Find Academic Supervisors

Chao RenView profile

Researcher

• Quantum Federated Learning
• Federated Learning
• Quantum Computing
• +3 more

Chao Ren is a Wallenberg-NTU Presidential Principal Researcher (Forskare) at KTH Royal Institute of Technology's Department of Intelligent Systems. He holds a Ph.D. from Nanyang Technological University (NTU), Singapore, where he received the prestigious Graduate College Research Excellence Award. His research focuses on Quantum Federated Learning, Power Engineering, and Big Data Analytics for smart grid stability assessment. Ren has held postdoctoral fellowships at NTU and KTH, collaborating with leading experts like Prof. Mikael Skoglund (IEEE Fellow). Education: Ph.D. in Interdisciplinary Graduate Programme, NTU (2017–2022) B.E. in Computer Science, Nanjing University of Aeronautics and Astronautics (2013–2017) Research Interests: Combining quantum computing with federated learning to enhance cybersecurity and efficiency in power systems. Key areas include dynamic security assessment, adversarial robustness, and battery degradation prediction. His work bridges theoretical advancements and practical applications in smart grids and distributed systems. Awards & Grants: Winner of Graduate College Research Excellence Award (NTU, 2022) Wallenberg AI, Autonomous Systems & Software Program (WASP) grant (SEK 300,000) NTU grant for 'Modern Smart Grid Stability Assessment' (S$100,000) Professional Activities: Guest Lecturer at KTH, Editorial Board member for IET AI for Engineering, and reviewer for top conferences like NeurIPS and AAAI. Active in organizing workshops on federated learning and quantum computing. Labs & Teams: Leads the Trustworthy Federated Ubiquitous Learning Research Lab (AI Singapore-TrustFUL) and collaborates with the Singapore Power Group-NTU Joint Lab. Focuses on interdisciplinary projects involving energy systems, AI, and quantum technologies.

Ron WakefieldView profile

Professor

• Construction Information Technology
• Industrialization of Construction
• Simulation of Engineering Systems
• +9 more

Professor Ron Wakefield is the Dean of the School of Property, Construction and Project Management and Associate Deputy Vice Chancellor, International at RMIT University. He holds a Professorship in Construction and has held leadership roles globally, including at Virginia Polytechnic Institute and State University and UNSW Sydney. His research focuses on construction information technology, industrialization of construction, occupational health and safety, and renewable energy integration. He has received several awards, including Excellence in Scholarship (Virginia Tech, 2003) and the Certificate of Teaching Excellence (Virginia Tech, 2001). Wakefield's academic journey includes roles as Program Director for the Cooperative Research Centre’s Built Assets project and Director of Virginia Tech’s Environmental Design and Planning PhD program. His work spans industrialized building systems, safety training efficacy, and BIPV design optimization. He has supervised over 17 research projects, including studies on renewable energy adoption and blockchain in construction. Education: Graduate Research Assistant at Princeton University (1985–1987), prior to academic roles. Awards: Multiple recognitions for scholarship, teaching, and contributions to construction safety and innovation. Research Themes: BIPV systems, construction automation, and sustainable urban energy solutions. He collaborates internationally on projects like the CIB World Building Congress and advises on renewable energy transitions (e.g., Bendigo’s energy feasibility study). His recent publications address VR-based safety training, reinforcement learning for virtual power plants, and fire safety in BIPV systems.

• Intelligent monitoring and maintenance of civil infrastructure
• Optimum asset maintenance and management
• Structural reliability analysis and safe life prediction of structures and infrastructure
• +4 more

