place), 2019 CNAM Best Presentation Award (3rd Place), 2018 She teaches courses such as CVL742 (Project Management) and CVL320 (Strength of Materials). Her work combines data-driven methodologies with practical engineering challenges to enhance infrastructure sustainability and decision-making.
Donato Romano serves as Associate Professor at The BioRobotics Institute of Scuola Superiore Sant'Anna, Italy, where he coordinates the Bio-Robotic Ecosystems Lab and co-founded the spin-off company HUBILIFE srl. His interdisciplinary work bridges robotics, biology, and AI to develop biohybrid systems for biodiversity preservation, sustainable environmental management, and life support in extreme scenarios including space exploration. With over 90 publications and an H-index of 27 (Scopus, March 2025), he has established significant academic leadership through editorial roles across 12+ international journals. Romano's educational foundation includes advanced degrees with honors: an M.Sc. in Agriculture Science and Technologies (2014) and a PhD in BioRobotics (2018), both from Scuola Superiore Sant'Anna. His academic journey includes visiting scholar positions at Khalifa University and substantial industry-academia collaboration through HUBILIFE srl, which commercializes bioinspired devices for human daily life improvement. His research program focuses on bioinspired and biomimetic robotics with particular emphasis on animal-robot interaction, biohybrid systems, and natural intelligence. Key projects address critical global challenges: SENSORBEES develops biohybrid environmental surveillance for ecological monitoring; REGOLIFE investigates lunar soil-terrestrial organism interactions for space agriculture; and OCEAN ROBOCTO explores marine ecosystem solutions. This work demonstrates a strategic progression from fundamental behavioral studies toward applied ecological and extraterrestrial systems. Analysis of his recent publications reveals strong trends in AI-driven behavioral analysis, with deep learning increasingly applied to entomological studies and pest management. The research spans agricultural applications (precision monitoring traps, larval detection systems), ecological conservation (biodiversity surveillance), and extreme-environment adaptation (lunar regolith studies). A distinctive feature is the consistent integration of biohybrid approaches where living organisms and robotic systems create synergistic capabilities exceeding either component alone. Romano's scientific recognition includes election as Junior Fellow of the Italian Academy of Engineering and Technology (2025), the Lucani fuori dal Comune award (2024), and multiple best-thesis prizes. His editorial leadership spans high-impact journals including IEEE Transactions on Medical Robotics and Bionics and Pest Management Science, where he serves as Associate Editor. As principal investigator, Romano coordinates major international projects totaling over €15M in funding: HORIZON-EIC's SENSORBEES (2024-2029), ASI's REGOLIFE (2024-2027), National Geographic's OCEAN ROBOCTO (2024-2026), and PRIN's COSMIC (2023-2025). His teaching portfolio includes PhD courses in Biosystems for Biorobotics and M.Sc. instruction in Bionics Engineering at Scuola Superiore Sant'Anna and University of Pisa. The Bio-Robotic Ecosystems Lab under Romano's direction pioneers biohybrid technologies where living organisms and robotic systems create integrated solutions. Current initiatives include SENSORBEES' environmental monitoring swarms, REGOLIFE's moonworm colonization systems, and HUBILIFE's commercial vector-control devices. The lab maintains active collaborations with space agencies, agricultural institutes, and conservation organizations, positioning biohybrid systems as next-generation tools for planetary-scale challenges.
Ruth Reef is an Associate Professor at the School of Earth Atmosphere and Environment, Monash University. She leads the Coastal Research Group, focusing on coastal dynamics, climate change impacts, and environmental DNA applications. Her research emphasizes mangrove and coral reef ecosystems' resilience to sea level rise and human activity. She coordinates courses such as EAE3311 (Oceans and Coasts) and teaches EAE1022 (Earth, Atmosphere and Environment 2). Expertise: Coastal processes, sediment transport, climate adaptation, and ecosystem management. Projects: Includes studies on mangrove restoration in Vietnam, coastal wetland carbon fluxes, and bathymetry innovations via CoastBAT. Her work addresses UN Sustainable Development Goals related to climate action and sustainable ecosystems. Notably, she received the 2021 Award for Exceptional Educational Service to the Faculty of Science.
