Find Academic Supervisors

Christina PapadimitriouView profile

Assistant Professor

• Smart Grids
• Integrated Grid Operation
• Renewable Energy Integration
• +7 more

Christina Papadimitriou is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), affiliated with the Intelligent Energy Systems and Electrical Energy Systems research groups. Her work focuses on smart grid operation, integrated energy systems, and grid flexibility for decarbonization. PhD and Diploma in Electrical & Computer Engineering from University of Patras Senior Researcher at National Technical University of Athens (2012-2016) System Engineer at Hellenic Distribution Network Operator (2016-2019) Special Scientist at University of Cyprus (2019-2021) Her research explores: Smart grid resilience through active asset flexibility Demand-side optimization in integrated grids Power-to-X (PtX) technology operation models Energy hub coordination with logistics fleets Multi-energy carrier synergies in residential clusters Recent work demonstrates: Grid capacity enhancement via dynamic charging strategies (IEEE Access 2024) Multi-objective PtX optimization tools (CRC Press 2025) Smart grid maturity assessment frameworks (Electric Power Systems Research 2024) She coordinates the eNeuron project under Horizon2020 and serves as peer reviewer for multiple journals.

Irena ZivkovicView profile

Lecturer

• MRI Hardware Development
• Antenna Engineering
• RF Coil Design
• +2 more

Irena Živković is a Lecturer in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), where she specializes in Integrated Circuits and leads research in MRI Hardware Development. She is affiliated with the Center for Care & Cure Technology Eindhoven, focusing on cutting-edge biomedical engineering solutions. Her work bridges antenna design, electromagnetic systems, and clinical imaging technology. Her research centers on optimizing MRI hardware for ultra-high-field (7T+) and low-field systems, with innovations in: Coaxial cable coils for enhanced signal-to-noise ratios Monopole antennas for head/spine imaging Twisted-pair transmission lines for flexible, robust array elements Dielectric materials to improve transmit efficiency Recent publications (2023-2025) demonstrate a strong focus on coil miniaturization, electromagnetic interference mitigation, and SAR reduction—critical for advancing high-resolution diagnostic imaging. She teaches specialized courses including Electromagnetic Fields in MRI and Introduction to NMR/MRI , emphasizing hardware-software integration in medical imaging systems.

• Computer Vision
• Data Science
• Machine Learning
• +7 more

Dr. Lucas Alexandre Ramos is a Lecturer and Researcher at the Professorship of Applied Sciences in Computer Vision & Data Science at NHL Stenden University of Applied Sciences. He holds a PhD in Artificial Intelligence from the University of Amsterdam (2016-2020), focusing on Representation Learning and Multimodal Data Modelling in cardiovascular diseases. His work spans clinical outcome prediction, machine learning applications in healthcare, and biomedical engineering. He currently teaches and mentors students in minor and master’s programs while leading Computer Vision research projects. Education: PhD in Artificial Intelligence, University of Amsterdam (2016-2020) Research Interests: Predictive modeling for stroke, cardiovascular diseases, and addiction interventions Multimodal data integration (clinical, imaging, and behavioral) Machine learning in clinical decision support systems Computer Vision applications in healthcare diagnostics Key Research Trends: Recent articles focus on predicting clinical outcomes using machine learning in stroke treatment, cardiovascular disorders, and digital health interventions. His work emphasizes quantitative methods (e.g., EEG/ECG analysis, angiographic imaging) and translational AI for clinical settings. Advising & Grants: While no students are listed, he mentors students through teaching roles. His research projects are funded by institutional grants, focusing on Computer Vision and medical AI applications. Labs & Teams: Active within the Professorship Computer Vision & Data Science, collaborating with biomedical institutions like the Amsterdam University Medical Center.

• Bioinformatics
• Genomics
• Metagenomics
• +5 more

Sven Warris is a researcher at BIOS Applied Bioinformatics within Wageningen University & Research. His work spans bioinformatics, genomics, and microbiome studies, with a focus on developing computational tools for genomic and metagenomic data analysis. PhD in Bioinformatics (2013-2019), Wageningen University Research Interests: Bioinformatics tool development for high-throughput data Gut microbiome analysis in insects Symbiotic virus colonization in parasitoids Metagenomic approaches to disease-suppressive soils Scientific Contributions: Developed Pacasus for palindromic sequence correction Contributed to chromosomal assembly of parasitic wasp genomes Studied gut bacteria impact on arbovirus transmission Advancing functional amplicon sequencing methodologies Projects: Microservices to connect genetic maps to (pan)genomes (2019) Low-cost high-performance biocomputing (PhD project, 2013-2019)

