Find Academic Supervisors

Lars BoletView profile

Researcher

• Traffic Engineering
• Road Safety
• Accident Prediction Modeling
• +5 more

Lars Bolet is affiliated with the Department of the Built Environment at the Faculty of Engineering and Science, Aalborg University (AAU), Denmark. His work focuses on traffic engineering, road safety, and municipal infrastructure management. He has contributed extensively to research and public discourse on transportation systems. His research interests include: Traffic safety and accident prediction modeling Integration of hospital data in traffic risk assessment Energy-efficient transportation technologies Winter road maintenance and de-icing policies Economic impacts of traffic accidents on municipalities Sustainable urban mobility and infrastructure planning The analysis of his 15 most recent publications reveals a consistent focus on practical applications in civil and traffic engineering, emphasizing data-driven decision-making, public safety, and cost-efficiency in municipal road management. His work often bridges technical engineering solutions with socioeconomic implications, particularly in how local governments manage traffic risks and infrastructure investments. Scientific contributions and media engagement: Active contributor to traffic safety research since the 1990s Frequent media commentator on road conditions, traffic policies, and accident prevention Presenter at public and private sector events on municipal transport costs and safety investments Co-author of influential reports using real-world injury data to improve accident hotspot identification Lars Bolet has also engaged in advisory and outreach activities, including contributions to national infrastructure reporting and expert commentary in policy debates. While formal PhD supervision appears limited, he has played a significant role in applied research and knowledge dissemination. His work is closely tied to public institutions such as the Danish Road Directorate and various Danish municipalities, reflecting a career deeply integrated with practical civil engineering challenges.

Clementina MoldovanView profile

Associate Professor

• Environmental Engineering
• Coal Combustion and Emissions
• Explosive Atmospheres Safety
• +3 more

Clementina Moldovan is an Associate Professor in the Department of Environmental Engineering and Geology at the Faculty of Mining, Politehnica University of Timişoara. Her research focuses on environmental safety, industrial emissions, and explosion protection systems in hazardous environments. She has contributed extensively to understanding coal combustion byproducts' environmental impacts, air quality monitoring, and electrical equipment safety standards in explosive atmospheres. Her work integrates computational modeling (e.g., CFD simulations for indoor air pollution) with geospatial analysis (e.g., hot spot mapping of pollutants in Craiova). Key research areas include: 1) Development of GHG intensity metrics for industrial processes, 2) Thermal safety of equipment in explosive environments, and 3) Heavy metal contamination in atmospheric particulates. Dr. Moldovan also investigates radiation dosimetry in soils and the application of natural materials like zeolites for pollution control. Recent studies address hydrogen safety protocols and the adaptation of safety standards to emerging energy technologies. Her publications emphasize practical applications of research to industrial safety compliance, environmental policy formulation, and sustainable development strategies for mining regions. Current projects explore synergies between computational fluid dynamics and regulatory frameworks for hazardous environment equipment certification.

Kay RömerView profile

Professor

• Wireless Sensor Networks
• Internet of Things
• Cyber-Physical Systems
• +7 more

Kay Römer is Professor and Director of the Institute for Technical Informatics at Graz University of Technology, Austria. He previously held a professorship at the University of Lübeck, Germany, and was a senior researcher at ETH Zurich, where he obtained his doctorate in computer science in 2005. His research focuses on networked embedded systems, particularly in the domains of Wireless Sensor Networks, Internet of Things (IoT), and Cyber-Physical Systems. Key areas include wireless networking, operating systems, programming models, dependability, and deployment methodologies for large-scale embedded networks. The most recent publications reflect a consistent trend in dependable and scalable IoT systems, with emphasis on wireless protocols, fault tolerance, real-time operation, and system robustness. His work bridges theoretical innovation with practical deployment, often involving cross-layer design and energy efficiency. Associate Editor, IEEE Transactions on Mobile Computing Associate Editor, IEEE Transactions on Computers Program Co-Chair, ACM SenSys 2011 Program Co-Chair, ACM/IEEE IPSN 2013 Coordinator, EU FP7 FIRE Project RELYonIT Coordinator, TU Graz Excellence Project "Dependable Internet of Things" Kay Römer has advised multiple research teams and coordinated major international projects funded by the Swiss National Science Foundation, European Commission, German Science Foundation, German Federal Ministry of Education and Research, and the Austrian Federal Ministry of Science, Research, and Economy. He has delivered invited keynote talks and co-directed five international summer schools, demonstrating strong leadership in research dissemination and mentoring. He leads research activities within the Institute for Technical Informatics at TU Graz, focusing on dependable and secure IoT systems, with active collaborations across Europe and industry partners.

