Find Academic Supervisors

• Robotics
• Underwater Robotics
• Computer Vision
• +7 more

Claire Dune is an Assistant Professor at the University of Toulon, affiliated with the COSMER Laboratory (Mechanical and Robotic Systems Design Laboratory). Her research focuses on robotics, computer vision, and underwater systems, with applications in environmental monitoring and human-robot interaction. She teaches computer science, numerical methods, image processing, and visual servoing. Institution: University of Toulon Laboratory: COSMER (Mechanical and Robotic Systems Design Laboratory) Academic Rank: Assistant Professor Email: claire.dune@univ-tln.fr Her research centers on perception for robot control, particularly in underwater robotics and computer vision. Key interests include visual servoing, SLAM, gesture recognition for diver-robot interaction, and autonomous capabilities in real-world marine environments. She applies deep learning and sensor fusion techniques to enhance underwater visual perception and navigation. The recent publications demonstrate a strong trend in underwater robotics, with focus areas including tether dynamics (catenary modeling), ROV localization using umbilicals and IMUs, long-term visual localization in deep-sea environments, and color restoration in underwater imagery. Her work bridges theory and real-world application, contributing datasets like 'Eiffel Tower' for benchmarking and advancing multi-agent SLAM systems. Claire Dune has contributed to leading journals such as IEEE Robotics and Automation Letters, Ocean Engineering, and The International Journal of Robotics Research. Her editorial and survey work highlights her leadership in the domain of deformable object manipulation. Retrieval of benthic habitat abundance and bathymetry from hyperspectral data (DESIS) in shallow waters ROV localization using ballasted umbilical equipped with IMUs MAM3SLAM: Towards underwater robust multi-agent visual SLAM Eiffel Tower: A Deep-Sea Underwater Dataset for Long-Term Visual Localization Challenges and Outlook in Robotic Manipulation of Deformable Objects Claire Dune actively collaborates with researchers such as Vincent Hugel, Juliette Drupt, and Andrew Comport. She has supervised or co-supervised numerous research projects and publications, particularly in underwater robotics and assistive technologies. Her work involves experimental robotics and system integration, often validated in real marine environments. She leads research in the COSMER laboratory focused on underwater robotics, including projects on tethered ROVs, diver-robot communication via gesture recognition, and environmental monitoring using visual and hyperspectral data. Her team develops practical solutions for marine science and offshore operations, emphasizing robustness and autonomy.

Sunnie Sun ChungView profile

Professor

• Big Data Analytics
• Artificial Intelligence
• Natural Language Processing
• +3 more

Dr. Sunnie Sun Chung is a Professor in the Department of Electrical Engineering and Computer Science at Cleveland State University's College of Engineering. She leads the Big Data Analytics & AI Lab and has received multiple Faculty Merit Recognition Awards (2020-2024) and Golden Apple Awards (2021-2022). Research Interests : Big Data Analytics, Artificial Intelligence, Natural Language Processing, Cyber Security, Machine Learning, and Optimization in Cloud/IoT environments. Teaching : Advanced courses in Data Mining, Big Data Systems, and Deep Learning (DSA460/CIS492/593, CIS611/711, etc.) with dedicated teaching labs. Publications reflect expertise in Knowledge Graphs for Medical QA , Network Intrusion Detection with Graph Models , Privacy-Preserving Cloud Learning , and Basketball Analytics . Her work spans journals like IEEE Transactions on AI and IEEE Access. Scientific Awards : Faculty Merit Recognition Awards (4x) Golden Apple Teaching Award (2x) Students Supervised : Over 10 PhD/Master’s students including Asanka Mananayaka (NLP-based Intrusion Detection), Yixi Luo (Homomorphic Encryption), Dennis Risch (Medical QA Systems), and collaborators with Case Western Reserve University. Labs & Collaborations : Director of the Big Data Analytics & AI Lab since 2018. Hosted annual IBM Health collaborative workshops since 2018. Maintains strong industry ties with Microsoft, Amazon, Oracle, and Cleveland Clinic.

