Find Academic Supervisors

Zachary SickmannView profile

Assistant Professor

• Sedimentology
• Stratigraphy
• Sediment Provenance
• +9 more

Zachary Sickmann is an Assistant Professor in the School of Natural Sciences and Mathematics at the University of Texas at Dallas. His research focuses on sedimentology, stratigraphy, and sediment provenance, with applications in environmental monitoring, construction materials, and climate change studies. His research interests include: Sediment transport in coastal and estuarine systems Detrital records of glaciation and sea-level change Fingerprinting sand sources for traceable construction material sourcing Machine learning applications in geological image analysis Tectonic controls on deep-water sediment dispersal His recent publications highlight a strong trend in integrating traditional geological field and laboratory methods with data science and machine learning, particularly through the development of the sandID project, which aims to create a global database for sand provenance using image-based classification. This work bridges academic research with practical applications in sustainability and resource management. Scientific contributions and projects: sandID : A machine learning–driven tool for identifying sand composition and provenance via image analysis Citizen science initiative for global sand sample imaging Collaborative research on sediment supply networks and environmental change Dr. Sickmann actively seeks contributions from citizen scientists and researchers to expand the sandID dataset. He is involved in advising and mentoring through research participation, though no formal students are listed. His work has implications for sustainable construction, coastal management, and paleoenvironmental reconstruction.

• Machine Learning
• Algorithm Optimization
• Neural Networks
• +4 more

Kyungmi Joanne Lee is a Senior Lecturer at James Cook University (JCU), Australia, specializing in Computer Science and Artificial Intelligence. She holds a PhD in Computer Science from Griffith University (2007) and previously served as a Lecturer at Charles Sturt University (2007–2008). Her research focuses on machine learning, algorithm optimization, neural networks, data mining, and applied AI. Key projects include developing real-world scheduling systems for mining operations, ultrasonic signal classification, and spatio-temporal trajectory analysis. Teaching responsibilities include modules like Database Modelling, where she coordinates and lectures. She currently supervises 5 PhD students, with 3 nearing completion. Her work spans diverse applications, such as emergency management through geospatial data analysis and curriculum development via text mining. With 58 publications across journals and conferences, her contributions highlight interdisciplinary approaches to data-driven solutions.

• Knowledge Representation
• Ontology Engineering
• Semantic Web
• +6 more

Cassia Trojahn is a permanent Lecturer at the University of Toulouse 2 Jean Jaurès , affiliated with IRIT - UMR 5505, Department of Mathematics and Computer Science. Her career spans institutions in France, Portugal, Brazil, and the Netherlands, with roles including Expert Engineer at Joseph Fourier University and Post-Doc at INRIA Rhône-Alpes. Education Semantic Web, Ontology Alignment, Business Intelligence (University of Toulouse) Functional Programming (Haskell, Scala), Information Extraction (Pierre Mendès University) Graph Theory and Complexity (University of Évora) Research Interests : Knowledge representation and semantic web technologies Ontology alignment methodologies (argumentation, complex alignments, holistic approaches) Earth observation data integration with contextual information Open science and FAIR data principles Argumentation frameworks for mapping reconciliation Query rewriting with complex correspondences Advising : Co-supervised 5 PhD theses across France and Brazil, including: Jordane Dorne (2018-2021) - Earth observation semantic change detection Élodie Thiéblin (2016-2019) - Complex ontology alignment Roger Granada (2011-2015) - Hierarchical relations extraction Projects : Participated in international (CAMELEON, MULTIFARM) and European (EFFECTOR, CANDELA, SEALS) projects focused on multilingual ontology alignment, maritime situational awareness, and semantic earth observation data analysis.

Tolga OvatmanView profile

Professor

• Algorithms and Computing Theory
• Computer Software and Software Engineering
• Cloud Computing
• +6 more

Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .

Carolin HeimView profile

Researcher

• Water Treatment
• Electrochemical Oxidation
• Water Disinfection
• +3 more

Dr. Carolin Heim serves as a Working Group Leader for the Analytical Laboratory at the Chair of Urban Water Management, Technical University of Munich since 2023. Her role involves leading analytical research in water treatment technologies, with a focus on electrochemical processes for water disinfection and contaminant removal. She works within the Department of Civil, Geo and Environmental Engineering at TUM's School of Engineering. Dr. Heim earned her Diplom (Dipl. Leb. Chem.) from Technische Universität Dresden in 2003, followed by her doctorate (Dr. rer. nat.) from Technical University of Munich in 2010. Her doctoral research focused on "Human plasma and peripheral blood mononuclear cell (PBMC) proteome databases for biomarker discovery studies in vivo." She completed her undergraduate studies in Food Chemistry at Technische Universität Dresden and Universität Karlsruhe. Dr. Heim's research centers on advanced water treatment technologies, particularly electrochemical oxidation processes using boron-doped diamond electrodes. Her work investigates pharmaceutical contaminant removal, water disinfection mechanisms, and transformation by-product analysis across various water matrices. She examines how different water qualities affect treatment efficiency and focuses on developing sustainable, eco-friendly water treatment solutions that address emerging contaminants while ensuring water safety. Her publication record demonstrates consistent contributions to environmental engineering, with a focus on electrochemical water treatment systems. Dr. Heim's research shows an evolution from fundamental analytical chemistry to applied environmental engineering, with increasing emphasis on practical water treatment solutions that address real-world challenges in water quality and safety. Dr. Heim leads the Analytical Laboratory at TUM's Chair of Urban Water Management, where her team conducts cutting-edge research on water treatment technologies. The laboratory specializes in electrochemical oxidation processes, pharmaceutical contaminant analysis, and water quality monitoring using advanced analytical techniques.

Federico CiardoView profile

Assistant Professor

• Geomechanics
• Subsurface Engineering
• Fault Dynamics
• +5 more

Federico Ciardo is an Assistant Professor of Civil and Environmental Engineering at Northwestern University, specializing in geomechanics and subsurface engineering. His research focuses on understanding deformation mechanisms in brittle rocks and fault zones under fluid injection, aiming to improve predictive models for geo-engineering applications like geothermal energy and CO2 sequestration. He leads the GEOFORCE Group, which develops advanced computational and theoretical approaches to study subsurface processes across multiple scales. Education: Ph.D. in Mechanics from École Polytechnique Fédérale de Lausanne (EPFL, Switzerland), M.Sc. and B.Sc. in Civil/Structural Engineering from the University of Bologna, Italy. Research Interests: Investigating fluid-driven deformation instabilities in fractured rocks, seismic hazard mitigation, and the interplay between in-situ stresses and external forces. Key topics include aseismic/a-seismic slip dynamics, hydraulic stimulation effects, and fault zone heterogeneity. His work integrates fracture mechanics, numerical modeling (e.g., boundary element methods), and scaling arguments to achieve mechanistic insights. Scientific Contributions: Published extensively on induced seismicity forecasting, fault slip nucleation, and hybrid hydromechanical models. Notable recognition includes the EPFL Doctoral Program Thesis distinction award (2020). Labs/Teams: Principal investigator of the GEOFORCE Group, affiliated with the Paula M. Trienens Institute for Sustainability and Energy. Collaborates on projects involving underground laboratories (e.g., Bedretto Lab) and geothermal energy systems.

Dean RehbergerView profile

Associate Professor

• Digital History
• US History
• Public History
• +6 more

Dean Rehberger is an Associate Professor in the Department of History at Michigan State University (MSU) and Director of MATRIX, MSU's digital humanities center. His research focuses on developing digital technologies for research and teaching, including semantic web, big data, digital libraries, and geospatial knowledge graphs. He leads interdisciplinary projects such as the KnowWhereGraph and the Enslaved.org hub knowledge graph, emphasizing ethical sustainability and disaster risk management frameworks. Education details are not explicitly stated in the provided text. Research interests include digital history, public history, and the application of computational methods to cultural heritage and emergency management. His work bridges geospatial analysis, ontology engineering, and humanities applications through projects like HIP Ontology and the S2 Discrete Global Grid System. Recent articles highlight advancements in knowledge graph architectures, geospatial data integration, and ethical frameworks for digital projects. Notable projects include the $1.5M Mellon Grant for the Enslaved.org database and collaboration with GLAM institutions (galleries, libraries, archives, museums). Grants: Mellon Foundation Grant (2023) for slave trade database Labs/Teams: MATRIX (digital humanities center at MSU)