Naonori UedaView profile

Research Professor

• Machine Learning
• Artificial Intelligence
• Physics-Informed Deep Learning
• +5 more

Naonori Ueda is a Research Professor and Deputy Director at RIKEN Center for Advanced Intelligence Project. He also serves as a Visiting Fellow at NTT Communication Science Laboratories, Research Supervisor for Mathematical Information Platform at Japan Science and Technology Agency (JST), and Visiting Professor at Kobe University's Graduate School of System Informatics. His distinguished career spans academia, government research institutions, and industry collaboration, with significant contributions to advancing artificial intelligence and machine learning applications across multiple scientific domains. Dr. Ueda's research interests focus on the intersection of machine learning, artificial intelligence, and physical sciences. He specializes in physics-informed deep learning approaches that integrate governing physical equations with neural network architectures. His work spans geophysical data analysis, remote sensing applications, computational seismology, and environmental monitoring systems. He has pioneered methods for crustal deformation modeling, earthquake prediction, tsunami inundation forecasting, and satellite imagery analysis using advanced machine learning techniques. His research demonstrates how AI can solve complex scientific problems by bridging the gap between data-driven approaches and physical domain knowledge. His publication record reveals a strong trend toward applying machine learning to solve real-world geophysical and environmental challenges. His recent work shows increasing sophistication in physics-informed neural networks that incorporate domain-specific knowledge into deep learning architectures. The publications span high-impact journals like Nature Communications, demonstrating the interdisciplinary significance of his work. His research consistently focuses on practical applications of AI for disaster prevention, environmental monitoring, and scientific discovery. Fellow of IEICE (Institute of Electronics Information and Communication Engineers) Member of Japan Prize field review committee Selection Committee Member for Brilliant Female Research Award (The Jun Ashida Award) Member of Kyoto Prize Selection Committee Dr. Ueda has secured substantial research funding through multiple government-sponsored projects including RIKEN Pioneering Project 'Prediction Science,' JST AIP Acceleration Research projects on weather prediction and drug discovery, and AMED-funded medical research initiatives. His leadership extends to serving as Sub-project Director for Japan's Moonshot R&D Project. He actively mentors researchers through his roles at RIKEN, NTT, and various academic institutions, fostering the next generation of AI scientists. As Deputy Director of RIKEN Center for Advanced Intelligence Project, Dr. Ueda leads one of Japan's premier AI research initiatives. He also serves on the Advisory Board of Kobe University's Mathematical and Data Science Center and Kyoto University's Graduate School of Informatics. His leadership extends to coordinating the AI Seminar at Osaka Industrial Association and supervising the Keihanna 'Edison Society' at the International Institute for Advanced Studies, demonstrating his commitment to bridging academic research with industrial applications.

• Programming Languages
• Compiler Construction
• Parallel Computing
• +7 more

Wayne Kelly is an Associate Professor in the School of Computer Science at Queensland University of Technology (QUT), Faculty of Science. He has over 25 years of academic experience and serves as the Academic Lead for Teaching and Learning and Course Coordinator for the Bachelor of Information Technology degree. PhD in Computer Science, University of Maryland, College Park, 1996 BSc (Hons) in Computer Science, University of Queensland, 1989 His research expertise lies in Programming Languages, Compiler Construction, and Parallel Computing, with significant contributions to High Performance Computing, Big Data, and Bioinformatics. His work has led to collaborations with Microsoft Research and over $2 million in external funding. His recent publications reflect a strong trend in parallel and distributed systems, embedded computing, bioinformatics data analysis, and remote sensing. Key themes include optimization of computational systems, memory management, and scalable data processing. Wayne Kelly has made impactful contributions to both teaching and research, guiding numerous postgraduate students and leading curriculum development in information technology. Optimizing I/O cost and managing memory for bioinformatics A communication model for streaming applications on MPSoC Ruby.NET: a compiler for the Common Language Infrastructure He is actively engaged in real-world technology development, including a project with a vision-impaired student to improve public transportation accessibility, currently trialed by transport authorities in Australia and the US.