Barbara E. MinskerView profile

Professor

• Urban water sustainability and resilience
• Systems analysis
• Data analytics
• +6 more

Barbara E. Minsker is the Bobby B. Lyle Endowed Professor of Leadership & Global Entrepreneurship at Southern Methodist University, Professor of Civil & Environmental Engineering, and Professor of Computer Science (by courtesy). She is concurrently a Senior Fellow at the Hunt Institute for Engineering and Humanity. Education Ph.D., Civil and Environmental Engineering, Cornell University, 1995 B.S. with Distinction, Operations Research and Industrial Engineering, Cornell University, 1986 Research Focus Dr. Minsker’s research integrates systems analysis , machine learning , and data analytics to advance urban water sustainability and resilience . Specific themes include real-time flood prediction using crowdsourced traffic data, equitable distribution of green infrastructure, identification of “infrastructure deserts,” and nature-based solutions for storm-water management. Her methodological toolkit spans optimization under uncertainty, meta-modelling, spatio-temporal analytics, and socio-environmental modelling to address both engineering performance and social equity dimensions of urban infrastructure. Awards & Honors Presidential Early Career Award for Scientists & Engineers (PECASE) NSF CAREER Award ASCE Walter L. Huber Civil Engineering Research Prize Fellow, ASCE Environmental and Water Resources Institute ASCE Margaret S. Petersen Award Over a dozen additional national and institutional honors spanning 1991-2019 Grants & Advising As Principal Investigator or co-Principal Investigator, Dr. Minsker has secured more than $25 million in competitive funding from NSF, DOE, US Army Research Office, NIST, ONR, Metropolitan Water Reclamation District of Greater Chicago, Microsoft, ADM, and John Deere. These projects support interdisciplinary teams of graduate students and post-docs working at the intersection of water resources, data science, and societal resilience. Labs & Teams She leads an active research group within the Lyle School of Engineering at SMU, collaborating closely with the Hunt Institute for Engineering and Humanity and leveraging high-performance computing resources for large-scale urban analytics.

Howard E. EpsteinView profile

Professor

• Ecosystem Ecology
• Arctic Ecology
• Climate Change Impacts
• +7 more

Howard E. Epstein is the Sidman P. Poole Professor in the Department of Environmental Sciences at the University of Virginia, College of Arts and Sciences. He leads an active research group focused on ecosystem ecology, with field sites in the Arctic tundra of North America and Russia, as well as temperate forests in the U.S. Mid-Atlantic region. His work integrates field observations, remote sensing, and biogeochemical analysis to understand ecosystem responses to climate change. Ph.D., Colorado State University, 1997 Dr. Epstein's research centers on arctic vegetation dynamics , carbon cycling , and permafrost-vegetation interactions . He investigates how warming climates drive shrub expansion, ice-wedge degradation, and landscape transformation in tundra ecosystems. His work also explores carbon and water fluxes in temperate forest successional gradients. He employs advanced techniques including drone-based spectroscopy, satellite remote sensing, and flux tower measurements. The recent publications highlight a strong focus on Arctic greening , permafrost degradation , and the use of remote sensing and machine learning to detect ecological change. His work spans spatial scales from fine-resolution drone imaging to continental-scale satellite analysis, with applications in climate modeling and ecosystem monitoring. Dr. Epstein teaches core courses in ecology, including Terrestrial Ecology (EVSC 5220) and Fundamentals of Ecology (EVSC 3200) . He advises graduate students and leads the Epstein Ecosystem Ecology Lab , which conducts fieldwork in diverse ecosystems from Alaska to Virginia. His research is supported by external funding, though specific grants are not listed in the provided text. He has made significant contributions to understanding climate change impacts on high-latitude ecosystems, with publications in top journals such as Global Change Biology , Environmental Research Letters , and Nature Reviews Earth & Environment .