Chris MannaertsView profile

Associate Professor

• Hydrological Remote Sensing
• Environmental Satellite Hydrology
• Water Resource Management
• +3 more

Chris Mannaerts is an Associate Professor of Environmental Satellite Hydrology at the Faculty of Geo-information Sciences & Earth Observation (ITC), University of Twente, Netherlands. He holds MSc degrees in (soil) physical chemistry, environmental sanitation engineering, and a PhD in agricultural hydrology from the University of Ghent, Belgium. His research focuses on hydrological remote sensing, biogeochemical data applications in water-food-health security, and climate impacts on ecosystems. He actively contributes to international networks like GEO, promoting open access to Earth observation data. Education: MSc in (soil) physical chemistry MSc in environmental sanitation engineering PhD in agricultural hydrology (University of Ghent) Research Interests: Satellite hydrology, land & water management, environmental protection, climate impacts, and international project collaborations. His work aligns with UN Sustainable Development Goals, emphasizing sustainable water resources and food security. Recent Activities: Invited talk on FAO WAPOR database applications (2020) Presented on near real-time Earth observation for early warning systems (2019) Collaborated on long-term SPM monitoring in the Scheldt Estuary (2022) Labs/Teams: Engaged in interdisciplinary teams focusing on Earth observation technologies and their societal applications, particularly in Africa, Latin America, and Asia.

• Data Analytics
• Distributed Systems
• Query Optimization
• +5 more

Jorge-Arnulfo Quiané-Ruiz is a researcher at Qatar Computing Research Institute , with affiliations at institutions like Technical University of Berlin and University of Nantes (PhD, 2008). His work focuses on data analytics , distributed systems , and query optimization , particularly in cross-platform environments and trusted execution frameworks . Research Interests : Data analytics across heterogeneous platforms Secure and compliant data processing in trusted environments Efficient query allocation and optimization Scalable algorithms for big data and streaming graphs Machine learning in data management Table extraction and data cleaning Publications : Recent work includes benchmarks for TEE-based joins and cross-database query frameworks (2023). Explores space-efficient graph algorithms and ML-driven revenue optimization (2022). Developed RHEEMix , a cost-based optimizer for cross-platform systems (2018). Collaborations : Regularly partners with Volker Markl and Zoi Kaoudi on unified analytics frameworks. Contributed to projects like Apache Wayang and AgoRA .

• Geodesy
• Astronomical Geodesy
• GIS
• +7 more

Paul Daniel DUMITRU is an Assistant Professor at the Technical University of Civil Engineering Bucharest (UTCB), Faculty of Geodesy. With a PhD awarded in 2011, he has established himself as a prominent researcher in geodetic sciences, having won the UTCB Award for "Researcher of the Year at the Faculty of Geodesy" three consecutive years (2017-2019). His research focuses on: Geodetic network design (satellite, classical and combined) GNSS and classical geodetic measurements Permanent GNSS station networks Astro-geodetic measurements for vertical deviation determination Coordinate transformations and quasi-geoid modeling GIS database design and geodetic application development DUMITRU's recent publications reveal a strong focus on applying space geodesy to practical problems, with significant work on quasi-geoid modeling using GOCE mission data, validation of satellite radar interferometry for landslide monitoring in the Carpathian regions, and development of CCD-based instruments for vertical deviation measurements. His research demonstrates consistent innovation in measurement techniques with applications spanning disaster management, infrastructure protection, and precision agriculture. His scientific contributions have been recognized with multiple awards, including: UTCB Award for "Researcher of the Year at the Faculty of Geodesy" (2017) UTCB Award for "Researcher of the Year at the Faculty of Geodesy" (2018) UTCB Award for "Researcher of the Year at the Faculty of Geodesy" (2019) DUMITRU has managed research projects with competitive funding, having won 4 projects through competition (PNII, PNIII) as Project Director or Project Partner Responsible. His work spans geodesy, geospatial analysis, and the application of space technologies to practical problems in civil engineering, disaster management, and agriculture. He has developed applications to automate geodetic works using programming languages including C++, MATLAB, and Python, demonstrating strong technical skills alongside his domain expertise in geodesy.