• Forest Carbon Management
• Sustainable Forest Management
• Remote Sensing in Forestry
• +5 more

Mathias Neumann is an Assistant Professor at the Institute of Forest Management within the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU). His research focuses on Forest Ecosystem Management with a specific emphasis on sustainable Carbon management in forests. Dr. Neumann leads multiple research projects including 'Totholzzersetzung in Zentraleuropäischen Wäldern' (Deadwood decay in Central European forests) and 'OPTimising FORest management decisions for a low-carbon, climate resilient future in EUrope'. Dr. Neumann's research interests span forest carbon dynamics, sustainable forest management, remote sensing applications in forestry, climate change impacts on forest ecosystems, deadwood decay processes, and wildfire risk assessment. His work integrates field measurements with modeling approaches to understand carbon allocation in forest ecosystems, forest productivity under changing climate conditions, and the development of sustainable management practices that enhance forest resilience and carbon sequestration capacity. His recent publications demonstrate a clear focus on understanding forest carbon cycles, developing methods for assessing forest carbon sinks, modeling forest responses to climate change, and evaluating sustainable management practices. The research trends show increasing emphasis on integrating multiple data sources to create comprehensive forest ecosystem models that can inform climate-resilient forest management decisions across Europe. Förderpreis Fonds 120 Jahre Universität für Bodenkultur (2020) Thurn und Taxis Förderpreis (2018) Outstanding Reviewer Award of Forests (2017) Dr. Neumann has secured significant research funding from the Austrian Science Fund (FWF), European Commission, and national agencies. His current projects address critical challenges in forest management under climate change, including wildfire risk mapping, deadwood management, and optimizing forest carbon sequestration. He actively collaborates with international research teams and contributes to policy-relevant research that bridges science and forest management practice. His work with the Institute of Forest Management involves both fundamental research on forest ecosystem processes and applied research that directly informs sustainable forest management practices in Austria and Europe.

• Aerial Robotics
• Unmanned Aerial Vehicles (UAVs)
• Remote Sensing
• +12 more

João Pedro Matos-Carvalho is an Assistant Professor at Lusófona University in Lisbon, affiliated with the School of Engineering and the Department of Electrical and Computer Engineering. He is also an Integrated Member of the Center of Technology and Systems (CTS) at UNINOVA and COPELABS, Lusófona University, contributing to interdisciplinary research in robotics and intelligent systems. Ph.D. in Electrical and Computer Engineering, FCT NOVA (2021) M.Sc. (Hons.) in Electrical and Computer Engineering, FCT NOVA (2017) His research focuses on aerial robotics, machine learning, remote sensing, and sensor networks, with applications in UAV navigation, precision agriculture, environmental monitoring, and embedded AI. He has made significant contributions to GPS-denied navigation, multispectral imaging, and AI-driven signal processing. The recent publications reflect a strong trend in integrating deep learning with real-world engineering systems, particularly in UAV autonomy, IoT, and human-centric applications like fall detection and online learning analysis. His work spans algorithm design, software development, and practical deployment in complex environments. Best Paper Award at IEEE Conference (2018) Distinguished Paper Award by LASIGE at FCUL (2021) Best Poster Presentation Award at International Complex Systems and Their Applications Conference (2023) He has secured the competitive Scientific Employment Stimulus (CEEC) grant from FCT and has advised or collaborated on multiple research projects. He has guest-edited special issues in journals such as Drones and Frotiers in Computer Science , and serves as a reviewer for leading scientific journals. He leads the development of open-source tools like AutoNAV and Raster Forge, supporting simulation and geospatial analysis. He is actively involved in research teams at CTS-UNINOVA and COPELABS, focusing on intelligent systems, aerial robotics, and data fusion. His lab work emphasizes practical UAV platforms, sensor integration, and AI deployment in real-time systems.

• Geological Carbon Storage
• Underground Hydrogen Storage
• Reservoir Engineering
• +4 more

Hongsheng Wang is a Research Fellow at the Bureau of Economic Geology within the Jackson School of Geosciences at The University of Texas at Austin. His research focuses on advancing subsurface energy technologies through interdisciplinary approaches combining geoscience, engineering, and machine learning. Key areas include geological carbon storage, underground hydrogen storage, reservoir simulation, and fracture mechanics. His work emphasizes innovative applications of machine learning for challenges such as CO2 plume migration forecasting, parameterization of 3D saturation data, and fracture conductivity analysis. He also investigates leakage mitigation strategies in hydrogen storage systems and the role of permeability heterogeneity in subsurface processes. Publications highlight contributions to microfluidic experiments, porous media dynamics, and AI-driven reservoir modeling. Current projects involve surrogate models for large-scale simulations and dimension reduction techniques to enhance computational efficiency in carbon storage assessments.

