Find Academic Supervisors

• Explainable Artificial Intelligence (XAI)
• Time Series Classification
• Cardiology
• +6 more

Prof. Dr. Jennifer Hannig is a leading researcher in Explainable Artificial Intelligence (XAI) and computational biology at the Technical University of Mittelhessen's KITE Competence Center. Her work bridges AI transparency with applications in cardiology, digital pathology, and smart home technologies, focusing on interpretable algorithms for safety-critical domains. Junior Research Group Leader, TimeXAI project (2024-2027, €1.09M) Collaborations with Kerckhoff Clinic, CRS medical GmbH, and Veli GmbH Member of good scientific practice committee Mentor at Mentoring Hessen and AI Grid initiative Research Focus : Developing human-understandable XAI methods for time series classification, particularly in cardiovascular diagnostics and smart home monitoring. Her approach combines mathematical modeling (Petri nets) with deep learning to ensure reliable AI decision-making. Scientific Contributions : Key publications in PLOS Computational Biology , Frontiers in Digital Health , and Bioinformatics , with h-index of 8. Developed AI models for myocardial scar detection, Hodgkin lymphoma analysis, and manufacturing predictions. Poster Award – 1st Place (German Conference on Bioinformatics, 2013) ECCB 2016 Travel Award Contact: jennifer.hannig@kite.thm.de

• Graph Drawing
• Information Visualization
• Visual Analytics
• +3 more

Professor Seokhee Hong is a distinguished academic at the School of Computer Science, The University of Sydney. With prestigious appointments including an ARC Future Fellowship (2013-2016) and Humboldt Fellowship (2013-2014), she has emerged as a leading researcher in graph drawing and visual analytics. Her research focuses on developing scalable algorithms for information visualization of massive complex networks, with applications spanning security analytics, computational biology, and software engineering. Key contributions include the creation of open-source visual analytics software GEOMI and foundational work in 2.5D graph visualization. 2013-2016: ARC Future Fellowship 2008-2012: ARC Research Fellowship 2013-2014: Humboldt Fellowship Recent publications demonstrate her ongoing innovation in graph drawing algorithms, network fairness, and computational geometry. She has served on editorial boards of key journals and as program chair for major conferences in her field. 2006: CORE Chris Wallace Award 2012: Eureka Prize Finalist Multiple Graph Drawing Competition wins Her work bridges theoretical algorithm development with practical applications, addressing challenges in biological network analysis, dynamic graph visualization, and cluster-preserving layouts. With over 140 publications and significant research funding, she continues to shape network visualization research.

Uwe RascherView profile

Professor

• Photosynthesis
• Remote Sensing
• Plant Physiology
• +5 more

Prof. Dr. Uwe Rascher is the Head of the Shoot Dynamics group at the Institute of Bio- and Geosciences (IBG) , Plant Sciences (IBG-2) within the Jülich Research Centre . His research bridges biophysical processes in photosynthesis with remote sensing applications. Research Focus: Spatiotemporal dynamics of photosynthesis Non-destructive physiological monitoring Solar-induced chlorophyll fluorescence (SIF) for ecosystem analysis Drought and stress response in crops Machine learning for agricultural decision support Integration of leaf-to-canopy scale observations Scientific Trends: Analysis of SIF for photosynthesis quantification, development of hyperspectral imaging systems, cross-scale stress detection (drought, heat), machine learning applications in plant phenotyping, and climate research collaborations. Technical Contributions: Development of HyScreen, FloX, and FluoMap systems for field spectroscopy, UAV-based sensor validation, and standardized ground measurement networks. His work emphasizes sensor fusion, light distribution models, and fractal geometry for fluorescence downscaling.

• Power Electronics
• Control Systems
• Renewable Energy Integration
• +3 more

Prof. Dr. Osman Kukrer is a full-time faculty member at Eastern Mediterranean University (EMU), Faculty of Engineering, Department of Electrical and Electronics Engineering. He has been actively supervising graduate students in power electronics, control systems, and renewable energy integration since the 1990s. His research spans advanced power conversion topologies, including quasi-Z-source inverters multilevel converters active power filters grid-connected systems adaptive beamforming algorithms electric vehicle grid integration Notable contributions include the EMU Publication Citation Award (2017) and extensive supervision of 41 graduate theses, with research interests aligning with modern energy systems and signal processing techniques.