Dr. Swati Chandna is a Senior Lecturer at the School of Computing and Mathematical Sciences, Birkbeck, University of London. She holds an honorary position as an Honorary Lecturer in Statistics at University College London (UCL) from January 2023 to January 2026. She earned her PhD in Statistics from Imperial College London in 2013. Her research focuses on statistical modeling, network analysis, and bioinformatics, with notable contributions to stochastic networks, single-cell genomic data analysis, and complex-valued signal processing. Teaching responsibilities include modules such as Bayesian Methods, Analysing Data, Statistical Analysis, and Project Applied Statistics. She serves as Admissions Tutor for Graduate Certificate and Diploma in Statistics for Data Science and as School Ethics Lead at Birkbeck. Her work bridges theoretical statistics with practical applications in genomics, environmental modeling, and biomedical research. Dr. Chandna’s recent research explores topics like covariate-driven network estimation, stochastic modeling of genomic data, and bootstrap techniques in source separation. Her publications reflect interdisciplinary collaboration across statistics, computer science, and life sciences.
Alva L. Couch is an Associate Professor at Tufts University's School of Engineering, Department of Computer Science, with a career spanning over 30 years. His work bridges network/system administration, autonomic computing, and hydrologic data science, focusing on scalable solutions for data management and automated system administration. Education: Ph.D. in Mathematics (1988), B.S. in Architecture (1978), and B.A. in Bassoon/Contrabassoon Performance (1978). Research Interests His research centers on: Network and System Administration: Tools like SLINK, Maelstrom, and Babble for dependency analysis, cloud migration, and policy enforcement. Geo-informatics: MEDFORD metadata language and HydroShare platform for hydrologic data curation and discovery. Autonomic Computing: Promise theory, convergent operators, and closure models for self-managing systems. Recent Work Trends His 2024-2018 publications emphasize: Cloud-based hydrologic data management (AnVILMEDFORD, HydroShare) Metadata standards for interdisciplinary research Machine learning for system administration Agent-based resource sharing models Scientific Awards Liebner Teaching Award (1996) Seymour Simches Advising Award (2017) Best Paper Awards: LISA 1996, AIMS 2008, LISA 2001 LISA 2000 Best Student Paper (with Michael Gilfix) Contributions He developed key software like Peep (network auralization) and Slink (configuration management), supported by NSF grants and industry partnerships. His work with CUAHSI's Water Data Center shapes national hydrologic data infrastructure. He also advocates for science education and privacy in computing.
Simon Neill is a Professor in Physical Oceanography at Bangor University’s School of Ocean Sciences, specializing in marine renewable energy, particularly tidal and wave energy resource characterization. He leads the MSc in Marine Renewable Energy and chairs IEC Technical Specification 62600-201 on tidal energy assessment. His research spans energy resource optimization, environmental impacts, and coastal management. He has secured £multi-million grants, including the £708k NERC-funded Southeast Asia Plastics project and the £7M European Regional Development Fund Smart Efficient Energy Centre. Education: PhD in Estuarine Physics (University of Strathclyde), BEng in Civil Engineering (University of Dundee), PGCertHE (Bangor University). Research Interests: Wave-tidal interactions, marine energy grid integration, sediment dynamics, microplastic dispersal, and climate change adaptation. He is lead sediment scientist at FORCE (Fundy Ocean Research Center for Energy) and contributes to the editorial board of Renewable Energy. Grants & Projects: NERC SEAmap: Marine Plastic Pollution Mitigation (2020-2023) European Regional Development Fund SEEC (£7M, 2019-2023) INTERREG ECOSTRUCTURE: Climate-Resilient Coastal Infrastructure (£3.5M, 2017-2020) Teaching: Module organizer for Marine Renewable Energy (MSc), Ocean Modelling (Undergraduate), and RV Prince Madog cruise. External examiner for Plymouth University’s MSc Marine Renewable Energy (2018-2022). Advising: Supervises PhD students researching underwater noise impacts, remote sensing for energy resources, microplastic dispersal, and estuarine energy modeling. Labs/Teams: Collaborates with FORCE, IEC, and industry partners like Repetitive Energy Ltd and Extra Mussel. Leads multi-institutional projects on estuarine dynamics and plastic pollution.