Dr. Mojtaba Mahmoodian is a Senior Lecturer in Civil and Infrastructure Engineering at RMIT University's School of Engineering, City Campus, Australia. He is a Chartered Engineer in both Civil Engineering and Asset Management with Engineers Australia. His work spans diverse infrastructure types including bridges, pipelines, railways, buildings, ports, and offshore platforms. Dr. Mahmoodian's research focuses on intelligent monitoring and maintenance of civil infrastructure, optimum asset maintenance and management, structural reliability analysis and safe life prediction of structures, and deterioration modeling of structures and infrastructures. His work integrates advanced technologies including digital twins, artificial intelligence, and machine learning to enhance infrastructure monitoring and management systems. He has developed innovative approaches for corrosion modeling, structural health monitoring, and real-time structural integrity assessment. His recent publications demonstrate a strong trend toward the integration of digital twin technology with artificial intelligence for infrastructure monitoring. The research spans civil infrastructure domains including bridges, railways, ports, and pipelines, with emphasis on real-time monitoring, predictive maintenance, and optimal sensor placement. His work shows increasing sophistication in applying machine learning techniques to accelerate finite element analysis and improve structural assessment accuracy. RMIT Vice-Chancellor's Award for Outstanding Contributions in Learning and Teaching (2019) Chartered Engineer in Civil Engineering and Asset Management (2019) Chair of special sessions at major international bridge conferences (IABMAS 2018, 2020) Conference chair for ICWSS 2017: International Conference on Water Supply Systems Kharazmi Festival Award for innovation in concrete testing (2004) Dr. Mahmoodian actively supervises Masters and PhD research students, with current projects focusing on AI-enabled health monitoring of bridge structures through digital twin technology, computer vision for damage detection, automatic condition assessments of civil infrastructure, and intelligent monitoring and maintenance systems. His research has significant practical applications for infrastructure asset management and maintenance optimization. His work involves collaboration with various research teams focusing on structural health monitoring, digital twin development, and AI applications in civil engineering. These teams work on developing innovative monitoring systems that integrate sensor networks, data analytics, and visualization tools to provide comprehensive infrastructure assessment capabilities.

Arlei SilvaView profile

Assistant Professor

• Data Science
• Network Science
• Machine Learning
• +5 more

Arlei Silva is an Assistant Professor of Computer Science at Rice University. He holds a Ph.D. from the University of California, Santa Barbara (UCSB), and M.Sc. and B.Sc. degrees from Universidade Federal de Minas Gerais, Brazil. His research focuses on data science, network science, machine learning, and graph algorithms, with applications in flood prediction, graph anomaly detection, and temporal graph analysis. He has held visiting roles at Rensselaer Polytechnic Institute and has contributed to projects like trajectory compression and network process discovery. Education: Ph.D. in Computer Science, University of California, Santa Barbara (2019) M.Sc. in Computer Science, Universidade Federal de Minas Gerais, Brazil (2011) B.Sc. in Computer Science, Universidade Federal de Minas Gerais, Brazil (2008) Research Interests: His work integrates machine learning and graph theory to address challenges in network dynamics, spatiotemporal modeling, and anomaly detection. Recent projects include FloodGNN-GRU for flood prediction, DOPPLER for dataflow optimization, and Pole for signed network embeddings. Awards: SNAKDD Best Paper Runner-up (2013) Best M.Sc. Thesis (Brazilian Computer Society, 2011) Best Undergraduate Research (top 6, Brazilian Computer Society, 2009) Labs/Teams: Engages in interdisciplinary projects at Rice, focusing on environmental informatics and network science. His GitHub repositories include work on trajectory compression, anomaly detection, and spectral algorithms for graph cuts.

Masoud BaratiView profile

Assistant Professor

• Electric Power Systems Modeling
• Quantum Computing
• Optimization and Simulation
• +8 more