Christos TryfonopoulosView profile

Associate Professor

• Information Retrieval
• Information Filtering
• Personal Information Management
• +20 more

Christos Tryfonopoulos is an Associate Professor and Head of the Department of Informatics & Telecommunications at the University of the Peloponnese, where he leads the Software and Database Systems (SoDa) Lab. His academic career spans prestigious institutions including the Max-Planck Institute for Informatics in Germany, where he led the P2P and Information Management research area from 2006-2009, and the Technical University of Crete, where he completed his PhD and MSc degrees. His research interests focus on information management, distributed systems, digital libraries, and data/user anonymity. His work bridges theoretical foundations with practical applications across diverse domains including environmental monitoring, cybersecurity, cultural heritage, and medical informatics. He has developed innovative frameworks for pollution prediction, cyber-threat intelligence, and academic expertise mapping that demonstrate the interdisciplinary nature of his research. Professor Tryfonopoulos has published over 80 papers in top-tier journals and conferences including TOIS, TKDE, SIGIR, and SIGMOD. His recent work shows a strong trend toward applying machine learning techniques to information management problems, with publications spanning environmental science, cybersecurity, and bibliometrics. His research group has developed several significant tools including VeTo+ for expert set expansion, inTIME for cyber-threat intelligence, and Hydria for cultural heritage analytics. Candidate for best research paper in ESWC 2016 conference Honorable mention for best poster (3rd place) in ESWC 2012 conference Award as Distinguished Scientist Excelling in Research Abroad (2008) Best student paper award in ECDL 2005 conference Heraclitus PhD fellowship from Greek Ministry of Education (2002-2005) National Scholarship Foundation of Greece (IKY) scholarship (1998) Professor Tryfonopoulos has supervised 5 PhD students (3 in progress), 19 MSc students, and 31 BSc students. He has led or participated in 13 competitive EU and national research projects including ENIRISST+ for shipping and transport infrastructure, WeCare for student support structures, and FORESIGHT for cybersecurity simulation. His current research focuses on intelligent infrastructure for transportation logistics, cyber-threat intelligence systems, and educational technologies for data science.

Mark DuceyView profile

Professor

• Forest Biometrics
• Quantitative Silviculture
• Remote Sensing in Forestry
• +6 more

Mark Ducey is a Professor in the Department of Natural Resources and the Environment at the University of New Hampshire. His research focuses on forest biometrics, quantitative silviculture, and the application of remote sensing technologies like LiDAR to analyze forest structure, carbon dynamics, and ecological change across scales from individual stands to regional landscapes. Primary Affiliation: University of New Hampshire Department: Natural Resources and the Environment His work spans mixed-species forests in New England, the Blue Mountains of Oregon, and international collaborations in Europe, Australia, New Zealand, Costa Rica, and Brazil. Key research themes include: Quantitative forest inventory techniques Carbon sequestration and climate change impacts Coarse woody debris sampling Remote sensing integration for ecological modeling Land cover change analysis Recent publications highlight advancements in height-diameter modeling, biomass estimation via novel sampling methods, and ecological implications of forest management practices. His teaching includes courses on forest inventory analysis, grant writing, and contemporary conservation issues.

Robbert KrebbersView profile

Associate Professor

• Semantics
• Separation logic
• Theorem proving
• +7 more

Robbert Krebbers is an associate professor at the Department of Software Science at Radboud University Nijmegen, Netherlands. He is a leading researcher in program verification, specializing in separation logic and the Coq proof assistant. Krebbers is a core contributor to the Iris framework, a higher-order concurrent separation logic framework implemented in Coq. His research spans theoretical foundations of programming languages and practical applications to real-world languages including C, Rust, and Scala. His research interests focus on scaling program verification techniques to challenging programming paradigms like concurrency, higher-order functions, and modules. Krebbers' work bridges formal methods with practical language implementation, particularly in verifying memory safety and concurrency properties. He has made significant contributions to Rust verification through the RustBelt project and has pioneered techniques for verifying concurrent data structures and message-passing systems. Krebbers' recent publications demonstrate a strong trend toward verifying complex concurrency patterns, developing automated proof techniques, and applying separation logic to practical programming language features. His work frequently appears in top-tier programming languages conferences including POPL, PLDI, and ICFP, with several papers receiving distinguished paper awards. The research spans from foundational logic development to practical verification tools for real-world programming languages. As a principal investigator in the Iris project, Krebbers has secured significant research funding including the ERC Consolidator Grant for the RustBelt project. His work has influenced both academic research and industrial practice, particularly in the Rust programming language ecosystem. The Iris framework he helped develop has been adopted by numerous verification projects worldwide. Krebbers has advised PhD students including Ike Mulder (focusing on proof automation for concurrent separation logic) and Jules Jacobs (working on guarantees by construction). He has been actively involved in the programming languages research community, serving on program committees for major conferences and organizing workshops on formal methods and verification. He leads research in the Department of Software Science at Radboud University, where his group focuses on developing foundational techniques for program verification. The group collaborates closely with the Logic and Semantics Group and Foundations of Programming Group across institutions, contributing to a vibrant research ecosystem around formal methods and programming languages.