Dr. Sharon O'Rourke is an Assistant Professor and Ad Astra Fellow at the University College Dublin (UCD) School of Biosystems and Food Engineering since 2019. Previously, she held roles at the University of Sydney and UCD's School of Agriculture and Food Science, focusing on soil science and environmental protection. She holds a BAgrSc from UCD and a PhD in Soil Nutrient Management from Queen's University Belfast. Research Interests: Her work centers on sustainable soil management, soil carbon sequestration, and environmental protection. She employs spectral techniques (e.g., mid-infrared, hyperspectral imaging) and modeling to study soil geochemistry, carbon dynamics, and climate change mitigation. Current projects include ClimateCropping (EU-wide soil carbon management), PRISM (in-field soil sensors), and CFunction (carbon-nutrient stoichiometry). Grants & Projects: Key grants include funding from Teagasc, the Department of Agriculture, and the Sustainable Energy Authority of Ireland. Notable projects include proximal soil sensing for carbon monitoring and bio-based product development via pyrolysis. Teaching: She coordinates modules such as 'Carbon & Sustainability,' 'Soil Technology,' and 'Research Skills,' emphasizing agricultural systems and climate-smart practices. Awards: Recognized as an Ad Astra Fellow, highlighting her contributions to innovative soil science research.
Prof. Can Dincer is a Professor of Sensors and Wearables for Healthcare at the TUM School of Computation, Information and Technology, Technische Universität München (TUM). His research focuses on bioanalytical materials, wearable sensors, and AI-driven diagnostics for One-Health applications, integrating disposable sensor technology with data science. He holds a doctorate from the University of Freiburg (summa cum laude, 2016) and worked as a visiting scientist at Imperial College London before joining TUM in 2024. He is a member of the Munich Institute of Biomedical Engineering (MIBE). Key research interests include: Development of wearable biosensors for real-time health monitoring CRISPR-based diagnostics for nucleic acids and proteins AI integration for therapeutic drug monitoring in sepsis and other critical conditions Environmental health connections via point-of-need diagnostics Notable achievements include the 2021 Biosensors & Bioelectronics Best Paper Award and inclusion in Stanford's World's Top 2% Scientists since 2022. His work spans clinical applications, microfluidic platforms, and nanotechnology-based solutions for healthcare challenges. Publications highlight innovations like optogenetic bioassays (Science Advances, 2024), CRISPR-powered multiplexed biosensors, and wearable systems for continuous biomarker monitoring. His research bridges material science, electrical engineering, and biomedicine to create practical diagnostic tools. Prof. Dincer collaborates across disciplines, focusing on translating lab innovations into clinical and commercial applications through advanced sensor technologies.
Gökhan Alcan is an Assistant Professor in Robotics and Machine Learning at the Automation Technology and Mechanical Engineering Unit of Tampere University, Finland. He leads the Advanced Learning, Control and AutomatioN (ALCAN) Research Group, focusing on safe model predictive control, constrained optimal control theory, reinforcement learning, and their applications to dynamical systems. His research addresses challenges in robotic manipulation, safe navigation, and human-robot collaboration through projects like the Aurora initiative on automated and connected machines. Education: B.Sc., M.Sc., and Ph.D. in Mechatronics Engineering from Sabanci University (2008–2019). Postdoctoral research at Sabanci University (2019) and Aalto University (2020–2024). Research Interests: Robotics, control theory, system identification, autonomous systems, and machine learning applied to robotic manipulation, autonomous vehicles, and safety-critical systems. Notable work includes trajectory optimization for hybrid systems, magnetic manipulation for medical applications, and sim-to-real gap analysis in cloth manipulation. Awards: Third Place in Aalto Open Science Award 2023, Elginkan Foundation Technology Award (2016), and multiple scholarships. Advised Ph.D. student David Blanco Mulero, who defended his thesis on robotic manipulation of deformable objects. Labs/Teams: ALCAN Research Group, former roles in Aalto University's Intelligent Robotics Group and Sabanci University's Control, Vision, and Robotics (CVR) Group.