Volker NannenView profile

Lecturer

• Artificial Intelligence
• Robotics
• Agent-Based Simulations
• +4 more

Volker Nannen is a Lecturer in Artificial Intelligence, Linear Algebra, and Advanced Programming at University College Groningen, part of the University of Groningen. He holds a PhD from Vrije Universiteit Amsterdam (2009) and has extensive experience in academic and industrial roles. His research focuses on robotics, agent-based simulations, and traction systems for extreme environments. He has contributed to projects such as soil-friendly agricultural robotics, lunar landing pad construction, and climate change policy analysis. Education: PhD in Computer Science from Vrije Universiteit Amsterdam (2009). Research interests include autonomous systems, evolutionary algorithms, and sustainable technologies. His work spans robotics for agriculture and space exploration, with a focus on minimizing environmental impact. Notable awards include the Best Paper Award at the 2006 Genetic and Evolutionary Computation Conference. He has advised on AI curricula, served as a scientific expert for German government grants, and collaborated with institutions like NASA and the German Federal Ministry of Transport. Labs/Teams: Involved in projects through Applied Biosignals GmbH (neonatal care) and sedewa.com (soil management robotics).

Joost BartView profile

Lecturer

• Pathology
• Oncology
• Gynaeco-oncology
• +3 more

Dr. Joost Bart is a University Lecturer at the University of Groningen's Faculty of Medical Sciences, specializing in Pathology and Oncology with a focus on gynaeco-oncology. His work bridges clinical pathology, molecular diagnostics, and cancer genetics. Expertise: Gynaeco-oncology, tumor genetics, and clinical translational research Professional Roles: President of the Dutch Society for Pathology (NVVP), Member of the European Society for Pathology's Advisory Board, and key member of ovarian cancer research networks His research emphasizes improving genetic testing protocols in ovarian cancer and optimizing diagnostic workflows. He has contributed to initiatives like the Dutch Archipelago of Ovarian Cancer Research biobank and the Tumor-First genetic testing framework. Public Engagement: Active in media discussions about diagnostic backlog impacts and autopsy insights during the early COVID-19 pandemic, featured in NOS, Radio, and Television interviews (2020-2024). Recent Articles: Focus on BRCA1/2 testing efficacy, AI-assisted pathology, and immunotherapy trials in gynecological cancers Professional Networks: Leadership roles in multiple national and international pathology and oncology societies

Peter van der GulikView profile

Researcher

• Evolutionary Biochemistry
• Genetic Code Evolution
• tRNA Biology
• +3 more

Peter van der Gulik is a researcher at Centrum Wiskunde & Informatica (CWI) in Amsterdam, working in the Algorithms and Complexity department and the Information & Documentation section. His research focuses on evolutionary biochemistry, specifically the genetic code structure, tRNA biology, and eukaryogenesis. He holds a Ph.D. from the University of Amsterdam (2019), advised by Harry Buhrman, Wouter Hoff, and Dave Speijer. His work bridges computational biology and evolutionary theory, addressing questions like the origins of the genetic code and the validity of taxonomic frameworks. Key contributions include defending the three-domain system of life, analyzing tRNA gene annotations in prokaryotes, and proposing taxonomic reforms. His publications span journals like BioEssays , Biological Reviews , and RNA Biology , reflecting interdisciplinary engagement with both computational methods and biological theory. Current efforts emphasize resolving inconsistencies in evolutionary narratives through rigorous genomic analysis and historical biochemical data integration. Despite no listed awards, his work has influenced debates on foundational evolutionary concepts such as the tree of life paradigm and Linnaean taxonomy modernization. Grant details are not explicitly mentioned, but his affiliation with CWI and collaborations with institutions like Quantinuum and Oklahoma State University suggest active research partnerships.

Tanja VosView profile

Professor

• Software Testing
• Automated Testing
• Behavior-Driven Development (BDD)
• +3 more

Tanja Vos is a Full Professor at the Faculty of Science , Department of Computer Science , specializing in Software Testing , Automated Testing , and Behavior-Driven Development (BDD) . Her work extends to Gamification in Education and Artificial Intelligence (AI) in Learning Systems . Research Program: Towards High-quality and Intelligent Systems (THIS) Active in Graphical User Interface (GUI) Analysis and Test Automation Research Interests : Vos focuses on advancing software testing methodologies through AI-driven solutions , particularly in 3D game testing , chatbot applications , and gamified educational platforms . Her work bridges theoretical research with industrial implementation . Recent Article Trends : Her publications emphasize automated testing frameworks (e.g., iv4XR ), GUI regression analysis , and AI chatbots for personalized learning . Subfields include evolutionary algorithms , dynamic interface testing , and gamification mechanics . Supervision & Collaboration : Vos leads projects like TESTOMAT and AI Study Coach , collaborating with institutions such as Universidad Politecnica de Valencia .