Arko LucieerView profile

Professor

• Remote Sensing
• Geospatial Science
• Environmental Monitoring
• +5 more

Professor Arko Lucieer is the Head of the School of Geography, Planning, and Spatial Sciences at the University of Tasmania. He holds a PhD in Remote Sensing from Utrecht University (Netherlands). His research focuses on advancing drone and remote sensing technologies for environmental monitoring, particularly in biodiversity mapping, ecosystem dynamics, and Antarctic ecology. He leads the TerraLuma research group, pioneering ultrahigh-resolution remote sensing applications. Key roles include: Established TERN DroneScape for national ecosystem monitoring Developed protocols for drone-based data collection and AI-driven analysis Recipient of the 2008 National Banksia Environmental Award Research Interests: Integration of drone technology, multispectral/hyperspectral imaging, and AI to quantify plant traits, map ecosystems, and address climate change impacts. Projects span forest health, Antarctic moss communities, and precision agriculture. Grants & Projects: TERN DroneScape: $1.6M for standardized drone-based ecosystem monitoring NatureScan: $1.2M for national biodiversity monitoring using drones and AI Supervision: Mentor to over 20 doctoral students, focusing on remote sensing applications in ecology, forestry, and environmental science. Labs/Teams: TerraLuma research group, specializing in drone remote sensing innovation and environmental data analytics.

David TodemView profile

Professor

• Biostatistics
• Epidemiology
• Longitudinal Data Analysis
• +6 more

David Todem is a Professor in the Department of Epidemiology and Biostatistics at Michigan State University. His work focuses on statistical methodology for longitudinal and clustered data, particularly in applications to cancer research and public health. He holds a Ph.D. in Statistics from the University of Wisconsin-Madison, an M.S. in Biostatistics from Hasselt University (Belgium), and an M.S. in Population Health from the University of Wisconsin-Madison. Dr. Todem's research interests include joint models for time-to-event and longitudinal outcomes, non-identifiable models with informative nonresponse, and testing heterogeneity in mixture models. His applied work addresses critical questions in cancer treatment efficacy, maternal-child health, and chronic disease surveillance. He has developed innovative methods for analyzing quality-of-life outcomes in cancer patients and spatial epidemiology of co-infections. Key contributions include the Validation of geospatial health indices Advancements in zero-inflated model testing Development of nonparametric scanning techniques Statistical frameworks for pediatric intervention evaluation He received a prestigious National Cancer Institute K01 award and has collaborated on federally-funded programs improving cardiovascular care in underserved populations. His work spans multiple domains including maternal-fetal medicine, environmental health, and global health equity. Methodological strengths include: Handling non-random missing data High-dimensional feature selection Weakly identifiable model sensitivity analysis Current research emphasizes translating statistical innovations into clinical practice through partnerships with healthcare systems and public health agencies.

Jiabi DuView profile

Assistant Professor

• Coastal Oceanography
• Climate Change Impacts
• Estuarine Hydrodynamics
• +3 more

Jiabi Du is an Assistant Professor at Texas A&M University at Galveston, specializing in coastal oceanography and environmental modeling. His research focuses on understanding how coastal systems respond to climate change, extreme weather events like hurricanes, and human activities, with particular emphasis on hypoxia, flooding, and habitat loss. He employs advanced numerical models and long-term observations to study processes such as pollutant dispersion and larval transport in estuaries. Dr. Du holds a Ph.D. in Physical Oceanography from the Virginia Institute of Marine Science (2017), an M.S. in Oceanography from Nanjing University (2012), and a B.S. in Physical Geography from Nanjing University (2010). His awards include the 2019 Institutional Postdoc Fellowship and recognition for academic excellence during his undergraduate and graduate studies. His research interests span coastal hydrodynamics, hurricane impacts, and microplastic transport. Notable contributions include studies on Galveston Bay's hydrodynamic responses to Hurricane Harvey and the role of baroclinic processes in estuarine flushing. He teaches courses in Physical Oceanography and computing. Awards: Best Student Paper (2018), Zengxianzi Scholarship (2007-2009), National Inspiration Scholarship (2007-2008). Labs/Teams: Coastal Modeling Group, Galveston Oyster Larvae Tracker Project. Future research directions include expanding microplastic pollution studies and investigating compounding climate-hurricane effects on coastal systems.