TOLGA ERENView profile

Professor

• Cooperative Localization
• Formation Control
• Wireless Sensor Networks
• +3 more

Professor Tolga Eren serves as a faculty member in the Department of Electrical and Electronic Engineering at Kirikkale University's Faculty of Engineering and Natural Sciences. Holding a PhD from Yale University with postdoctoral training at Columbia University, he previously held a visiting professorship at KTH Royal Institute of Technology and earned his BSc from Bilkent University under full scholarship. His educational trajectory includes: BSc in Electrical and Electronics Engineering, Bilkent University (full scholarship) MSc from University of Massachusetts and Yale University PhD from Yale University Postdoctoral research at Columbia University Eren's research centers on networked systems with dual focus on cooperative localization in wireless sensor networks and formation control for multi-robot systems. He pioneers applications of optimization algorithms like Particle Swarm and Bat Algorithm for positioning challenges while advancing rigidity theory for network stability. His work bridges theoretical frameworks with practical implementations in constrained environments. Analysis of his 2019-2021 publications reveals three dominant trends: (1) Hybrid optimization approaches for wireless sensor network localization using swarm intelligence variants, (2) Rigidity-theoretic foundations for formation control under input constraints, and (3) Geometric methods for robot path smoothing and shape maintenance. These intersect at the nexus of graph theory, control systems, and distributed computing. Professor Eren has advised at least one graduate student, Gülçin AKTAŞ, who completed her departmental thesis in 2014. While no specific grants are documented in the available records, his research output demonstrates sustained investigation into networked system fundamentals through institutional support at Kirikkale University.

• Electronic Components
• Circuit Design
• Sensor Systems
• +5 more

Prof. Dr.-Ing. Volker K. S. Feige is a Professor at the Faculty of Electrical Engineering & Information Technology at Düsseldorf University of Applied Sciences (Hochschule Düsseldorf), where he has been teaching since March 2012. He teaches Electronic Components, Circuit Design, Sensor Systems & Signal Processing, and Manufacturing Measurement and Testing Technology. His research focuses on non-destructive testing methods using electromagnetic Terahertz waves, enabling more resource-efficient and sustainable manufacturing processes. Since August 28, 2023, Prof. Feige has also served as a member of the University Council of Düsseldorf University of Applied Sciences. Education: Vocational training as Energieelektroniker - Betriebstechnik (1988-1992) College entrance qualifications and bridge courses (1992-1993) Diploma in Electrical Engineering, Bergische Universität Wuppertal (1993-1998) Doctorate at Bergische Universität Wuppertal (2003) Prof. Feige's research centers on Terahertz technology applications for non-destructive testing and quality control. His work spans electronic components, circuit design, sensor systems, and signal processing with practical applications in corrosion protection of steel bridges and quality control of industrial coatings. He has developed innovative approaches for multilayer thickness measurements using reflection-mode Terahertz time-domain spectroscopy, particularly for challenging industrial environments. His research addresses real-world manufacturing challenges through precise, non-contact measurement techniques that improve sustainability and resource efficiency. Analysis of Prof. Feige's publication history reveals a clear research evolution from fundamental Terahertz measurement techniques toward integrated industrial solutions. His recent work increasingly incorporates robotics and machine learning for automated quality inspection systems, with growing applications in additive manufacturing and 3D printing. The consistent theme across his publications is the development of practical non-destructive testing methods that solve specific industrial challenges, particularly in coating thickness measurement across various substrates and multi-layer systems. Research Leadership: Principal investigator for multiple Terahertz technology research projects Contributor to VDI/VDE guidelines on Terahertz systems standardization Collaborator with industry partners on practical measurement solutions Lead on patents for 3D interferometric position measurement systems Prof. Feige directs research in the Electronics Laboratory at Düsseldorf University of Applied Sciences, where his team develops semi-mobile robotized Terahertz systems for automated quality inspection. His research group maintains strong industry connections, translating fundamental measurement technology into practical industrial applications for non-destructive quality control in manufacturing processes.