• Computational Biology
• Bioinformatics
• Mass Spectrometry Data Analysis
• +5 more

Attila Kertesz-Farkas is a Hungarian-born academic currently serving as Assistant Professor at the Faculty of Computer Science, Department of Data Analysis and Artificial Intelligence, at the National Research University Higher School of Economics (HSE) in Moscow. Since 2021, he has also been Head of the Research and Educational Laboratory of Artificial Intelligence for Computational Biology. He joined HSE in 2015 after completing postdoctoral positions at the University of Washington and the International Centre of Genetic Engineering and Biotechnology. His educational background includes: Doctor of Science (2022) from National Research University Higher School of Economics PhD (2010) from University of Szeged Master's degree in Computer Science (2004) from University of Szeged Kertesz-Farkas's research focuses on the intersection of artificial intelligence and computational biology, particularly in mass spectrometry data analysis. His work spans computational proteomics, human gait analysis, and medical applications of machine learning. He develops novel algorithms for peptide identification, protein classification, and single-cell analysis, with applications ranging from cancer research to environmental contamination analysis. His research group actively explores how deep learning can improve the analysis of biological data that is inherently non-human readable. His scientific contributions have been recognized with several awards including a Letter of thanks from the Rector of HSE (December 2022), a Letter of gratitude from the Faculty of Computer Science (September 2021), and the Best presentation award at ICMLC 2023 conference. As an academic supervisor, Kertesz-Farkas mentors multiple PhD students working on diverse projects including generative models for mass spectrometry data, human gait control systems for prosthetics, and deep learning applications for single-cell analysis. His research is supported by the allowance for defending a doctoral dissertation (2022-2025) and various research projects at HSE. He leads the Laboratory of Artificial Intelligence for Computational Biology, which focuses on developing AI methods specifically tailored for biological data analysis problems. The laboratory conducts research in computational proteomics, medical applications of machine learning, and the development of tools for mass spectrometry data interpretation.

• Marine Science
• Environmental Policy
• Ocean Governance
• +6 more

Professor Elaine Baker holds the UNESCO Chair in Marine Science at the University of Sydney and directs the GRID-Arendal office, a UNEP collaborating center. She specializes in marine governance, environmental policy, and sustainable development, focusing on continental shelf delineation, mercury pollution, and waste management. Her work bridges academia with global policy, contributing to UN reports like the GEO-6 and leading initiatives such as the Pacific Maritime Boundaries project. She has advised on maritime boundary disputes, mine safety protocols, and coral reef conservation. Key roles: UNESCO Chair, Director (GRID-Arendal), Lead Author (GEO-6 Report) Research interests: Climate change, ocean governance, mine tailings safety, and coral reef resilience Global collaborations: UN Environment Programme, Pacific Islands States, Norwegian Ministry of Foreign Affairs Her research emphasizes real-world impact, including policy frameworks for waste management and coastal ecosystem preservation. She co-founded the Pacific Maritime Boundaries initiative, aiding over 60 nations in maritime jurisdiction claims. Awards include the 2015 Australian Financial Review Women of Influence recognition. Recent work focuses on coral reef island stability under climate threats, mine tailings safety databases, and the human health dimensions of environmental degradation. She collaborates on interdisciplinary projects through the Sydney Institute of Marine Science, integrating GIS and marine data analysis into education and policy. Grants and projects: UN Environment’s Global Environmental Outlook for Cities, Basel Convention guidelines, African Development Bank wastewater studies Labs/teams: GRID-Arendal research unit, Pacific Shelf Programme, Global Tailings Review advisory panel

Deligiannakis AntoniosView profile

Professor

• Databases
• Sensor Networks
• Online Analytical Processing (OLAP)
• +6 more

Antonios Deligiannakis is a Professor at the Department of Electronic and Computer Engineering, Technical University of Crete. His research focuses on databases, sensor networks, online analytical processing (OLAP), approximate query processing, and distributed systems. He holds a Ph.D. in Computer Science from the University of Maryland (2005), an M.Sc. from the same institution (2001), and a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (1999). His career includes postdoctoral work at the University of Athens (2006–2007), a lecturer position there (2007), and an internship at AT&T Labs-Research (2003). He leads the Software Technology and Network Applications Laboratory , contributing to projects like extreme-scale analytics platforms (INFORE) and federated learning systems. Research areas span IoT workflow optimization, communication-efficient distributed learning, and real-time maritime event detection. His work emphasizes scalability, efficiency, and practical implementations for big data challenges. Courses taught include Structured Programming . Notable contributions include DAG* algorithms for IoT workflows, federated learning frameworks, and systems for proactive streaming analytics at scale. He has pioneered methods for outlier detection in sensor networks and efficient query processing over distributed streams.