Masoud Barati is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh's Swanson School of Engineering. Previously, he held similar roles at the University of Houston and Louisiana State University. He earned his PhD in Electrical Engineering from the Illinois Institute of Technology (2009-2013) and completed a postdoctoral fellowship at the University of Chicago Booth School of Business in 2014. His research bridges pure and applied mathematics with electric power systems, focusing on resilience, quantum computing, and control systems. Barati’s academic journey includes a diverse range of studies: his doctoral work at Illinois Tech focused on electrical engineering, while his postdoctoral research at the University of Chicago explored business-related systems through a computational lens. His current role at the University of Pittsburgh allows him to advance interdisciplinary research in energy systems. Research interests span algebraic geometry and category theory for computational problem-solving in power systems, alongside applied areas like optimization, quantum computing, Bayesian statistics, and deep learning. He investigates resilience in power grids under natural hazards and cyber-attacks, with specific attention to AC optimal power flow, energy justice, and multi-interdependent infrastructure management. His work integrates smart city technologies, blockchain for energy trading, and data-driven methods such as kernel regression and neural networks for real-time grid analysis. His recent publications emphasize quantum protocols for entanglement detection, smart city energy infrastructure resilience, and machine learning-augmented approaches to power system control. These trends reflect a focus on leveraging advanced computational tools to address modern energy challenges. Barati has contributed to collaborative research projects, including a global algorithm for AC-OPF optimization funded by the National Science Foundation (NSF). While no scientific awards are explicitly listed, his research portfolio demonstrates significant contributions to energy systems and quantum computing. His advisory work includes various projects on grid resilience, though formal student advisee names are not provided in the text. Grants and funding are associated with his collaborative efforts in developing scalable optimization algorithms for power systems. Research activities involve partnerships with institutions like IBMQ for quantum simulations and local case studies in Pittsburgh. He explores innovative solutions such as mobile charging stations for EVs and blockchain-based energy trading models, reflecting a commitment to both theoretical and applied advancements in energy engineering.

Robert MeraView profile

Lecturer

• Climate Science
• Atmospheric Science
• Environmental Science
• +3 more

Robert Mera is a Lecturer and Program Coordinator in the Department of Marine, Earth, and Atmospheric Sciences at North Carolina State University. His primary affiliation is with the College of Sciences. His research focuses on climate science, atmospheric processes, and environmental modeling, with notable work on climate change attribution, regional climate modeling, and climate-justice intersections. He has contributed to studies on CO2 emissions, heat extremes in California, and climate impacts on agriculture. His academic work bridges meteorological data analysis, hydrological modeling, and public health applications, such as using weather forecasts to manage meningitis in West Africa. His regional climate modeling efforts for the western U.S. and West African Sahel highlight his expertise in superensemble methodologies and climate variability. Mera's publications span climate change effects on crops, factor separation methods in climate models, and moisture dynamics in West Africa. His research emphasizes interdisciplinary approaches to address environmental challenges, including sustainability and policy implications of climate science findings.

• Analytical Chemistry
• Environmental Chemistry
• Materials Chemistry
• +9 more

Md. Abu Bakar Siddique serves as a Senior Scientific Officer at the Institute of National Analytical Research and Service (INARS), Bangladesh Council of Scientific and Industrial Research (BCSIR), currently on study leave while pursuing his Ph.D. in Chemistry at Howard University. With over a decade of research experience, he has established himself as a leading environmental chemist in Bangladesh specializing in water quality analysis, heavy metal contamination, and sustainable remediation technologies. His educational credentials include a B.Sc. (Honors) in Chemistry (2009), M.S. in Inorganic Chemistry (2011) from the University of Chittagong, and an M.Phil. in Physical and Inorganic Chemistry (2018) from Bangladesh University of Engineering and Technology (BUET). He received the Chittagong University Dean's Scholarship based on his undergraduate academic performance and maintains life memberships in the Bangladesh Chemical Society and Network of Instrument Technical Personnel and User Scientists of Bangladesh. Dr. Siddique's research spans analytical, environmental, and materials chemistry with particular focus on pressing environmental challenges in Bangladesh. His laboratory work combines traditional analytical techniques with computational approaches and machine learning to address water treatment, microplastics pollution, phytoremediation, and waste management issues. He has pioneered studies on heavy metal contamination in Bangladesh's coastal regions, river systems, and urban centers, with strong emphasis on human health implications. His extensive publication record reveals a clear trend toward interdisciplinary research that bridges environmental chemistry with data science and public health. Recent work increasingly incorporates machine learning models for pollution source identification and health risk assessment, reflecting his growing expertise in computational environmental analysis. Chittagong University Dean's Scholarship based on B.Sc. (Honors) result As a research supervisor, Dr. Siddique has jointly mentored over 30 M.S. thesis students from multiple Bangladeshi public universities. His laboratory at INARS maintains ISO/IEC 17025:2017 accreditation for water quality testing and conducts research using advanced instrumentation including Atomic Absorption Spectrometry. His current Ph.D. research at Howard University with Dr. Mirza Galib continues his focus on environmental analytical chemistry while expanding into new methodological approaches. The Inorganic Analytical Research Laboratory under his contribution has been instrumental in developing analytical protocols for environmental monitoring across Bangladesh. His work with the Bangladesh Accreditation Board as a technical assessor demonstrates his leadership in establishing national standards for analytical laboratories, further extending his impact beyond direct research contributions.