Jin-Kao HaoView profile

Professor

• Algorithms and Analysis of Algorithms
• Optimization Theory and Computation
• Artificial Intelligence
• +2 more

Jin-Kao Hao is a Professor of Computer Science at Université d'Angers , France, and a Senior Fellow of the Institut Universitaire de France . He specializes in computational methods for large-scale combinatorial optimization problems, with applications in computer science, artificial intelligence, and computational biology. Editorial Board Member: PeerJ Computer Science Research Affiliation: LERIA Laboratory , SFR MathSTIC Research Interests: His work spans algorithms, optimization theory, artificial intelligence, and computational biology. He develops advanced techniques for solving complex combinatorial problems, including parallel exact algorithms, dynamic thresholding, and metaheuristics. Publication Trends: Recent articles focus on feedback set problems, traveling salesman variants, gene-gene interactions, and scheduling. These align with his expertise in optimization, graph theory, and computational biology applications. Scientific Awards: Senior Fellow, Institut Universitaire de France Labs & Teams: Affiliated with the LERIA Laboratory at Université d'Angers and the SFR MathSTIC research federation.

Siddhartha BhattacharyyaView profile

Professor

• hybrid intelligence
• pattern recognition
• multimedia data processing
• +10 more

Dr. Siddhartha Bhattacharyya is a Professor in the Department of Computer Science and Engineering at Christ University, Bangalore, with expertise spanning hybrid intelligence, quantum computing, and multimedia data processing. He has authored/edited 65 books and published over 300 research articles, focusing on interdisciplinary applications of machine learning and computational methods. Editorial Board Member, PeerJ Computer Science Holder of two PCT patents Active in academic leadership (organizing conference committees) His research integrates Artificial Intelligence , Computer Vision , and Quantum Computing to solve complex problems in education, healthcare, and environmental monitoring. Recent work includes multimodal student learning assessment, gas plume detection, and Metaverse applications. He leads an active academic lab focused on hybrid intelligence systems and their practical implementations. Key trends in his publications include: deep learning architectures for computer vision (YOLOv7, CNN-Transformer), quantum-inspired algorithms for graph coloring and bioinformatics, and educational technology innovations for remote learning environments. His work bridges theoretical advancements with real-world applications across diverse domains.

Nieko PuntView profile

Researcher

• Pharmacokinetics
• Pharmacokinetic Modeling
• Pharmacodynamics
• +3 more

Nieko Punt is an active researcher at the University of Groningen, specifically within the Faculty of Medical Sciences, Department of Clinical Pharmacy and Pharmacology. With numerous publications spanning pharmacokinetics, pharmacodynamics, and personalized medicine, Punt contributes significantly to clinical pharmacology research. Punt's research focuses on pharmacokinetic modeling, drug dosing optimization, and personalized therapy approaches across various therapeutic areas. Key research interests include treatment-resistant depression pharmacotherapy, inflammatory bowel disease management, pediatric pharmacology, endocrine disorders, and ADHD treatment optimization. The research integrates biomarker data with pharmacokinetic modeling to develop individualized dosing strategies. The publication record demonstrates expertise in translating pharmacokinetic principles to clinical practice across multiple therapeutic areas. Recent work has particularly focused on developing novel methods for individualizing drug dosing through pharmacokinetic-pharmacodynamic modeling approaches. Punt's scientific contributions align with UN Sustainable Development Goals related to good health and well-being, particularly through research aimed at optimizing drug therapies and improving patient outcomes. As an active researcher with multiple recent publications in high-impact journals, Punt collaborates extensively with colleagues across the University Medical Center Groningen and international institutions, contributing to advancements in clinical pharmacology and personalized medicine.