Muhammad UmarView profile

Academic

• Fluvial Dynamics
• Remote Sensing
• GIS Applications
• +5 more

Muhammad Umar is a Teaching Assistant Professor in the Department of Geography & Geographic Information Science at the University of Illinois, Urbana-Champaign, affiliated with the School of Earth, Society & Environment. He holds a Ph.D. and M.S. in Geography and Meteorology, respectively, and completed a postdoctoral fellowship in Civil and Environmental Engineering. His research focuses on fluvial dynamics, remote sensing, process modeling, and GIS applications, with particular emphasis on river confluences, landslide susceptibility, and agricultural environmental management. Education: Postdoc: University of Illinois, Department of Civil and Environmental Engineering Ph.D.: University of Illinois, Department of Geography and GIS M.S.: COMSATS University Islamabad, Department of Meteorology Research interests span fluvial hydrology, remote sensing for environmental monitoring, and geospatial tool development. Recent work includes analyzing river confluence mixing dynamics, landslide susceptibility in Pakistan’s upper Indus Basin, and crop health assessments using satellite data. He has developed online platforms for soil nitrogen tracking and precision agriculture. His publications (2012–2025) reflect expertise in hydrology, geohazards, and climate-agriculture interactions. Notable contributions include studies on U.S. river confluences, Pakistan’s precipitation datasets, and evapotranspiration trends in South Korea. Teaching includes advanced GIScience and high-performance geospatial computing courses. No scientific awards are explicitly listed, but his work demonstrates significant academic and applied impact. Advising and grants details are not provided in the text. He is affiliated with the university’s Geography department and contributes to interdisciplinary research teams addressing environmental challenges through geospatial technologies.

Bryan MarkView profile

Professor

• Physical Geography
• Climate and Environmental Change
• Paleoclimatology
• +4 more

Bryan Mark is a Professor in the Department of Geography at The Ohio State University, affiliated with the College of Arts and Sciences. He is also involved with the Byrd Polar and Climate Research Center and the State Climate Office of Ohio. His research focuses on physical geography, climate-glacier-hydrologic dynamics, and mountain studies, with fieldwork in the Peruvian Andes, Great Basin, and Himalayas. Education: Ph.D. 2001, Syracuse University (Earth Sciences) M.A. 1995, Ohio State University (Geography) B.A. 1992, Brown University (History) Research Interests: Earth-Water-Atmosphere interactions, tropical glaciers, and climate change impacts on mountain regions. His work integrates field, lab, and computational methods across disciplines like paleoclimatology, geomorphology, and biogeochemistry. Recent projects include studying glacier retreat, proglacial hydrology, and climate adaptation strategies in vulnerable regions. Advising & Grants: Leads the Glacier Environmental Change research group, collaborating internationally. Active in interdisciplinary projects funded by NSF and other agencies. Courses taught include climatology, global environmental change, and mountain geography. Labs/Teams: Byrd Polar and Climate Research Center, State Climate Office of Ohio. His lab focuses on mountain hydroclimate dynamics and cryo-social systems in the American Cordillera and Himalayas.

Art PoonView profile

Associate Professor

• Bioinformatics
• Phylogenetics
• Molecular Epidemiology
• +4 more

Art Poon is an Associate Professor at Western University, specializing in bioinformatics and molecular epidemiology. His research focuses on reconstructing virus spread and adaptation using genomic data, with a particular emphasis on HIV and SARS-CoV-2. He holds a PhD from the University of California, San Diego, and completed a postdoc at the UCSD Center for AIDS Research. Poon leads the Poon Lab, developing computational tools for evolutionary analysis and open-source software for high-performance computing. Education: PhD in Biology (UC San Diego), MSc in Zoology (UBC), Postdoctoral training in HIV genomics. His work bridges mathematical modeling, phylogenetics, and machine learning to address public health challenges. Research Interests: Virus evolution, phylodynamics, and the application of network science to epidemiological data. His lab’s tools, like HexSE and CoVizu, enable real-time genomic epidemiology and wastewater-based surveillance. Key Contributions: Developed methods for HIV transmission cluster detection and SARS-CoV-2 variant tracking in wastewater. His work appears in journals like PLoS Computational Biology and Molecular Biology and Evolution.