Estela Capelas BarbosaView profile

Research Fellow

• Health Economics
• Social Welfare
• Domestic Violence
• +7 more

Dr. Estela Capelas Barbosa is a health economist and researcher at the Violence and Society Centre, City, University of London. She joined the Centre in April 2021 and holds a PhD in methods for measuring unfair inequalities in the Brazilian National Health System. Her work bridges health economics, public policy, and social justice, with a focus on domestic and sexual violence. Her research interests include: Health economics and equity in healthcare systems Economic evaluation of domestic violence interventions Cost-effectiveness modelling of public health programmes Secondary data analysis using administrative datasets Measuring societal costs of violence, especially sexual violence Policy evaluation in primary care settings The recent articles reflect a strong thematic focus on the economic dimensions of violence, health system responses, and equity. Her work frequently employs secondary data and modelling techniques to assess the impact and efficiency of interventions, particularly in primary care and cross-national contexts. She has led projects evaluating IRIS and HIV screening, and is involved in international collaborations across the UK, Brazil, Nepal, Palestine, and Sri Lanka. Scientific contributions and projects include: Economic component of international evaluation of domestic violence responses NIHR CLAHRC North Thames projects at UCL Development of methods for measuring unfair inequalities in health Secondary analysis of specialist domestic violence service data Probabilistic profiling of violence experiences Lifetime cost modelling of sexual violence Dr. Barbosa has advised on policy evaluation and contributed to health economic assessments in both the UK and Brazil. She has not supervised any named students in the provided text. She is affiliated with interdisciplinary teams working on violence prevention and has no listed scientific awards. Her research is grounded in real-world data and aims to inform equitable and cost-effective health and social policies.

Jacob Birk JensenView profile

Associate Professor

• Hydrology
• Groundwater Modeling
• Urban Hydrology
• +7 more

Jacob Birk Jensen is an External Associate Professor in the Department of Construction, Urban and Environmental Engineering at Aalborg University, Faculty of Engineering and Science, Denmark. His work bridges hydrology, environmental engineering, and stochastic modeling, with a focus on groundwater systems and urban hydrology. Department: Department of Construction, Urban and Environmental Engineering School: Faculty of Engineering and Science University: Aalborg University Position: External Associate Professor His research interests include groundwater modeling, inverse modeling, stochastic methods, eco-hydrology, and urban drainage systems. He applies reliability theory and probabilistic modeling to assess hydrological risks and environmental impacts, particularly in groundwater-dependent ecosystems and agricultural landscapes. The recent publications show a strong trend in integrated modeling approaches, such as coupling SWAT and MODFLOW to evaluate streamflow responses to groundwater abstraction. His work spans environmental sustainability, agricultural hydrology, and coastal engineering, reflecting a multidisciplinary approach to water resource challenges. Keywords across his research include hydrology, groundwater abstraction, eco-hydrology, reliability methods, and urban drainage. He has contributed to significant research projects including: Application of Reliability Theoretical Methods in Hydrological Simulations Eco-hydrological Modeling of Stream Valleys Impact of Rising Groundwater Tables on Agricultural Land Use Rotating Wave Energy Absorber Development Jacob Birk Jensen has advised PhD students such as O. Johansen and M. L. Fejerskov. While no formal scientific awards are listed, his publications are well-cited, particularly in the areas of groundwater abstraction and fen ecosystem responses. He has also delivered lectures at international conferences, including the International Multidisciplinary Conference on Hydrology and Ecology. His research group, the Urban Hydrology section, focuses on infrastructure, hydraulic engineering, and environmental technology, contributing to sustainable urban water management and climate resilience.