Hedderik van RijnView profile

Professor

• Temporal Cognition
• Interval Timing
• Cognitive Control
• +5 more

Hedderik van Rijn is a Professor at the Department of Psychology, University of Groningen, and chair of "Cognitive Science and Neurosciences." His research focuses on temporal cognition, exploring how time influences cognitive processing, memory, and decision-making through behavioral, neuroimaging (fMRI, EEG, MEG), and computational modeling approaches. He develops methods like the adaptive learning system SlimStampen / RuggedLearning , which personalizes fact-learning using cognitive models and is used by 800,000+ students in the Netherlands. University: University of Groningen Department: Department of Psychology Academic Rank: Professor Van Rijn's research spans computational models of interval timing, cognitive control mechanisms, and applications in education and public health. He integrates symbolic process models (ACT-R) with neurobiological data, particularly in Drosophila studies, to uncover genetic bases of temporal processing. His work on time perception has theoretical and practical implications, from understanding neural substrates to real-world applications in skill training and language processing. His recent publications highlight interdisciplinary collaborations in temporal cognition, memory dynamics, and educational technology. Key themes include the interplay between time perception and cognitive load, the development of adaptive algorithms for learning, and the neural correlates of timing and decision-making. His lab's focus on deconvolving pupillary responses and modeling multi-tasking scenarios underscores methodological innovation. Scientific Awards: VICI grant (NWO Netherlands Organization for Scientific Research) Van Rijn has supervised numerous PhD students whose work spans pronoun processing, interval timing, Bayesian optimization of learning systems, and clinical applications of timing research. He collaborates with institutions like Noordhoff Publishers and the University Medical Center Groningen, and is a founding director of SlimStampen B.V., a spin-off commercializing adaptive learning principles. His grants include NWO, Horizon 2020, and John Templeton Foundation support.

Mohammad FotouhiView profile

Assistant Professor

• Structural Health Monitoring
• Composite Materials
• Bio-inspired Structures
• +3 more

Mohammad Fotouhi is an Assistant Professor at Delft University of Technology's Faculty of Civil Engineering and Geosciences, specifically within the Materials, Mechanics, Management & Design (3MD) department. He has held academic positions at the University of Glasgow, University of the West of England, and University of Bristol, focusing on structural health monitoring and composite material development. PhD in Mechanical Engineering from Amirkabir University of Technology MSc and BSc in Mechanical Engineering from Amirkabir and Tabriz Universities His research spans bio-inspired composites , 4D printing , and smart materials , with emphasis on self-sensing , multi-functional composites , and damage detection . Recent work explores piezoelectric sensors for structural strain analysis and chaos-integrated neural networks for nonlinear regression. While no formal awards are listed, his publications demonstrate leadership in fatigue monitoring , impact damage detection , and hybrid material design . Collaborations with institutions like University of Bristol and ResearchGate profile highlight his academic network.

Yanqiu HuangView profile

Assistant Professor

• Internet of Things (IoT)
• Cyber-Physical Systems
• Embedded Systems
• +6 more

Yanqiu Huang is an Assistant Professor in Pervasive Systems, focusing on interdisciplinary research in Internet of Things (IoT), cyber-physical systems, embedded systems, wireless communication, and optimization. Their work addresses resource-constrained networks, emphasizing energy efficiency and collaborative algorithms for IoT devices. Research Interests Design of energy-efficient algorithms for IoT networks Integration of wireless communication and control systems Edge AI and sensor technologies for intelligent transport Recent Publications Key contributions include advancements in Bluetooth Low Energy (BLE) discovery, DNN task allocation for edge computing, and cyclist behavior prediction via IMU data. Research spans environmental monitoring, industrial ventilation, and smart mobility solutions like connected bicycles. Scientific Awards Best Poster Award: DNN Task Allocation for Edge-Aided IoT (2023) Best Poster Award: Smart Connected Bikes (2023) Best Presentation Award (2025) Activities Active in organizing and participating in international conferences (PerVehicle 2024/2025), hosting academic visitors (Koojana Kuladinithi, Konrad Fuger), and delivering invited talks on privacy-preserving crowdsensing.

Ana Gabriela MaguitmanView profile

Associate Professor

• Natural Language Processing
• Machine Learning
• Information Retrieval
• +8 more

Ana Gabriela Maguitman serves as Associate Professor in the Department of Computer Science and Engineering at Universidad Nacional del Sur (Argentina) and holds a Principal Researcher position at Argentina's National Council for Science and Technology (CONICET). She leads the Knowledge Management and Information Retrieval Research Group at Universidad Nacional del Sur and earned her PhD in Computer Science from Indiana University (USA). Her research spans multiple domains within artificial intelligence, with primary focus on Natural Language Processing, Machine Learning, and Information Retrieval. Specialized interests include sentiment analysis, text mining, computational linguistics, neural networks, and social computing applications. Her work demonstrates strong interdisciplinary connections between theoretical computer science and practical applications in web technologies and data science. As an active scholarly contributor, Maguitman has served as Academic Editor for 19 publications in PeerJ Computer Science while authoring 3 significant research articles through mid-2025. Her editorial work covers diverse topics including healthcare data privacy, language models, event extraction, and time-series analysis. Though no formal awards are documented in the provided materials, her substantial peer review contributions (60 reviews) and editorial leadership (3,105 contributions) demonstrate significant scholarly impact. Maguitman's research group focuses on knowledge management systems and information retrieval methodologies, with recent work exploring causal relationship inference from news and opinion data, multi-objective search optimization, and time-series causality techniques. Her ongoing projects appear to bridge theoretical AI developments with real-world applications in climate science and information systems.