• Geodesy
• Global Navigation Satellite System (GNSS)
• Geodetic monitoring
• +7 more

Félicia Norma Rebecca TEFERLE is a Full Professor in Geodesy at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), Department of Engineering. She leads the Geodesy and Geospatial Engineering research group, focusing on high-precision GNSS applications, remote sensing, and digital engineering technologies. Her work integrates geodetic, geophysical, and environmental methodologies. PhD in high-precision vertical land movement monitoring for sea level studies from the University of Nottingham. Industry experience in GPS systems for offshore geophysical investigations. Research interests include: GNSS processing strategies and atmospheric water vapor monitoring 3D land movement monitoring via SAR and photogrammetry BIM/GIS integration and machine learning for 3D city modeling No specific scientific awards or grant details are provided in the text. She maintains active roles in teaching, mentoring, and research innovation.

Johan BarthelemyView profile

Academic

• Complex Systems
• Agent-based Simulation
• Computer Vision
• +7 more

Dr. Johan Barthelemy is an Honorary Associate Professor at the University of Wollongong's Faculty of Sciences - SAEF, where he leads the SMART IoT Hub and Digital Living Lab. His research focuses on complex systems, agent-based simulation, AI for IoT, and smart cities. He holds a PhD in Applied Mathematics from the University of Namur (Belgium) and has contributed to projects like the mipfp statistical package for R. His work spans environmental monitoring, transportation modeling, and infrastructure resilience. He supervises higher-degree research students and collaborates with NVIDIA as a Deep Learning Institute Ambassador. Education: PhD in Applied Mathematics, University of Namur (2007–2014) MSc in Mathematics, University of Namur (2005–2007) BSc in Applied Mathematics, University of Namur (2003–2005) Research Interests: Agent-based simulation and synthetic population generation AI-driven video analytics for smart cities and environmental monitoring IoT sensor networks and edge computing GPU-based high-performance computing Climate change impact analysis via drones and multispectral imaging Funding & Projects: Lead investigator for ARC grants on future mobility and Antarctic environmental futures CSIRO-funded project on AI-driven sugarcane assessment Multiple University of Wollongong grants for IoT sensors, climate testing facilities, and disaster-resilient transport Labs & Collaborations: SMART Infrastructure Facility (UOW) Namur Center for Complex Systems (Belgium) NVIDIA Deep Learning Institute partnership

Kevin HeaslipView profile

Professor

• Transportation Engineering
• Transportation Technology
• Critical Infrastructure Cybersecurity
• +11 more