• Control Engineering
• Hydrodynamics
• Marine Control Systems
• +3 more

Asgeir Johan Sørensen is a Professor at the Department of Marine Engineering, Faculty of Engineering at NTNU. He holds a Dr. Eng. in Technical Cybernetics (1993) and an M.Sc. in Marine Engineering (1988), both from NTH (now NTNU). His research focuses on control engineering, hydrodynamics, autonomous systems, and marine robotics. He leads projects like Oppdrag Mjøsa , advancing autonomous marine operations and environmental monitoring. Key contributions include risk-based path planning, hydrogen fuel cell systems for marine propulsion, and hyperspectral imaging for underwater mapping. Research interests emphasize autonomous systems integration, underwater vehicle control, and sustainable marine technologies. He co-founded the Marine Cybernetics Laboratory (MC-lab) and Applied Underwater Laboratory (AUR-Lab) . His work bridges academia and industry, addressing challenges in marine robotics, energy systems, and satellite-based Earth observation. Recent publications highlight advancements in marine autonomy, including collision avoidance algorithms, hybrid power systems, and Arctic satellite missions. He collaborates widely, contributing to national and international initiatives in marine technology and environmental data governance.

• Flood Risk Assessment
• Drought Risk Assessment
• Hydrological Modeling
• +4 more

Dr. Mark Thyer is an Associate Professor in Civil and Environmental Engineering at the University of Adelaide, affiliated with the School of Architecture and Civil Engineering under the Faculty of Sciences, Engineering and Technology. His research focuses on enhancing hydrological, environmental, and water resource models through physical-statistical approaches. He specializes in flood/drought risk assessment, predictive uncertainty quantification, and behavioral water use modeling for urban water management. Dr. Thyer has over 17 years of research experience and is internationally recognized for his work on Bayesian approaches to quantify uncertainty in hydrological predictions. He has authored over 30 journal papers in top-tier water resources journals and secured research grants totaling over $5 million. His collaborations include institutions like CSIRO, the Australian Bureau of Meteorology, and the Goyder Institute for Water Research. Key contributions include leading the eWater CRC project to develop the Behavioral End-Use Stochastic Simulator (BESS) for household water use modeling, integrated into eWater’s Urban Developer tool. He also serves as an Associate Editor for the Australian Journal of Water Resources and reviews for top international journals and ARC grants. His recent work emphasizes seamless subseasonal streamflow forecasting, probabilistic modeling of ephemeral catchments, and smart stormwater storage systems to mitigate urban flooding. He actively engages in consultancy for water authorities, including Hunter Water Corporation and the Wimmera Mallee Pipeline Project.

Thordis Linda ThorarinsdottirView profile

Professor

• Statistics
• Data Science
• Environmental Science
• +5 more

Thordis Linda Thorarinsdottir is a Professor of Statistics and Data Science at the University of Oslo's Department of Mathematics, affiliated with the Faculty of Mathematics and Natural Sciences. She previously worked as a Chief Research Scientist and Research Leader for Climate and Environment at the Norwegian Computing Center (2006–2023). Her research focuses on developing stochastic models for environmental sciences, emphasizing uncertainty quantification and probabilistic prediction in climate, weather, and hydrology. Key areas include spatial and spatio-temporal modeling, Bayesian frameworks, and forecast evaluation. **Education**: PhD in Mathematical Statistics from Aarhus University (2006). **Research Interests**: Environmental applications in climate science, spatial modeling, probabilistic forecasting, and extreme event analysis. She collaborates with experts in meteorology, hydrology, and climate science to address data deficiencies and real-world challenges. **Projects**: Leads initiatives like CONFER (Climate Futures) and is part of the Integreat research group. Her work integrates statistical theory with environmental process understanding to enhance predictive accuracy and decision-making under uncertainty. **Awards**: Not explicitly listed, but her contributions to climate and environmental statistics are recognized internationally. **Grants & Labs**: Active in interdisciplinary collaborations, including the Norwegian Research Council-funded projects. Her team focuses on probabilistic modeling and ensemble forecasting techniques.