Emmanuel StefanakisView profile

Professor

• Geospatial Data Science
• Digital Earth
• Discrete Global Grid Systems (DGGS)
• +17 more

Emmanuel Stefanakis is a Professor and Department Head of Geomatics Engineering at the Schulich School of Engineering, University of Calgary. He holds a PhD in Electrical and Computer Engineering (National Technical University of Athens, 1997), an MScE in Geodesy and Geomatics Engineering (University of New Brunswick, 1994), and a Dipl.Eng in Rural and Surveying Engineering (National Technical University of Athens, 1992). His research focuses on Geospatial Data Science, Discrete Global Grid Systems (DGGS), GeoAI, and applications of Geomatics in natural hazards, transportation, and climate change . He has led over 140 student projects and authored/co-authored five textbooks and 150+ articles. Notable awards include the 2023 Canadian Cartographic Association’s Award of Distinction and the 2023 UCalgary Teaching Excellence Award. Recent articles emphasize high-performance trajectory analysis, DGGS integration, and geospatial quantum computing . His work bridges theoretical advancements with practical tools for flood modeling, epidemiology, and urban planning. Grants include NSERC Discovery Grants and collaborations with industry partners like McElhanney Ltd. Professional memberships span the Canadian Institute of Geomatics, Canadian Cartographic Association, and APEGA. He served as Editor-in-Chief of Cartographica (2014–2022) and actively contributes to international conferences on geoinformatics. His educational initiatives include innovative course designs in online and distance learning. Current roles include leadership in the HALOS and Geospatial Quantum Computing projects, advancing geomatics engineering education in the digital era.

Georgios J. FakasView profile

Associate Professor

• Big Data
• Keyword Search
• Spatial Databases
• +9 more

Georgios J. Fakas is an Associate Professor (Docent) in the Department of Information Technology at Uppsala University, Sweden, where he leads the Uppsala DataBase Laboratory (UDBL). He has held academic positions at prestigious institutions including the Hong Kong University of Science and Technology, EPFL, UMIST, University of Cyprus, and Manchester Metropolitan University, where he served as a Senior Lecturer. Education: Ph.D. in Computation, UMIST, Manchester, UK (1998) M.Phil. in Computation, UMIST, Manchester, UK (1996) B.Sc. in Computation, UMIST, Manchester, UK (1995) His research spans big data, keyword search on structured and graph data, spatial databases, web and geo-social search, workflow management, and data summarization . He also explores applications in educational technologies, distance learning, and health informatics. His work emphasizes efficient, user-centric data access and intelligent querying paradigms. The 15 most recent publications highlight a sustained focus on keyword search, object summarization, spatial and semantic data, and ranking , published in top venues like SIGMOD, VLDBJ, IEEE TKDE, and PVLDB. His work integrates algorithmic innovation with practical database applications. Scientific Awards: International Sabbaticals grant from Teknat (2023), hosted by Boston University Fellowship 'Hosting of Experienced Researchers from Abroad' from RPF, Cyprus (2009) ERCIM Fellowship (2001), hosted by EPFL, Switzerland He is actively involved in PhD supervision and grant leadership. He currently serves as Principal Investigator for an eSSENCE-funded project on Data-intensive analytics for discovering critical minerals using Machine Learning , in collaboration with industry partners. He has supervised multiple PhD students to completion, including Georgios Kalamatianos, Khalid Mahmood, Zhi Cai, and Ben Cawley. He is a frequent reviewer for leading journals and serves on program committees of major conferences such as ACM SIGMOD and PVLDB. He leads the Uppsala DataBase Laboratory (UDBL) , a research group focused on advanced data management systems, where he mentors students and drives innovation in database technologies.