Kevin Heaslip is a Professor and Director of the Center for Transportation Research in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville. He joined the university in 2022, bringing extensive experience from his prior role as Professor and CACI Faculty Fellow at Virginia Tech. Education: PhD in Civil and Environmental Engineering, University of Massachusetts Amherst, 2007 MS in Civil and Environmental Engineering, Virginia Tech, 2003 BS in Civil and Environmental Engineering, Virginia Tech, 2002 Dr. Heaslip's research focuses on the intersection of transportation engineering, intelligent systems, and cybersecurity. His work spans future transportation concepts such as electrified and automated vehicles, transportation operations including freeway and transit management, and cybersecurity for transportation and critical infrastructure. He applies advanced data analytics, machine learning, and cyber-physical systems modeling to real-world challenges in mobility and national security. The recent articles highlight a strong trend in leveraging big data and artificial intelligence for transportation mode detection, traffic event identification, and security risk assessment. His work increasingly integrates cybersecurity into transportation systems, particularly in autonomous and connected vehicles, reflecting the evolving technological landscape and national priorities in infrastructure protection. Scientific Awards and Recognitions: Virginia Tech G.V. Loganathan Faculty Achievement Award for Excellence in Civil Engineering Education (2019) Virginia Tech Favorite Faculty Award (2017) Outstanding Alumni, University of Massachusetts Institute of Transportation Engineers Student Chapter (2015) Outstanding Young Alumni, Virginia Tech Department of Civil & Environmental Engineering (2013-2014) USU Civil & Environmental Engineering Teacher of the Year (2014) USU Civil & Environmental Engineering Undergraduate Research Mentor of the Year (2013) USU Civil & Environmental Engineering Outstanding Researcher (2011, 2012) USU College of Engineering Undergraduate Research Mentor of the Year (2011) Dr. Heaslip has secured over $25 million in research grants and contracts from federal and state governments as well as industry partners. He has advised numerous students and mentored undergraduate researchers, receiving multiple awards for teaching and mentorship. His professional service includes membership in the American Society of Civil Engineers (ASCE), Institute of Transportation Engineers (ITE), and Transportation Research Board (TRB), as well as serving as an Appointed Member of the Resilient America Roundtable of the National Academy of Sciences from 2014 to 2020. He leads the Center for Transportation Research at UT Knoxville, a multidisciplinary lab focused on advancing transportation technologies and policies. The lab's research is organized around three thrusts: future transportation systems (electrified, connected, and automated vehicles), transportation operations (freeway, transit, and corridor management), and cybersecurity of transportation and critical infrastructure.

• Acoustic Pollution
• Low-Cost Noise Sensors
• Digital Signal Processing
• +1 more

Guillermo Quintero Perez is a Senior Lecturer at the Department of Mechanical Engineering , Technical University of Catalonia . His work focuses on acoustic pollution , low-cost noise sensors , digital signal processing , and noise mapping . He collaborates with researchers like Jordi Romeu and Andreu Balastegui on urban noise monitoring projects. Research Interests : Developing low-cost noise sensors for scalable urban monitoring Optimizing noise mapping through mobile sampling and data stratification Applying digital signal processing to environmental acoustics Investigating sound insulation properties of metamaterial structures Publications : His recent work (2024) includes studies on broadband noise reduction in acoustic windows and compliance testing for low-power sensors. Earlier contributions (2023-2017) explore statistical models for noise estimation, cluster analysis for temporal stratification, and sensor network deployment.

Mitra BaratchiView profile

Associate Professor

• Spatio-Temporal Data Analysis
• Machine Learning
• Mobility Data Modeling
• +5 more

Mitra Baratchi is an Associate Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University. She leads the Spatio-temporal data Analysis and Reasoning (STAR) research group, co-leads the Automated Design of Algorithms (ADA) group, and founded the Special Interest Group on Spatio-Temporal Data Mining (SIG-SDTM) . PhD from University of Twente (Mobility Data) Master’s/Bachelor’s in Computer Engineering, Iran Research Interests focus on automated pattern extraction from spatio-temporal data across urban, environmental, and industrial domains. Key applications include: Automated Machine Learning (AutoML) for Earth Observations Time-Series Forecasting for public health (e.g., pandemic modeling) Urban Mobility Optimization with ESA, Honda, and municipalities Reliable Vehicular Communication Systems Smart Garments for Health Risk Detection Geocast Protocols for Internet-wide Communication Grant Highlights include €120K NWO-Aspasia, €2.9M Marie Skłodowska-Curie, €350K NWO-KLEIN, and €135K Center for BOLD Cities funding. She has supervised 12 PhD students and 4 current Master’s students since 2011, with notable best paper award at WWIC'16. Teaching includes Machine Learning (2020-present) and Urban Computing (2018-present) at Leiden, plus past courses in Data Visualization, Software Engineering, and Research Methods.

