Find Academic Supervisors

Guy G. DrijkoningenView profile

Associate Professor

• Applied Geophysics
• Seismic Experiments & Modelling
• Seismic Data Acquisition
• +3 more

Guy G. Drijkoningen is an Associate Professor in Applied Geophysics at Delft University of Technology (TU Delft), Faculty of Civil Engineering and Geosciences. He is actively involved in teaching and research within the Department of Applied Geophysics & Petrophysics. Education: MSc, Delft University of Technology, The Netherlands PhD, Cambridge University, UK Research Focus: His work centers on Seismic Experiments & Modelling , particularly in exploration and shallow-subsurface contexts. Key areas include: Seismic data acquisition on land Continuous seismic monitoring Shallow shear-wave imaging (land and marine) Seismic wave propagation in porous media Current projects leverage advanced sensor networks (e.g., LOFAR), full-waveform inversion for tunnel-boring machines, and novel vibrator technologies. Publications Trend: Recent works (2011–2016) emphasize seismic modeling, inversion techniques, and experimental validation across marine and terrestrial environments. Topics span poroelastic wave theory, ambient-noise interferometry, and innovative seismic source design, reflecting a blend of theoretical and applied geophysics. Scientific Awards: Best-paper award Geophysics 2015 for "A seismic vertical vibrator driven by linear synchronous motors" Professional Memberships & Editorial Roles: Member: Society of Exploration Geophysicists (SEG) Member: European Association of Geoscientists and Engineers (EAGE) Associate Editor: Geophysics Teaching: He teaches undergraduate and graduate courses including Introduction to Geophysics, Reflection Seismology, and specialized PhD-level modules on seismic data analysis.

• High-dimensional probability theory
• Data Science
• Machine Learning
• +5 more

Sjoerd Dirksen is a Professor of Mathematics for Data Sciences at Utrecht University since May 2025, having previously served as an Associate Professor for Applied Mathematics (2019-2025) and Junior Professor at RWTH Aachen University (2014-2019). He is affiliated with the Mathematical Institute within the Faculty of Science at Utrecht University, where his office is located in the Hans Freudenthal Building. His research interests focus on high-dimensional probability theory and its applications in data science, machine learning, and signal processing. Specifically, he investigates randomized data dimension reduction methods using structured random matrices, theory for deep learning including random neural networks, high-dimensional covariance estimation for wireless communication systems, and statistical postprocessing of weather forecasts in collaboration with the Royal Netherlands Meteorological Institute (KNMI). Previously, he worked on compressed sensing, sharp estimates for stochastic processes in Banach spaces, and noncommutative analysis. Analysis of his recent publications (2018-2024) reveals a strong focus on quantization effects in high-dimensional data processing, particularly one-bit compressed sensing and covariance estimation under coarse quantization. His work bridges theoretical mathematics with practical applications in signal processing, wireless communications, and meteorological forecasting, demonstrating a consistent trajectory from foundational mathematical research to applied data science problems. Dirksen's academic career shows progression from postdoctoral work at the Hausdorff Center for Mathematics in Bonn to independent research positions. His publication record demonstrates significant contributions to the mathematics of data science, with papers appearing in top journals across mathematics, statistics, and signal processing. His research combines deep theoretical insights with practical applications, particularly in the areas of dimensionality reduction and high-dimensional statistics.

Andreas Milias ArgeitisView profile

Associate Professor

• Systems Biology
• Biochemistry & Molecular Biology
• Mathematics, Interdisciplinary Applications
• +6 more

Andreas Milias Argeitis is an Associate Professor in the Faculty of Science and Engineering at the University of Groningen. He leads the Milias-Argeitis Lab within the Molecular Systems Biology research unit at the Groningen Biomolecular Sciences & Biotechnology Institute (GBB). His research focuses on integrating experimental and computational approaches to understand cellular processes, particularly the coordination between cell growth, division, and metabolic dynamics in budding yeast. Key research areas include systems biology, TOR signaling pathways, cell cycle regulation, and the application of machine learning and mathematical modeling. His lab develops advanced tools like optogenetic control systems and deep learning algorithms for cell segmentation and tracking. Recent work has revealed metabolic oscillations linked to the cell cycle and explored the role of proteins like Sch9 in TORC1-dependent signaling. Notable achievements include an NWO Vidi Grant (2018) and an ENW Science-M Grant (2023) for studying how growth drives the cell division cycle. He has over 40 peer-reviewed publications, including work in Nature Communications , Nature Metabolism , and Journal of Cell Science . His research bridges fundamental biology with technological innovations in single-cell analysis and synthetic biology. Lab activities include CRISPR/Cas9 genome editing protocols, fluorescent protein maturation studies, and the development of photo-switchable enzymes. Collaborations span biochemistry, mathematics, and engineering, reflecting his interdisciplinary approach to unraveling cellular mechanisms.

Aida Todri-SanialView profile

Professor

• Energy-Efficient Circuits
• Quantum Computing
• Neuromorphic Computing
• +4 more

Aida Todri-Sanial is a Full Professor in the Integrated Circuits group of the Electrical Engineering department at Eindhoven University of Technology (TU/e). She leads the NanoComputing Research Lab and is affiliated with the Center for Quantum Materials and Technology Eindhoven (CQMT-E), EAISI, and the Integrated Circuits group. Her research focuses on energy-efficient circuits, novel computing paradigms (e.g., 3D integration, neuromorphic computing, quantum computing), and nanotechnology-driven architectures. Education: PhD in Electrical and Computer Engineering, University of California Santa Barbara (2009) Bardeen Fellow at Fermi National Accelerator Laboratory (2009–2010) Scientist/Research Director at CNRS (2011–2021) Visiting Fellow at the University of Cambridge (2016–2017) Research Interests: Dr. Todri-Sanial’s work integrates physics and electronics to design unconventional computing systems. Key areas include: Physical design optimization for energy efficiency Oscillatory neural networks (ONNs) for edge AI Quantum computing hardware and error mitigation 3D integration and monolithic-3D architectures Nanomaterials (e.g., VO₂, MoS₂) for neuromorphic and sensing applications Awards & Grants: ERC Consolidator Grant THERMODON (2023) NWO AiNed Fellowship (2024) NWO Quantum Technology Grant (2024) CNRS Bronze Medal (2016), IBM Quantum Open Science Prize (2021), and IEEE Distinguished Lecturer (2022) Labs & Teams: Principal Investigator of the NanoComputing Research Lab Lead researcher in EAISI (Eindhoven Artificial Intelligence Systems Institute) Collaborator with global institutions (e.g., IBM, STMicroelectronics)

Alexander HirschView profile

Researcher

• Cardiac Magnetic Resonance Imaging
• Acute Coronary Syndrome
• Myocardial Infarction
• +7 more

Alexander Hirsch is a researcher at Erasmus MC, affiliated with the Department of Radiology & Nuclear Medicine and the Cardiology division. His work focuses on advanced cardiovascular imaging techniques, particularly cardiac magnetic resonance imaging (CMR) and coronary CT angiography, with applications in myocardial disease, congenital heart defects, and arrhythmias. Institution: Erasmus MC School: Department of Radiology & Nuclear Medicine Department: Cardiology Academic Rank: Researcher His research interests include Cardiac Magnetic Resonance Imaging , Acute Coronary Syndrome , Myocardial Infarction , ST Elevation , and Computed Tomography Angiography . He investigates disease mechanisms in conditions such as hypertrophic cardiomyopathy and idiopathic ventricular fibrillation, often leveraging imaging biomarkers for early detection and risk assessment. The recent publication trends indicate a strong focus on improving imaging accuracy, longitudinal patient outcomes, and the application of novel technologies like photon-counting CT and feature tracking MRI. These efforts contribute significantly to precision diagnostics in cardiology. Alexander Hirsch has supervised several research projects, as indicated by 'Supervised Work (5)' on his profile, though specific student names are not listed. He has not received any explicitly mentioned scientific awards in the provided text. He is actively involved in a research group focused on cardiovascular imaging at Erasmus MC, collaborating with experts in radiology, nuclear medicine, and clinical cardiology to advance diagnostic methodologies and patient care.

Martin J. BastiaansView profile

Associate Professor

• Signal Processing
• Fourier Optics
• Wigner Distribution
• +1 more

Martin Bastiaans is an Associate Professor specializing in signal processing systems and optical signal theory. His research focuses on time-frequency signal analysis methods like the Wigner distribution and Gabor expansions for optical communication and imaging systems. Research Focus: Signal representation in phase space, optical system modeling, and applications in coherent optics and holography. Publications: Contributions to time-frequency analysis textbooks and linear canonical transform theory, with applications in optical tomography and wave propagation.

• Nanophotonics
• Semiconductor Nanophysics
• Antenna Engineering
• +3 more

Steven J. Verwer is a Doctoral Candidate at the Resonant Nanophotonics group at AMOLF and the Photonics and Semiconductor Nanophysics group at Eindhoven University of Technology (TU/e). His work focuses on metrology targets using Fanoresonant structures. Education: B.Sc (Hons.) in Electrical Engineering (2021), dual M.Sc (Hons.) in Electrical Engineering and Applied Physics (2024) from TU/e. Current Role: Doctoral Candidate since September 2024, affiliated with TU/e and AMOLF. Verwer's research spans Nanophotonics , Semiconductor Nanophysics , and Antenna Engineering , with a focus on mmWave Technology for 6G communication. His work involves Reverberation Chamber measurements, Phased-Array Systems , and Wireless Communication protocols. Key trends in his publications include advanced Antenna Efficiency analysis, Distance Estimation methods, and Skyrmionic Structured mmWave Beam development. He is actively involved in academic collaborations and will participate in the 19th European Conference on Antennas and Propagation (EuCAP 2025) as an organiser. His affiliations include the Resonant Nanophotonics group at AMOLF and the Photonics and Semiconductor Nanophysics group at TU/e .

H.L. OfferhausView profile

Senior Lecturer

• Non-linear Optics
• Laser Technology
• Optical Characterization
• +5 more

H.L. Offerhaus is a Senior Lecturer and Department Chair in the ANP Department at the University of Twente's Faculty of Science and Technology. His research focuses on Non-linear Optics, Lasers, Optical Characterization, and Biomedical Imaging applications. He leads the Optical Sciences group and has held roles such as Chair of the EU-COST action MP112 MicroCor (2013–2015) and Chair of the governing board of the AMO section of the Dutch Physical Society (NNV). Research interests include CARS spectroscopy/microscopy, fiber lasers, holography, and near-field optics. He has supervised over 20 PhD/Master’s students, contributing to advancements in optofluidic sensors, nonlinear optical materials, and biomedical imaging technologies. Key awards include the Olympus BioScapes Prize (2009) and recognition in business plan competitions. His work spans interdisciplinary collaborations in photonics, environmental monitoring, and cancer diagnostics via extracellular vesicle analysis. He actively contributes to academic governance, serving on faculty councils and editorial boards of journals like Scientific Reports and Journal of Optics . His lab develops innovative optical sensors and microscopy techniques with applications in healthcare, environmental science, and materials engineering.

Bregje van der BoltView profile

Assistant Professor

• Climate Change
• Water Management
• Dynamic Systems
• +7 more

Dr. Bregje van der Bolt is an Assistant Professor in Water Management and Climate Change Adaptation at Wageningen University & Research. She specializes in complex systems dynamics and deep uncertainty in climate adaptation planning. Her research integrates qualitative and quantitative methods to analyze interactions between climate, water, and human systems. She employs system dynamics modeling, time series analysis, scenario planning, and co-creation approaches to develop robust adaptation frameworks. Her expertise spans climate change impacts, dynamic systems analysis, resilience engineering, and adaptation pathways. Key projects include the CASTOR initiative (enhancing resilience in river landscapes) and KLIMAP (practical climate adaptation strategies). She teaches courses like Climate Change Studies and Integrated Water Management , supervising MSc theses on topics like socio-ecological systems and adaptive policy design. Her research focuses on predicting tipping points in environmental systems, early warning signals for critical transitions, and spatial adaptation strategies for water and food security. Notable contributions include frameworks for designing climate services and user engagement methods for capacity building. Dr. van der Bolt is involved in interdisciplinary collaborations across environmental science, policy, and engineering. She actively contributes to global discussions on climate resilience and sustainable futures through initiatives like the Empower Sustainable Futures subgroup at Wageningen.

• Inverse Problems
• Variational Methods
• Total Variation Regularization
• +7 more

Jose A. Iglesias Martínez is an Assistant Professor in the Department of Applied Mathematics at the University of Twente, affiliated with the Mathematics of Imaging and AI (MIA) group within the Faculty of Electrical Engineering, Mathematics and Computer Science. He conducts research at the intersection of variational analysis, inverse problems, shape analysis, and machine learning, with a geometric perspective on regularization and optimization. University: University of Twente School: Faculty of Electrical Engineering, Mathematics and Computer Science Department: Department of Applied Mathematics Research Group: Mathematics of Imaging & AI (MIA) His research focuses on analytic and variational methods for inverse problems in imaging, particularly involving total variation and related regularization models. The geometric structure of function domains and convex geometry in minimization problems plays a central role in his work. He applies these methods to imaging, shape analysis, and machine learning, with strong mathematical foundations in PDEs, functional analysis, and optimization. The recent publications reflect a consistent focus on variational regularization, extremal point analysis, sparse optimization, and PDE-constrained problems. Key themes include total variation, TGV, nonlocal perimeters, and shape optimization, with applications in image denoising, optical flow, and fluid dynamics. His work spans both theoretical convergence analysis and algorithmic development, often with computational implementations. Scientific Awards and Recognition: Member of the Editorial Board, Numerical Functional Analysis and Optimization (since August 2023) He actively teaches in applied mathematics, including courses such as Analysis 3, Mathematics behind Data-Driven Methods, and interdisciplinary topics like Art, Mathematics and Technology. He has supervised tutorials and projects in calculus, linear algebra, and modeling. His academic training includes dual MSc degrees in Mathematics and Telecommunication Engineering from Madrid, a PhD (2015) and habilitation (2021) in Mathematics from the University of Vienna, followed by postdoctoral work at the Radon Institute in Linz. He has no listed students yet, but is actively publishing and contributing to the mathematical imaging community. He is involved in editorial work and maintains a strong publication record in top-tier applied mathematics journals.

Sylwester LatkowskiView profile

Researcher

• Integrated Photonics
• Photonics
• Semiconductor Lasers
• +3 more

Sylwester Latkowski is a University Researcher and Project Manager in the Department of Photonic Integration at Eindhoven University of Technology (TU/e), the Netherlands. He also serves as Scientific Director at the Photonic Integration Technology Center. His work focuses on integrated photonics, particularly in photonic integrated circuits (PICs), semiconductor lasers, and their applications in telecommunications, sensing, and emerging technologies. Academically, he holds M.Sc. and Eng. degrees in optoelectronics and technical physics from West Pomeranian University of Technology (Poland) and a Ph.D. from Dublin City University (Ireland), where his research centered on semiconductor mode-locked lasers and terahertz generation. He is a senior member of IEEE and the IEEE Photonics Society, actively contributing to standards and road-mapping initiatives for integrated photonics through organizations like AIM Photonics Academy and Photon Delta. His research interests include photonic integration technologies, test automation for PICs, and applications in gas sensing, optical gyroscopes, and LiDAR. He chairs technical working groups for electronic-photonic test standards and collaborates internationally on projects such as the Integrated Photonics System Roadmap (IPSR-I). His work emphasizes bridging the gap between photonics and electronics, with a focus on scalable manufacturing and standardization. Notable contributions include pioneering open standards for photonic test automation, developing widely tunable laser sources, and advancing InP-based integration platforms. His publications span topics like thermal management in electronic-photonic systems, optical alignment optimization, and narrow-linewidth ring lasers for gyroscopes. He has supervised two research projects and is involved in industry partnerships to commercialize photonic technologies. His expertise spans from fundamental research to applied engineering, reflecting his belief in the seamless integration of science and technology.

Bin ChenView profile

Researcher

• Optical Communications
• Cooperative Communications
• Information Theory
• +5 more

Bin Chen is a researcher at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e), focusing on optical communications, signal processing, and information theory. He holds a PhD from University College Dublin (2015), supported by the China Scholarship Council and Science Foundation Ireland. His roles include Postdoc positions in the Signal Processing Systems (SPS) and Electro-Optical Communication Systems (ECO) groups at TU/e, and a current guest researcher affiliation. His research emphasizes geometric shaping, coded modulation, and nonlinear channel mitigation in optical systems. Education: B.Sc. Electronic Information Science and Technology, Hefei University of Technology (2010) Ph.D. Electronics and Communications Engineering, University College Dublin (2015) Affiliations: Signal Processing Systems Group (SPS) Electro-Optical Communication Systems (ECO) Group ICT Lab Research interests include optical communication systems, cooperative communications, channel coding, and network coding. Key achievements include over 60 peer-reviewed publications and awards such as the Asia Communications and Photonics Conference Best Paper Awards (2018, 2022). He has contributed to projects like PATRIOT (coded modulation optimization) and NLCAP (nonlinear capacity maximization in optical channels). Grants and collaborations span EU-funded initiatives and industry partnerships. His work on multidimensional constellations and fiber nonlinearity models has advanced long-haul transmission systems. Current projects explore neural network-based demappers and hybrid decoding techniques.

Paolo GorgiView profile

Associate Professor

• Score-driven time series models
• Stochastic processes
• Forecasting economic variables
• +3 more

Dr. Paolo Gorgi is an Associate Professor at the Department of Econometrics and Data Science in the School of Business and Economics at Vrije Universiteit Amsterdam. He holds a PhD in Statistics and Econometrics from the Joint Degree Program of the University of Padova and Vrije Universiteit Amsterdam (2017). His research focuses on score-driven time series models, stochastic processes, forecasting economic variables, and statistical inference in non-linear dynamic models. He is also a Partner at ACMetric B.V. since 2021. His work contributes to UN Sustainable Development Goals related to economic growth and sustainable cities. Key research interests include developing novel methodologies for time series analysis, particularly in handling non-linear dynamics and high-dimensional data. He has authored over 36 publications, including influential works on score-driven models, copula-based count models, and robust statistical estimation techniques. Teaching responsibilities include courses on Data Science Methods and Financial Econometrics . His research network spans collaborations with institutions globally, focusing on econometric applications in finance, macroeconomics, and sports analytics. He has supervised two PhD theses and actively contributes to the academic community through editorial roles and conference participation.

• Cardiovascular Imaging
• Radiology
• Nuclear Medicine
• +7 more

Ricardo Budde is a Full Professor in the Department of Radiology & Nuclear Medicine at Erasmus MC, Faculty of Medicine. His work is centered on advanced cardiovascular imaging techniques, integrating radiological and nuclear medicine methodologies to improve diagnosis and monitoring of heart and vascular diseases. His research focuses on cardiovascular imaging , particularly in cardiac MRI , coronary CT angiography , and hybrid PET-CT applications. Key areas include aortic valve disease, abdominal aortic aneurysm progression, and post-interventional imaging in heart transplant and stent patients. He employs cutting-edge technologies such as photon-counting detector CT and phase-contrast MRI to enhance image accuracy and diagnostic value. The recent publication trends show a strong emphasis on image quality optimization , quantitative disease monitoring , and non-invasive diagnostic validation . His work frequently explores the technical and clinical aspects of novel imaging modalities, aiming to reduce unnecessary surveillance and improve patient outcomes. While no specific awards are listed in the provided text, his extensive research output and frequent collaborations suggest recognition within the academic and clinical imaging communities. Dr. Budde supervises academic work, as indicated by 12 supervised items in his profile, and actively contributes to peer-reviewed journals. His research is supported by a broad network of clinical and technical collaborators across Erasmus MC and beyond. He is actively involved in a research environment focused on innovative cardiovascular imaging , working within multidisciplinary teams that bridge radiology, cardiology, and medical physics to advance diagnostic precision.

• Pediatrics
• Pediatric Cardiology
• Congenital Heart Disease
• +7 more

W.A. Helbing is a Full Professor in the Department of Pediatrics at Erasmus MC, Faculty of Medicine. His work is centered on pediatric cardiology, particularly congenital heart diseases and advanced cardiovascular imaging techniques. His primary research interests include pediatric cardiology , congenital heart disease , cardiac magnetic resonance imaging (CMR) , and long-term outcomes in surgically repaired patients. He investigates ventricular function, pulmonary artery stiffness, and quality of life in survivors of complex cardiac repairs such as Mustard procedure and transannular patch repair. The recent articles demonstrate a consistent focus on CMR-based assessment of hemodynamic parameters, longitudinal cohort studies , and systematic evaluation of surgical outcomes. Themes include ventriculo-arterial coupling, flow measurement accuracy, and vascular stiffness in preterm and congenital heart disease populations. Dr. Helbing has supervised 21 research works, indicating an active role in mentoring students and junior researchers. Although specific grants are not listed, his extensive publication record in high-impact journals suggests sustained research funding. His collaborations span multiple institutions, with strong internal networks at Erasmus MC, particularly in cardiology and imaging. He contributes to large-scale, multi-center longitudinal studies in congenital heart disease.