Gregory B. BaecherView profile

Professor

• Civil Engineering
• Environmental Engineering
• Risk and Reliability of Civil Infrastructure
• +4 more

Gregory B. Baecher is the Glenn L. Martin Institute Professor of Engineering at the University of Maryland College Park, affiliated with the Department of Civil and Environmental Engineering within the A.J. Clark School of Engineering. He holds a Ph.D. from the Massachusetts Institute of Technology (MIT). His expertise spans risk assessment, geotechnical engineering, and probabilistic methods applied to civil infrastructure resilience. Research Interests: Pioneering probabilistic approaches for infrastructure safety Geotechnical and water-resource engineering systems Resilience strategies for civil infrastructure Honors include over a dozen prestigious awards from organizations such as the National Academy of Engineering, American Society of Civil Engineers, and the U.S. Army Corps of Engineers. He has delivered distinguished lectures at leading institutions like UC Berkeley and Texas A&M. Collaborates actively with researchers in the College of Engineering. Advised at least one student: Billy Hernawan. Recognized as a Distinguished Alumni of UC Berkeley Civil Engineering and a recipient of international innovation awards.

Shasha HanView profile

Assistant Professor

• Hydrology
• Water Resources
• Flood Forecasting
• +11 more

Dr. Shasha Han is an Assistant Professor in Physical Geography (Hydrology and Water Resources) at the University of Birmingham, affiliated with the School of Geography, Earth and Environmental Sciences (GEES). She is actively engaged in research, teaching, and supervision, with a strong focus on flood forecasting, hydroclimatic extremes, and climate change impacts. PhD in Hydrology and Water Resources – McMaster University, 2019 MSc in Environmental Science – Beijing Normal University, 2014 Postgraduate Certificate in Higher Education (PGCHE) – University of Birmingham, 2024 Dr. Han's research centers on enhancing probabilistic flood forecasts, investigating flood non-stationarity, and advancing hydrological process understanding under human and natural influences. Her work spans uncertainty analysis , urban hydrology , machine learning in hydrology , and climate extremes and health . She integrates data science with physical modeling to improve flood prediction and risk assessment. Her recent publications demonstrate a consistent focus on flood modeling under climate change , urbanization impacts on river flow , and probabilistic forecasting systems . The research trends highlight a strong interdisciplinary approach combining hydrology, climatology, and data science to address evolving flood risks in the UK and globally. Fellow of Advance Higher Education Academy Dr. Han leads multiple funded research projects, including NERC and NIHR grants, and supervises several PhD students and postdoctoral researchers. She serves as a module lead for Quantitative Analysis of Hydrological Processes and Hydrology and Geomorphology, and acts as a personal tutor and dissertation supervisor. Her research group includes PhD students working on groundwater-surface water interactions, flood futures, machine learning for flood forecasting, and flood risk in India. She is actively involved in academic service as a reviewer for journals such as Water Resources Research and Journal of Hydrology , convener of EGU sessions, and member of professional societies including the British Hydrological Society, EGU, AGU, and IAHS.

Farahnaz SoleimaniView profile

Assistant Professor

• Structural Engineering
• Seismic Analysis
• Multi-Hazard Resilience Assessment
• +4 more

Farahnaz Soleimani is an Assistant Professor in the Department of Civil and Construction Engineering at Oregon State University, part of the College of Engineering. Her research focuses on multi-hazard resilience assessment of infrastructure systems, leveraging machine learning and physics-based models for seismic performance evaluation and risk mitigation. She develops computational tools for predictive modeling and sensitivity analysis in structural systems. Education: Ph.D., Civil/Structural Engineering, Georgia Institute of Technology, 2017 M.Sc., Civil Engineering, Georgia Institute of Technology, 2015 M.Eng., Civil Engineering, Tufts University, 2012 B.Sc., Civil Engineering, Sharif University of Technology, 2009 Her research interests include probabilistic modeling, structural dynamics, earthquake engineering, and applications of reliability theory and risk assessment. She also collaborates on interdisciplinary projects at the intersection of data science and STEM education to improve educational practices and diversity. Teaching focuses on structural engineering fundamentals (e.g., statics, dynamics) and applied mathematics/statistics, as well as specialized topics like finite element methods and bridge engineering. No specific labs or teams are listed, but her work emphasizes collaborative, data-driven approaches to civil engineering challenges.