Richard BeckerView profile

Professor

• Environmental Remote Sensing
• GIS Applications
• Hydrogeology
• +7 more

Dr. Richard Becker is a Professor in the Department of Environmental Sciences at the University of Toledo , affiliated with the College of Natural Sciences and Mathematics . He directs the Environmental Remote Sensing Lab , where he employs interdisciplinary methods including remote sensing, geochemistry, hydrologic modeling, and UAV technologies to address geological and environmental challenges. Education: Ph.D. (2008) from Western Michigan University, M.A. and B.A. from Washington University Contact: richard.becker@utoledo.edu | 419.530.4571 | Wolfe Hall, Toledo, OH Research Focus Dr. Becker's work spans three decades, concentrating on: Environmental applications of remote sensing and GIS for geohazard mapping Assessment of land subsidence in arid regions and coastal areas Monitoring toxic algal blooms in the Laurentian Great Lakes Hydrological impacts of engineering projects on wetland systems Climate change effects on groundwater resources in Africa and the Middle East Article Trends His recent publications (2018-2024) demonstrate a consistent focus on: Integration of UAV/drone technologies for high-resolution environmental monitoring Application of remote sensing to track climate change impacts on water systems Development of multi-model ensembles for watershed management Analysis of human-environment interactions through geospatial methods

Th. UdelhovenView profile

Professor

• Remote Sensing
• Geoinformatics
• Environmental Monitoring
• +6 more

Th. Udelhoven is a Professor and Head of the Environmental Remote Sensing & Geoinformatics Department at Trier University's Faculty of Regional and Environmental Sciences in Germany. He maintains an active research program in remote sensing technologies and environmental monitoring with extensive publications spanning over two decades. His research interests focus on Remote Sensing , Geoinformatics , Environmental Monitoring , Satellite Data Analysis , and Land Degradation Assessment . His work integrates advanced hyperspectral imaging, UAV technology, and spatial analysis techniques to address environmental challenges related to soil science, precision agriculture, and forest ecology. His methodological expertise spans from traditional remote sensing techniques to cutting-edge machine learning applications in geospatial analysis. Analysis of his recent publications reveals a strong emphasis on practical applications of remote sensing technologies for environmental monitoring, with particular focus on agricultural systems, soil health assessment, and land cover change detection. His research demonstrates consistent innovation in applying remote sensing technologies to solve real-world environmental problems across diverse geographical contexts from European agricultural landscapes to African and Asian ecosystems. Professor Udelhoven actively teaches courses including Pattern Recognition in long term global satellite archives, Statistik I: Statistische Grundlagen für die Bio- und Geowissenschaften, and Umweltwissenschaftliche Projektstudie, demonstrating his commitment to education in environmental sciences and geoinformatics. He has mentored numerous students who appear as co-authors on his publications, particularly in areas of crop monitoring, land cover analysis, and soil science applications. His collaborative research extends across multiple institutions and international boundaries, reflecting the global relevance of his work in environmental monitoring and sustainable land management.

• Watershed Hydrology
• Surface Water Quality
• Hydroinformatics
• +5 more

Jeffrey Horsburgh is a Professor in Civil and Environmental Engineering and a Water Researcher at the Utah Water Research Laboratory (UWRL) at Utah State University. His work focuses on hydroinformatics, environmental sensor networks, and watershed hydrology, integrating data models, cyberinfrastructure, and GIS for water quality and hydrology research. Professor, Utah State University (College of Engineering) Utah Water Research Laboratory Research Interests: Dr. Horsburgh develops technology for environmental observatories, emphasizing high-frequency sensor data, reproducibility, and cyberinfrastructure. His research spans watershed hydrology, surface water quality, human dimensions of water use, and standards-based data sharing through platforms like HydroShare and HydroServer. Notable Awards: 2024 USU Outstanding Researcher 2023 Reproducibility Author Award 2019 Outstanding Teacher 2014 Early Career Excellence Award (International Environmental Modelling & Software Society) Education: Ph.D., MS, and BS in Civil/Environmental Engineering from Utah State University (2009, 2001, 1999).