Hamed Badihi is an Assistant Professor in Automation Technology and Dependable Systems at Tampere University , part of the Faculty of Engineering and Natural Sciences. He leads the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group within the Dependable Systems Cyber Laboratories . His research focuses on critical aspects of condition monitoring, fault-tolerant control, and attack-resilient control to advance sustainable, dependable cyber-physical systems. Research Interests include: Cybersecurity for industrial control systems Fault-tolerant control mechanisms Resilient control strategies for renewable energy systems Condition monitoring of wind turbines and microgrids Recent Contributions emphasize hybrid approaches combining machine learning and control theory for cyber-attack detection and system resilience in wind farms and microgrids. His work addresses challenges like real-time fault diagnosis and adaptive control under adversarial or environmental perturbations. Awards & Roles : Senior Member of IEEE, editor for International Transactions on Electrical Energy Systems , Advances in Fuzzy Systems , and Processes journals. Active in EU projects like StreamSTEP . Labs & Teams : Directs the DARES Group, collaborating on initiatives like the Dependable Systems Cyber Laboratories to pioneer innovations in cyber-physical system dependability.
Prof. Chong-Yu Xu is a Professor of Hydrology at the University of Oslo's Department of Geosciences, affiliated with the Section for Geography and Hydrology (GeoHyd). He has held this position since 2005, having previously served as an Associate Professor at Uppsala University (1998–2005) and Assistant Professor (1994–1998). His research focuses on hydrological modeling, climate change impacts, regional evapotranspiration, and uncertainty analysis. He teaches courses such as GEO4310 (Stochastic Methods in Hydrology) and GEO4320 (Hydrological Modelling). Education: BSc in Hydrology (Nanjing University, 1978–1982), MSc in Regional Hydrological Modeling (Free University Brussels, 1986–1988), and PhD in Hydrological Modelling (Free University Brussels, 1988–1992). He has been honored with prestigious awards, including the NHF Lifetime Achievement Award (2022) and IWA Publishing Award (2022). He serves as an honorary professor at institutions like Hohai University and is a doctoral supervisor at multiple universities. His research spans global, regional, and local hydrological modeling, with a focus on climate change adaptation and water resource management. He leads projects such as the NORHED-II initiative on climate change and ecosystem management in Malawi and Tanzania. His work bridges theoretical hydrology with practical applications, including flood risk reduction and hydropower optimization. Publications highlight advancements in hydrological extremes, non-stationary drought assessment, and AI-driven flood prediction. Collaborative efforts with international networks like the Nordic Hydrological Association underscore his global impact in hydrological sciences.
Helmholtz Centre for Environmental ResearchGermany
Prof. Dr. Beate Escher is Head of the Department of Cell Toxicology at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. She holds professorial positions at Eberhard Karls University of Tübingen , is a Privatdozent at ETH Zurich , and is affiliated with the University of Queensland and Griffith University in Australia. Her research program focuses on advancing in vitro bioassays and New Approach Methods (NAMs) for environmental and human health risk assessment of micropollutants. Her research interests lie at the intersection of environmental toxicology , molecular toxicology , and exposure science . She develops and applies bioanalytical tools for water quality assessment, with a focus on pharmaceuticals, pesticides, and transformation products. Her work includes mechanism-based toxicity assessment , toxicokinetic-toxicodynamic (TKTD) modeling , and the development of the CITEPro robotic bioassay platform for high-throughput screening. She integrates omics data , computational modeling , and machine learning to improve chemical hazard characterization. Recent publications highlight trends in chemical mixture toxicity , safe-by-design chemicals , ionic compound assessment , and machine learning applications in toxicology. Her work increasingly leverages data-driven approaches to prioritize contaminants and predict biological effects across species. Scientific Awards: Highly Cited Researcher (Web of Science/Clarivate, Top 0.1%, 2020) Outstanding Achievements in Environmental Science and Technology (ES&T & ACS ENVR, 2023) Advising and Grants: She supervises multiple doctoral students and leads major collaborative projects such as InCeTo, MibiTox, nanoINHALE, and SafePol. She received an Australian Research Council grant (2011–2014) and leads Swiss National Science Foundation-funded initiatives. She was a member of the German Science Council (2017–2024) and serves on the Board of Reviewing Editors of SCIENCE . Labs and Teams: She leads the Cell Toxicology team at UFZ, which includes researchers such as Dr. Luise Henneberger, Dr. Julia Huchthausen, and Dr. Haotian Wang. The team operates the CITEPro platform and contributes to international consortia focused on exposome research and chemical safety.