• Genetics of Obesity
• Body Fat Distribution
• Metabolic Disorders
• +4 more

Matt Neville serves as the Oxford Biobank Scientific Coordinator within the Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM) at the University of Oxford's Medical Sciences Division. His primary responsibilities include curation of the Oxford Biobank resources, facilitation of translational research studies, and management of biobank operations. As a Lecturer, he supervises DPhil students and contributes to the Experimental and Translational Therapeutics MSc program. His research focuses on the genetic determinants of body fat function and distribution and their impact on obesity-related health consequences. Neville employs genomic, epigenomic, and metabolomic approaches to investigate adipose tissue biology, metabolic disorders, and Type II diabetes pathogenesis. His work leverages large-scale biobank resources including Oxford Biobank and UK Biobank for translational studies. Analysis of his 15 most recent publications reveals a consistent emphasis on genetic architecture of metabolic traits , with particular attention to adipose tissue biology, obesity genetics, and biomarker discovery. His research integrates multi-omic approaches (genomics, epigenomics, proteomics) to understand context-specific molecular mechanisms in metabolic diseases, with strong translational applications for risk prediction and personalized medicine. Neville holds critical operational roles including Person Designated for the OCDEM HTA license and serves as the RDM OCDEM EDI Champion. His academic journey began with a DPhil in human molecular genetics from Oxford in 2000, followed by industry R&D experience, and a postdoctoral position with Prof Fredrik Karpe since 2003 investigating adipose tissue genetics.

Süleyman MeteView profile

Associate Professor

• Operations Research
• Modeling and Optimization
• Multi-criteria Decision Making
• +4 more

Süleyman Mete is an Associate Professor in the Industrial Engineering Department at Gaziantep University's Faculty of Engineering. He has been serving in this position since 2021, following previous roles as a Doctor Lecturer at Gaziantep University (2019-2021) and Munzur University (2017-2019). His academic career began as a Research Assistant at Gaziantep University (2011-2016) and Tunceli University (2010-2011). Dr. Mete earned his Doctorate in Industrial Engineering from Gaziantep University (2013-2017), followed by a Master's degree in Industrial Engineering from the same institution (2011-2013). He completed his undergraduate studies in Industrial Engineering at Selcuk University (2005-2010). Dr. Mete's research focuses on Operations Research, Modeling and Optimization, and Multi-criteria Decision Making. His work spans several specialized areas including disassembly line balancing, humanitarian logistics, risk assessment, and fuzzy logic applications. His research integrates mathematical programming with practical industrial applications, particularly in disaster response, sustainable manufacturing, and supply chain optimization. He has developed innovative approaches combining various multi-criteria decision-making methods with fuzzy logic to address complex real-world problems in occupational safety, transportation, and humanitarian aid distribution. His extensive publication record demonstrates a clear trajectory toward increasingly complex applications of optimization techniques, particularly in humanitarian contexts. Recent work shows a strong focus on drone-assisted logistics, urban mobility sustainability, and advanced risk assessment methodologies using various fuzzy set approaches. His research consistently bridges theoretical methodological development with practical applications in industrial engineering problems. University 2% Most Influential Scientist (2023) University 2% Most Influential Scientist (2022) Dr. Mete has successfully supervised numerous graduate students through their thesis work, with a particular focus on humanitarian logistics, disassembly line balancing, and risk assessment applications. His research projects include "Sustainable, Digital, and Smart Humanitarian Logistics in Disaster Relief Operations" (EU-funded) and "Data-Driven and Web-Based Decision Support System Development for Integrated Optimization of Vector Control Process" (Tübitak 1505). He has also served as a visiting researcher at Karlsruhe Institute of Technology (KIT) in Germany under the TÜBİTAK 2219 Postdoctoral Research Program. Dr. Mete's work demonstrates strong integration between theoretical methodological development and practical applications, particularly in humanitarian contexts and industrial engineering problems. His research group appears to focus on optimization techniques applied to real-world challenges in disaster response, sustainable manufacturing, and supply chain management.

K Siva KumarView profile

Professor

• Multi-level Inverters
• Induction Motor Drives
• Micro-grids
• +3 more

K Siva Kumar is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Hyderabad . His research focuses on multi-level inverters , induction motor drives , and micro-grid systems , with applications in renewable energy and electric vehicles . He holds a Ph.D. in Electrical Engineering from IISc Bengaluru (2010), an M.Tech in Power Electronics from NIT Warangal (2006), and a B.Tech in Electrical and Electronics Engineering from Sri Venkateswara University (2004). He joined IIT Hyderabad in 2011, progressing from Assistant Professor to Professor in 2022. His research interests span power quality and control , Pole Phase Modulation (PPM) , and Open-end winding induction motor drives . His publications (over 20 in 2021-2025) focus on photovoltaic systems , electric vehicle propulsion , and advanced inverter topologies . Scientific recognitions include: Fellow Indian National Academy of Engineers (FNAE) - 2024 Teaching Excellence Award (2021-22), IIT Hyderabad IETE-BIMAL BOSE AWARD - 2018 Senior Member IEEE Best Paper Awards at IEEE ICIAfS (2014), ANSYS Convergence Conference (2014), and IEEE ISIE-2009. He has supervised 15 Ph.D. and M.Tech students , including current scholars Tukaram Alias and Saurabh P Dhavjekar , and alumni like Kiran Kumar N and Madhukar Rao A . His teaching portfolio includes undergraduate courses in Power Electronics and Electromechanical Energy Conversion , and postgraduate courses in Electrical Drives and Multilevel Converters .