Cory McCartanView profile

Professor

• Computational Social Science
• Bayesian Methods
• Causal Inference
• +5 more

Cory McCartan is the Hoben and Patricia Thomas and Thomas and Ann Hettmansperger Early Career Professor of Statistics at Penn State University, with an affiliate appointment in Political Science. His research focuses on methodological and applied problems in computational social science, including redistricting, Bayesian methods, causal inference, and racial disparities. He co-leads the Algorithm-Assisted Redistricting Methodology (ALARM) Project at Harvard University and develops open-source software for redistricting analysis (e.g., redist , birdie ). McCartan holds a Ph.D. in Statistics from Harvard (2023) and a B.A. in Mathematics from Grinnell College (2019). His work bridges statistical methodology and policy applications, with recent emphasis on legislative redistricting reforms, gerrymandering analysis, and privacy-preserving census data methods. Key projects include evaluating redistricting algorithms, quantifying partisan bias, and estimating disparities in administrative data using Bayesian models. Publications span topics like redistricting simulation, census privacy impacts, and neighborhood modeling. His ALARM Project produces 50-state redistricting simulations for public use, emphasizing reproducible workflows and open-source tools. McCartan's software packages ( e.g. , redist , conformalbayes ) are widely adopted in policy and academic research. Grants and collaborations involve the Voting and Election Science Team and Harvard Data Science Initiative, with computational support from Microsoft. His work has been covered in Science Advances , Proceedings of the National Academy of Sciences , and Science .

Subra SureshView profile

Professor

• Algorithmic Fairness
• Machine Learning Ethics
• Data Privacy
• +3 more

Subra Suresh is a Professor at Large at the School of Engineering, Brown University. His email is Subra_Suresh@brown.edu . He focuses on interdisciplinary research at the intersection of technology and society, emphasizing algorithmic fairness, AI ethics, and computational law. His research interests include addressing biases in machine learning systems, ensuring equitable access to technology, and developing frameworks for ethical AI governance. He explores topics such as data privacy, social network disparities, and legal implications of emerging technologies. Recent publications highlight trends in auditing algorithms for fairness, mitigating bias in decision-making systems, and designing policies for responsible AI deployment. His work bridges technical innovation with societal impact, advocating for transparent and accountable technologies. No scientific awards or grants are explicitly listed in the provided materials. He has not disclosed advisee information, and there is no mention of lab affiliations or teams in the text.

Mansour AlmazrouiView profile

Research Fellow

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

Mansour Almazroui is a Research Fellow at the School of Environmental Sciences, University of East Anglia. His research focuses on climate science, environmental monitoring, and atmospheric processes with a particular emphasis on Middle Eastern and Asian regions. He has published extensively on topics including rainfall patterns in Saudi Arabia, satellite-based groundwater monitoring techniques, and the environmental impacts of PPE during the pandemic. Almazroui's work integrates observational data with advanced modeling techniques, as seen in his analysis of CMIP6 climate models and high-resolution atmospheric simulations of ENSO teleconnections. His collaborative projects span across institutions in Egypt, China, Pakistan, and the UK, reflecting a global approach to environmental challenges. Key research areas include climate dynamics, aerosol monitoring, pandemic-related environmental impacts, and hydrological systems. His studies have contributed to better understanding of regional climate variability and pollution mitigation strategies in coastal and arid environments.

Dhirendra ShuklaView profile

Professor

• Entrepreneurial Finance
• Corporate Governance
• Venture Capital
• +7 more

Dr. Dhirendra Shukla is the Dr. J. Herbert Smith ACOA Chair at the University of New Brunswick's J Herbert Smith Centre for TME. He holds a PhD in Entrepreneurial Finance from King's College London, an MBA from the Telfer School of Management (University of Ottawa), and advanced engineering degrees from the University of Bradford. His research focuses on venture capital, corporate governance, entrepreneurial finance, and sustainability in renewable energy and technology-driven industries. Education: BEng/MSc in Chemical Engineering & Computing (University of Bradford) MBA (University of Ottawa/Telfer School) PhD in Entrepreneurial Finance (King's College London) His teaching portfolio includes courses on entrepreneurial finance, global engineering, and leadership in technology management. Research interests span venture capital dynamics, IPO governance, blockchain applications, and smart energy systems. He has presented at conferences like the Strategic Management Society and Academy of International Business, contributing to cross-national studies on corporate governance and IPO performance. Shukla's work bridges academia and industry, with projects addressing renewable energy partnerships in Atlantic Canada and federated learning systems for privacy-preserving data analytics. His recent studies explore AI-driven digital twins, cyber-physical systems in smart cities, and blockchain adoption in higher education.