Maozhen Li is a Professor in the Department of Electronic and Electrical Engineering at Brunel University of London , within the College of Engineering, Design and Physical Sciences . He serves as the Vice-Dean of the NCUT Transnational Education (TNE) programme, overseeing a joint school with North China University of Technology. He has been at Brunel since 2002, progressing from Lecturer to Professor in 2013. Education: PhD, Institute of Software, Chinese Academy of Sciences (1997) Postdoctoral Research, School of Computer Science and Informatics, Cardiff University (1999–2002) His primary research interests lie in high performance computing, big data analytics, and artificial intelligence, with applications in smart grids, smart manufacturing, and cybersecurity. He focuses on developing interpretable, robust, and lightweight AI models, including work in causal AI, parallel machine learning, and edge computing. His research integrates advanced techniques such as deep learning, reinforcement learning, and blockchain for real-world system optimization. An analysis of his recent publications reveals a strong and consistent research trajectory in AI-driven solutions for environmental monitoring (e.g., PM2.5 prediction), industrial defect detection, IoT security, and intelligent transportation. His work frequently combines deep learning with graph-based modeling and federated or reinforcement learning, emphasizing scalability, efficiency, and robustness in distributed and edge environments. Scientific Awards and Recognition: Fellow of the Institution of Engineering and Technology (IET) Fellow of the British Computer Society (BCS) Shortlisted for the Computing UK BIG DATA EXCELLENCE AWARDS 2018 in the category of Most Innovative Big Data Solution Maozhen Li has successfully supervised 25 PhD students and examined over 30 PhD theses externally. He has secured significant research funding from EPSRC, the European Union (Horizon 2020), Innovate UK, and the Royal Society , with projects including Z-BRE4K, IoRL, and TDX-ASSIST. He serves as an Associate Editor for journals such as the Journal of Cloud Computing and the International Journal of Grid and High Performance Computing . Research Groups and Teams: He is affiliated with the Intelligent Engineering Frameworks (IEF) research group at Brunel, contributing to collaborative efforts in AI, IoT, and smart systems. His leadership in transnational education also fosters international research collaboration between Brunel and Chinese institutions.
Dr. Srishti Banerji is an Assistant Professor in the Department of Civil and Environmental Engineering at Utah State University and Director of the Systems, Materials, and Structural Health (SMASH) Lab. She leads research on advanced construction materials, structural resilience under extreme loads (particularly fire), sustainable infrastructure, and structural health monitoring. Her group focuses on experimental testing, numerical simulations, and developing design solutions for civil infrastructure. Education: PhD in Civil (Structural) Engineering, Michigan State University (2021) MS in Civil (Structural) Engineering, Concordia University (2016) BS in Civil Engineering, National Institute of Technology Silchar (2013) Research Focus: Her work spans: 1) Characterization of high-performance/sustainable materials (e.g., UHPC, recycled glass pozzolan), 2) Structural behavior under fire exposure, 3) Integration of electric charging systems in concrete pavements, 4) Non-destructive testing and structural health monitoring, and 5) Retrofitting techniques for infrastructure strengthening. She employs machine learning, thermo-mechanical modeling, and full-scale experimentation. Publication Trends: Her 13+ journal articles primarily analyze fire resistance of concrete/timber structures, UHPC material properties at high temperatures, sensor-based infrastructure monitoring, and sustainable material development. Recent works increasingly incorporate machine learning and electrification concepts. Awards & Honors: Teacher of the Year (USU, 2025) ASCE ExCEEd Faculty Teaching Fellowship (2023) Top Cited Article Award, Fire and Materials Journal (2023) SHMII-11 Early Career Grant (2022) NSERC Scholarship (2015) Best Conference Paper (SEC 2016) Current Projects & Teams: She leads 5+ funded projects including fire performance of polymer concrete, self-healing concrete for bridges, and Utah-sourced UHPC development. Mentees include 3 PhD students (Abdullah Al Sarfin, Mehrnoosh Nazari, Mahmoud Ali) and alumni working on sustainable materials and additive manufacturing.
Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .
