جست‌وجوی استاد و پژوهشگر

Andrea Capiluppiمشاهده پروفایل

دانشیار

• Open Source Software
• Software Development
• Software Maintenance
• +۳ مورد دیگر

Andrea Capiluppi is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, Department of Software Engineering — Bernoulli Institute. His research focuses on open source software, software development processes, natural language processing, and machine learning applications in software engineering. He holds roles including Member of the Board of Examiners and Member of the Governing Board of the Thematic Digital Competence Centre (TDCC) for NES. Research interests span open source technologies, software component analysis, software maintenance, and applying NLP to software traceability. His work bridges empirical studies with practical software engineering challenges, such as developer sentiment analysis and legacy code refactoring. He has published over 110 papers, contributing to areas like technical debt detection, code obfuscation impact, and academia-industry collaboration models. No awards are explicitly mentioned, but his leadership roles reflect academic and institutional contributions. He advises on software ecosystems and innovation dynamics, with ongoing projects involving automated software classification and traceability in DevOps environments.

• Wind Turbine Engineering
• Wind Farm Flow Control
• Wake Dynamics
• +۴ مورد دیگر

J.W. van Wingerden is a Professor at the Wind Energy Institute (DUWIND) within the Mechanical Engineering school at Delft University of Technology (TU Delft) . His work focuses on wind turbine engineering, flow control strategies, and wake dynamics optimization in wind farms. Active research in model-predictive control systems Leadership in multidisciplinary wind energy projects Development of open-source simulation tools His research explores wake dynamics , atmospheric boundary layer interactions , and data-driven modeling to enhance wind farm efficiency. Recent publications address open-source frameworks for flow control and validation studies on turbine arrays. He received the O. Hugo Schuck Prize (2023) for contributions to automatic control applications. Current projects include Active Wind Farm Cluster Wake Mixing (2024–2028), aiming to improve wake mixing and energy capture in large wind farms.

• Data Analytics
• Data Governance
• Cloud Computing
• +۷ مورد دیگر

Indika Kumara is a Researcher at Tilburg University with expertise in Data Analytics , Data Governance , and Cloud Computing . His work focuses on decentralized data architectures, privacy engineering, and machine learning applications in infrastructure-as-code analysis.

• Sleep Research
• Lucid Dreaming
• Memory Consolidation
• +۴ مورد دیگر

Dr. Martin Dresler is an Associate Professor at Radboud University, Netherlands, leading the Donders Sleep & Memory Lab at the Donders Institute for Brain, Cognition and Behaviour. His research focuses on the functions of sleep, lucid dreaming, and brain plasticity. He investigates how sleep impacts memory consolidation, cognitive processes, and neurological conditions like nightmare disorder. Dresler’s work combines neuroimaging (EEG/fMRI), wearable technologies, and citizen neuroscience to study sleep dynamics and dream mechanisms. His lab develops open-source tools for sleep research and explores applications of lucid dreaming in clinical settings. Research interests include sleep neurophysiology, dream engineering, and the neural basis of exceptional memory. He collaborates internationally on large-scale studies, such as multi-center lucid dreaming induction trials. His contributions bridge basic science and translational research, emphasizing open science practices and accessible neurotechnology. Key achievements include pioneering real-time dream communication during REM sleep and advancing methodologies for sleep stage classification using wearable EEG devices. Dresler actively advocates for reform in research funding structures and promotes interdisciplinary approaches to understanding human cognition.

• Neuromorphic Engineering
• Spiking Neural Networks
• CMOS Circuit Design
• +۳ مورد دیگر

Hugh Greatorex serves as a Researcher at the University of Groningen within the Faculty of Science and Engineering, affiliated with the Bio-inspired Circuits & Systems research group. His work centers on neuromorphic hardware design, specializing in spiking neural networks and event-based processing systems that prioritize energy efficiency and real-world applicability in robotics and embedded AI. His research spans critical areas in neuromorphic engineering: Neuromorphic Engineering Spiking Neural Networks CMOS Circuit Design Memristive Computing Event-based Vision and Audio Processing Symbolic Computation in Neural Hardware Greatorex integrates circuit design with neural algorithms to solve power efficiency challenges, frequently exploring beyond-CMOS technologies like memristors and multi-timescale neural dynamics for practical implementations. Analysis of his 14 recent publications (2022-2025) reveals a cohesive trajectory toward hybrid neuromorphic processors combining CMOS with emerging devices. Key contributions include the TEXEL and Fused-MemBrain architectures for beyond-CMOS integration, alongside advancements in event-based sensory processing and symbolic operations within spiking hardware. This work consistently bridges neural computation with symbolic AI paradigms while emphasizing scalability and robustness. No scientific awards were documented in available sources. Information regarding student advisement and research grants was not provided in the source materials. As a core member of Groningen's Bio-inspired Circuits & Systems group, Greatorex contributes to internationally collaborative projects focused on biologically inspired electronic systems for intelligent processing, with applications spanning edge AI and neural computation modeling.

Charalampos Tsoumpasمشاهده پروفایل

استاد

• Quantitative Positron Emission Tomography (PET)
• Single Photon Emission Computed Tomography (SPECT)
• Medical Imaging
• +۴ مورد دیگر

Prof. Charalampos Tsoumpas is a Full Professor in Quantification in Molecular Diagnostics & Radionuclide Therapy at the University Medical Centre Groningen (UMCG), affiliated with the Faculty of Medical Sciences. His research focuses on advancing quantitative PET and SPECT imaging, including novel reconstruction algorithms and motion correction techniques. He holds academic roles including team leader in the Crystal Clear Collaboration (CERN), editorial board memberships in journals like European Journal of Nuclear Medicine , and leadership in initiatives such as the Collaborative Computational Project Synergistic Reconstruction in Biomedical Imaging (CCP SyneRBI) . Education includes a BSc in Physics (National University of Athens), MSc in Biomedical Engineering (National Technical University of Athens), and a PhD from Imperial College London. His career includes roles at King’s College London and the University of Leeds, where he led research projects funded by the Leverhulme Trust, EPSRC, and EU grants. Research Highlights: Pioneered methods for parametric image reconstruction, developed open-source STIR software, and contributed to PET-MRI integration. His work on motion correction and scatter correction has influenced commercial systems. Notable achievements include the Rotblat Medal (2017) for impactful research in medical physics. Leadership and Mentorship: Supervised 23 PhD students, fostering open science through collaborative coding and educational resources. Maintained industrial partnerships with companies like GE Healthcare and Bruker. Current projects include the SAFIR PET-MRI preclinical scanner and LAFOV PET/CT advancements. Labs/Teams: Leads the Quantification in Molecular Diagnostics lab at UMCG, collaborates on the SAFIR project (ETH Zurich), and contributes to CCP SyneRBI for synergistic reconstruction frameworks.

• Cryptographic Hardware
• Symmetric Cryptographic Schemes
• Hardware Implementations of Cryptographic Algorithms
• +۵ مورد دیگر

Silvia Mella is an Assistant Professor in the Digital Security (DiS) group at Radboud University, Netherlands, and a member of the Cryptographic Engineering & Side-Channel Analysis (CESCA) Lab. Her research focuses on cryptographic hardware for embedded devices, including secure implementations of cryptographic algorithms and analysis of side-channel and fault attacks. She holds a PhD from the University of Milan (2018) and previously worked at STMicroelectronics (2015–2022), developing hardware accelerators for public-key cryptography. She has supervised numerous PhD and Master’s students, co-authored over 30 publications, and contributed to cryptographic standards like ASCON and Xoodoo. Her work emphasizes bridging theoretical cryptography with practical hardware security solutions. Education: Bachelor and M.Sc. in Mathematics, University of Milan, Italy PhD in Cryptography (2018), University of Milan, Italy Research Interests: Design/analysis of symmetric cryptographic schemes Hardware implementation security Side-channel and fault attack countermeasures Post-quantum cryptography Lightweight cryptographic primitives Recent Research Trends: Recent work focuses on novel code-based cryptographic constructions (ChiLow/ChiChi), low-latency pseudorandom functions (Koala), and SCA-resistant implementations of algorithms like Xoodoo and Xoodyak. Her research bridges theoretical cryptographic analysis with practical hardware vulnerabilities, often leveraging machine learning techniques for attack detection. Advising & Collaboration: Co-supervised 10+ PhD/Master students on topics like cryptographic permutations and post-quantum schemes Active in industry-academia collaborations through STMicroelectronics and PROACT projects Involved in open-source cryptographic library development Labs & Teams: Leading research in the CESCA Lab at Radboud University, focusing on cryptographic engineering and embedded system security. Collaborates with the Politecnico di Milano and STMicroelectronics on hardware security projects.

Poonacha Medappaمشاهده پروفایل

استادیار

• Open-source software development
• Project management
• Online communities
• +۳ مورد دیگر

Poonacha Medappa is an Assistant Professor in Information Systems at the Department of Information Systems and Operations Management (ISOM) within the Tilburg School of Economics and Management (TiSEM) at Tilburg University. He holds a PhD in Information Systems from HEC Paris (2014–2019) and a Post Graduate Diploma in Management from the Indian Institute of Management, Calcutta (2008–2010). Prior to academia, he worked as a Senior Business Analyst/Consultant at Cognizant Technology Solutions (2010–2013) and Design Engineer at Larsen & Toubro Limited (2006–2008). His research focuses on open-source software development, project management, online communities, and applications of machine learning in research. He has published in top journals such as Information Systems Research , Research Policy , and Decision Support Systems , and presented at conferences like the International Conference on Information Systems and Academy of Management. His work has been recognized with awards including the Best Paper Award for Creativity at the Strategic Management Society Annual Conference (2021). Medappa organizes major conferences such as the International Conference on Electronic Business (ICEB 2022, 2024) and leads the project Understanding the Negative Impact of AI on Open Source Software Development Communities (2025–2026). He actively advises PhD students and explores topics like AI’s role in software development, funding mechanisms in open-source ecosystems, and contributor behavior dynamics.

• Aramaic Studies
• Ancient Judaism
• Historical Linguistics
• +۴ مورد دیگر

ML Folmer is an Associate Professor at Vrije Universiteit Amsterdam's Faculty of Social Sciences and Humanities, specializing in Religious Sources. They concurrently serve as Universitair Docent (University Lecturer) in Aramaic at Leiden University since 1998. Their research focuses on ancient languages and religious practices, particularly Aramaic dialects, Jewish communities in the Achaemenid Empire, and linguistic interactions in antiquity. Research interests include code-switching in Elephantine Aramaic, administrative language evolution, and material culture analysis of ancient Jewish diasporas. Folmer has published extensively on topics such as Persian loanwords in Aramaic texts and the sociolinguistic context of ancient curse tablets. They have organized academic events like the IOTS 10th International Meeting (2022) and delivered key lectures on topics ranging from Hebrew-Aramaic linguistic connections to official Aramaic's historical development. Notable recognition includes the 1996 Bulthuis van Oosternieland Prize for scholarly contributions. Teaching responsibilities include leading courses on Aramaic and Biblical Hebrew at VU, covering introductory to advanced levels. Their work bridges textual analysis with archaeological evidence, offering interdisciplinary insights into ancient Near Eastern societies.

Hugo Weissbartمشاهده پروفایل

پژوهشگر ارشد

• Language Processing
• Speech Comprehension
• Cortical Oscillations
• +۴ مورد دیگر

Hugo Weissbart is a Research Fellow at the Donders Institute for Brain, Cognition and Behaviour, Radboud University, specializing in neural mechanisms of language processing and brain-computer interfacing. His work bridges cognitive neuroscience, neurotechnology, and computational linguistics. His educational background includes: PhD in Neurotechnology (2020) from Imperial College London MRes in Neurotechnology (2016) from Imperial College London MSc in Physics (2013) from Imperial College London MSc in Aerospace Engineering (2014) from ISAE-SUPAERO Research focuses on predictive language processing mechanisms across phoneme, lexical, and syntactic levels using MEG to study how slow linguistic dynamics modulate high-frequency neural activity. Current projects involve developing Brain-Computer Interfaces for communication through neural decoding of speech comprehension and auditory attention. His methodology emphasizes naturalistic stimuli analysis and cross-frequency dynamics in spoken language comprehension. Software contributions include the pyEEG library for M/EEG analysis with naturalistic stimuli and feature-PAC code for cross-frequency dynamics research. He actively develops open-source tools and created educational materials like the CNSP 2025 Workshop tutorial on non-linear temporal response function analysis. Professional activity shows consistent GitHub contributions with 184 commits in the last year, primarily in Python and Jupyter Notebook repositories related to neural decoding and EEG analysis. His ORCID (0000-0003-2820-3865) links to scholarly works in cognitive neuroscience and neuroengineering.

• Geo-information Science
• Remote Sensing
• Digital Twin
• +۷ مورد دیگر

Jascha Grübel is an Assistant Professor at the Laboratory of Geo-information Science and Remote Sensing, Wageningen University & Research. His work focuses on immersive digital twins, spatial cognition, and open-source software development for virtual environment analysis. Active in digital twin frameworks Researches spatial perception and VR/HCI Emphasizes reproducibility and open science Recent projects include AnywhereXR for real-time 3D environments and IUMENTA* for animal digital twins on open platforms. He collaborates on UAV tunnel inspection using UWB positioning technology. Specializes in affective workplace design Developed SPACE for cognitive evaluation via VR Advocates for experiment-as-code methodologies His publications highlight cross-disciplinary approaches combining geo-spatial analysis, digital twin systems, and human factors research. Current work involves creating open-source tools for immersive environments and behavioral studies in virtual infrastructure.

Nathan W. Casseeمشاهده پروفایل

پژوهشگر

• Software Engineering
• Sentiment Analysis
• Technical Debt
• +۳ مورد دیگر

Nathan W. Cassee is a University Researcher at Eindhoven University of Technology (TU/e) in the Department of Mathematics and Computer Science. His work focuses on software engineering, sentiment analysis, and technical debt prioritization, combining empirical studies with natural language processing. Education: PhD Thesis (2024) on "Sentiment in Software Engineering" Research Themes: Technical Debt, Sentiment Polarity, Software Maintainability, and Empirical Studies Recent Publications: Explore sentiment's impact on code quality, self-admitted technical debt, and security questions using empirical methods Teaching: Involved in the course "Automata, Language Theory and Complexity" (2018-2025)

• Emotion
• Interpersonal Relationships
• Psychophysiology
• +۵ مورد دیگر

Dr. Monika Donker serves as Assistant Professor in the Department of Youth and Family within Utrecht University's Faculty of Social and Behavioural Sciences. Her academic base is the Martinus J. Langeveld Building (Heidelberglaan 1, Room E2.28) in Utrecht, Netherlands. As an active researcher, she contributes to the Dynamics of Youth (DoY) initiative and leads investigations within the InTransition project focusing on parent-adolescent interactions and adolescent autonomy development. Her research expertise spans emotion dynamics, interpersonal relationships, and psychophysiological measurement techniques. Specializing in longitudinal and dynamical systems approaches, she examines teacher-student relationships, parent-child interactions, and adolescent development through multimodal methodologies including heart rate monitoring and behavioral coding. Her work integrates personality theory with developmental frameworks to understand stress responses in educational and family contexts. Analysis of her recent publications reveals strong thematic continuity in educational and developmental psychology, with increasing emphasis on pandemic-related family dynamics and physiological assessment methods. Her scholarly output demonstrates methodological sophistication through integration of self-report, observational, and physiological data streams, particularly in classroom and family settings. Professional activities include presentations at major international conferences (EARLI, SAA, ISPA), service on the PhD council of the Faculty of Social Sciences, and membership in the Educational Committee of the Interuniversity Centre of Educational Sciences (ICO). She completed a visiting research period at the University of Konstanz (Germany) under Prof. Thomas Goetz in 2018. Her technical proficiency encompasses advanced statistical software (MLwiN, Mplus, HLM, AMOS, SPSS, R) for multilevel and structural equation modeling. Current media engagements include expert commentary on teacher emotional experiences and research dissemination regarding parent-adolescent relationships during the COVID-19 pandemic.

Martijn Goordenمشاهده پروفایل

استادیار

• supervisory control theory
• synthesis-based engineering
• formal methods in control
• +۲ مورد دیگر

Martijn Goorden is an Assistant Professor at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e), Netherlands, since October 2024. He previously served as an Assistant Professor at Aalborg University (2022-2024) and was a postdoc there starting in 2020. He also serves as a senior advisor on synthesis-based engineering within Rijkswaterstaat, part of the Dutch Ministry of Infrastructure and Water Management, since 2020. Education: Ph.D. in Mechanical Engineering, Eindhoven University of Technology (2019) Martijn Goorden's research focuses on supervisory control theory, synthesis-based engineering, and formal methods in control. He is particularly interested in applying these approaches to complex systems like infrastructural systems and lithography. His work bridges theoretical foundations with practical applications, developing methodologies that can be implemented in real-world scenarios. His research often involves the development of algorithms and tools for automated controller synthesis. His recent publications demonstrate a strong focus on water management systems, particularly stormwater detention ponds, where he applies formal methods and reinforcement learning to develop optimal control strategies. His work spans both theoretical advancements in supervisory control and practical implementations in infrastructure management. The research shows a progression from foundational theoretical work to specific applications in critical infrastructure. Scientific Awards: Best Paper Award (2025) in Control Systems Technology Martijn Goorden leads the open-source Eclipse project ESCET (Eclipse Supervisory Control Engineering Toolkit), which is used both in academia and industry for developing supervisory controllers in a synthesis-based approach. As project lead, he actively contributes to the development of ESCET with new algorithms and code implementations as well as reporting and solving issues. His work with Rijkswaterstaat since 2020 demonstrates strong industry-government collaboration. He is affiliated with the Control Systems Technology group at TU/e, specifically within Group Reniers, focusing on applying formal methods to real-world control problems. His work bridges the gap between theoretical computer science and practical engineering applications, particularly in infrastructure systems.

James Townsendمشاهده پروفایل

پژوهشگر

• deep generative models
• lossless compression
• unsupervised learning
• +۴ مورد دیگر

James Townsend, also known as Jamie, is a machine learning researcher at the Amsterdam Machine Learning Lab (AMLab) within the Informatics Institute at the University of Amsterdam. He completed his PhD in 2020 at the UCL AI Centre in London under the supervision of Professor David Barber. His educational background includes a PhD in lossless compression with latent variable models from University College London, with prior research contributions to the Autograd library and early development of JAX during a Google Brain internship in 2018. Townsend's research centers on deep generative models and lossless compression, extending to unsupervised learning, approximate inference, Monte Carlo methods, optimization, and machine learning software systems. His work bridges theoretical information theory with practical implementation, particularly in neural compression techniques. He has significantly contributed to open-source tools including Autograd and JAX, demonstrating expertise in automatic differentiation systems. His publication record spans high-impact venues like NeurIPS, ICLR, and ICML, with recent work focusing on innovative compression paradigms for complex data structures including graphs and multisets. Key contributions include shuffle coding, reversible programming for compression verification, and multiset compression techniques that challenge conventional approaches. Scientific recognition includes: Best Paper Award at Deep Generative Models and Downstream Applications Workshop (2021) Townsend actively participates in the research community through invited talks at Stanford's Information Theory Forum and the Languages for Inference workshop. His collaborations span academic institutions and industry partners like Google Brain, with current work centered on advancing lossless compression through deep learning at the AMLab. He maintains an active open-source presence via GitHub (@j-towns) and technical discourse on Twitter (@_j_towns), while publishing through Google Scholar under his formal name James Townsend.