Gerda ClaeskensView profile

Professor

• Model Selection
• Model Averaging
• Post-Selection Inference
• +4 more

Gerda Claeskens is a full professor of Statistics at the Faculty of Economics and Business (FEB) at KU Leuven, Belgium. She holds positions in the Operations Research and Statistics Research Group (ORSTAT) and is affiliated with the Leuven Statistics Research Center. Her academic journey includes a Licentiate in Mathematics (Summa Cum Laude) from the University of Antwerp and a Ph.D. in Statistics from Limburgs Universitair Centrum (now Hasselt University). Research Interests: Her work focuses on model selection, post-selection inference, nonparametric methods, and high-dimensional statistics. She has contributed extensively to methodologies like focused information criteria, penalized splines, and quantile regression. Awards and Honors: Notable accolades include Fellow of the American Statistical Association (2019), Goodeve Medal (2017), and Medallion Lecturer (2016). She has also held editorial roles in top journals such as Biometrika and Journal of the American Statistical Association . Teaching and Mentoring: She has advised over 20 PhD students and mentored postdoctoral researchers. Her teaching spans advanced statistical methods, probability theory, and business statistics. She has delivered invited lectures globally, including at the European Meeting of Statisticians and the International Society for NonParametric Statistics. Key Contributions: Her book Model Selection and Model Averaging (2008) is a seminal work in statistical methodology. Her research addresses challenges in high-dimensional data, survival analysis, and model averaging, with applications in finance, insurance, and biostatistics.

• Quantum Optics
• Nanophotonics
• Solid-State Physics
• +6 more

Dr. Trong Toan Tran is a Senior Lecturer (equivalent to Associate Professor in the US) at the School of Electrical and Data Engineering , University of Technology Sydney (UTS). He leads the Nanoscale Electro-Thermo-Optical (NETO) laboratory and holds prestigious fellowships including the DECRA and UTS Chancellor's Postdoctoral Research Fellowship. His research focuses on quantum optics, nanophotonics, solid-state physics, and nanofabrication, with breakthroughs in quantum light sources and thermal sensing technologies. Dr. Tran earned his Ph.D. in Material Science and Chemical Engineering, completing a thesis on quantum emission from hexagonal boron nitride. His work in Nature Nanotechnology (2016) introduced room-temperature ultra-bright quantum emitters, now cited over 1,600 times. He has secured over $2M in grants, including leadership in the Quantum Challenge 2032 and DECRA projects. His team develops advanced photonic devices, thermal sensors, and quantum technologies. Key research themes include quantum emitters in 2D materials , nanoscale thermometry , and optical architectures . He has advised three PhD students and serves on editorial boards for top journals like Physical Review Letters and Nature Communications . Recognition includes an h-index of 34, 6,100+ citations, and awards such as the AIP Postgraduate Excellence Award (2017). Beyond academia, he engages in science communication, advocating for quantum technologies and nanomaterial applications.

Ralf BrownView profile

Researcher

• Machine Translation
• Computational Linguistics
• Digital Forensics
• +5 more

Ralf Brown is a Principal Systems Scientist at Carnegie Mellon University's School of Computer Science, affiliated with the Language Technologies Institute (LTI). His research focuses on machine translation , language identification , and digital forensics , with notable contributions like the open-source CMU-EBMT system and the LTI LangID Corpus for 2000+ languages. Academic Roles: Research faculty since 1993, teaching courses like Coding & Algorithms Bootcamp and MIIS Capstone Project . Research Interests: Multilingual processing, example-based translation, low-resource languages, and text mining. Scientific Contributions: Authored 15+ publications on EBMT, corpus indexing, and context-sensitive translation. Developed tools for digital forensics (corrupted ZIP recovery) and language identification at scale. Awards: IJCAI Distinguished Paper Award Allen Newell Award for Research Excellence Open-Source Contributions: Key developer of darktable image editor Maintainer of the Interrupt List and other technical resources