جست‌وجوی استاد و پژوهشگر

Bert Sadowskiمشاهده پروفایل

دانشیار

• Economics of Innovation
• Technological Change
• Management of Innovation
• +۴ مورد دیگر

Bert Sadowski serves as Associate Professor of Economics of Innovation and Technological Change within the Technology, Innovation & Society research group at Eindhoven University of Technology's Department of Industrial Engineering and Innovation Sciences. His academic career spans over three decades with appointments at Maastricht University, Delft University of Technology, Radboud University Nijmegen, and Victoria University of Wellington. Currently affiliated with both the Department of Industrial Engineering and Innovation Sciences and EAISI Health, he maintains an active research profile focused on digital transformation and innovation systems. MSc in Technology and Innovation Management, University of Sussex (1991) PhD from Science and Technology Policy Research Unit (SPRU), University of Sussex (1994) Sadowski's research explores the economic dimensions of technological change with particular emphasis on digital markets, open data strategies, and the Internet of Things. His work investigates how innovation processes unfold in different economic contexts, with significant attention to China's development trajectory. Current research examines blockchain governance models, the impact of ownership structures on innovation productivity, and the dynamics of technological catch-up during industry transitions. His scholarship bridges theoretical economics with practical policy implications for digital infrastructure and innovation ecosystems. Analysis of Sadowski's publication record reveals consistent focus on innovation economics with increasing attention to digital technologies since 2015. His work spans multiple methodological approaches including econometric analysis of Chinese manufacturing data, case studies of pharmaceutical companies in China, and computational modeling of technological transitions. Recent publications (2022-2025) show expanding interest in sustainability applications, energy communities, and the governance challenges of emerging technologies like blockchain. Sadowski actively contributes to academic discourse through service on editorial boards and participation in international research collaborations, particularly with Chinese institutions as evidenced by multiple co-authored papers with researchers from Chinese universities. His educational activities include teaching courses on Economic Policy in Practice, Infonomics, Governing Innovations, and Green and Digital Transformation. These courses reflect his research interests while addressing contemporary challenges in technology management and policy. Sadowski leads research within the Technology, Innovation & Society group which investigates the complex interplay between technological development, organizational change, and societal impacts. His work often involves interdisciplinary collaboration with researchers from computer science, engineering, and social sciences to address multifaceted innovation challenges.

• Robust Optimization
• Bilevel Optimization
• Explainable Optimization
• +۳ مورد دیگر

Jannis Kurtz is an Assistant Professor in Mathematical Methods and Applications in Data Science at the University of Amsterdam 's Faculty of Economics and Business, Department of Business Analytics. His research focuses on robust optimization, bilevel optimization, explainable optimization, integer optimization, machine learning, and operations research. Robust Optimization Bilevel Optimization Explainable Optimization Integer Optimization Machine Learning Operations Research Recent publications include advancements in counterfactual explanations for linear optimization, neural bilevel optimization frameworks, and data-driven robust combinatorial optimization. He organizes the Robust Optimization Webinar series and actively participates in international conferences like INFORMS, ICSP, and LION. Contact: j.kurtz@uva.nl

Mireille Boutinمشاهده پروفایل

استاد

• Applied Mathematics
• Signal Processing
• Machine Learning
• +۵ مورد دیگر

Mireille Boutin is a Professor at the Eindhoven University of Technology , affiliated with the Department of Mathematics and Computer Science within the Discrete Algebra and Geometry group. Her research spans applied mathematics, signal processing, and machine learning, with a focus on discrete inverse problems and the integration of geometric tools in probabilistic frameworks. Academic Background : She earned a Ph.D. in Mathematics from the University of Minnesota under Peter Olver, followed by postdoctoral positions at Brown University and the Max Planck Institute for Mathematics in the Sciences . Before joining TU/e, she served on the faculty at Purdue University . Research Trends : Recent publications demonstrate her interdisciplinary approach, including solutions to global positioning uniqueness problems via algebraic geometry, computer-aided qualitative data analysis in education, symmetry-breaking in acoustic path tracking, and novel clustering models for high-dimensional data. Her work often bridges theoretical mathematics with practical applications in engineering and education. Educational Contributions : She actively teaches Computational Algebra at TU/e and has collaborated on studies applying machine learning to qualitative education research, such as analyzing student explanations in programming and faculty teaching conceptions.

• Foundations of Complex Systems
• Abelian Varieties
• Finite Fields
• +۵ مورد دیگر

Valentijn Karemaker is an Assistant Professor at the Faculty of Science, Utrecht University , specializing in the Mathematical Institute under the Fundamental Mathematics sub-unit. He focuses on the Foundations of Complex Systems , with particular expertise in Abelian Varieties , Finite Fields , Galois Representations , and Isogeny Classes . His research bridges theoretical mathematics and computational methods, notably contributing to problems like Hilbert's Tenth Problem and the Gauss problem for central leaves . He has published extensively in top-tier journals and co-authored significant surveys on local-global principles. Scientific Awards : NWO-Veni Award (2019) Westerdijk Award (2021-2022) Utrecht Young Academy (2021) NWO-XL Award (2022) NWO-Vidi Award (2023) Grants and Collaborations : He has received competitive NWO awards, hosted international researchers like Chia Fu Yu and Mihran Papikian, and contributed to editorial work for the American Mathematical Society.

Rik Smitمشاهده پروفایل

پژوهشگر

• Digital Humanities
• Media Studies
• Discourse Analysis
• +۳ مورد دیگر

Rik Smit is a Researcher at the Faculty of Arts , affiliated with the Research Centre for Media and Journalism Studies (CMJS) . His work bridges Digital Humanities , Media Studies , and Discourse Analysis , focusing on how Artificial Intelligence and algorithmic memory technologies shape societal narratives and individual memory practices. Key research themes : Interdisciplinary analysis of AI in journalistic discourse Memory as a digital and sociotechnical practice Platformization of cultural and entrepreneurial activities His publications address cross-cultural discourses on AI, algorithmic memory , and early web entrepreneurship , reflecting collaborations across institutions in the Netherlands, Brazil, and the US. Activities include academic presentations at international conferences and contributions to datasets like the Devising DigiD project.

Ömür Arslanمشاهده پروفایل

استادیار

• Robotics
• Motion Planning
• Control Theory
• +۵ مورد دیگر

Ömür Arslan is an assistant professor in the Department of Mechanical Engineering at the Eindhoven University of Technology (TU/e) , affiliated with the Robotics Group and the EAISI Mobility and EAISI High Tech Systems institutes. His research focuses on the algorithmic foundations of robotics, particularly safe adaptive motion planning algorithms for robots operating around humans. Education: PhD in Electrical and Systems Engineering (2016), University of Pennsylvania MSc in Electrical Engineering (2012), University of Pennsylvania MSc in Electrical & Electronics Engineering (2009), Bilkent University BSc in Electrical & Electronics Engineering (2007), Middle East Technical University His research interests span robotics, motion planning, control theory, sensor networks, dynamical systems, optimization, machine learning , and machine perception . Recent work includes safe unicycle control, probabilistically safe corridors, and statistical coverage control of mobile sensor networks. He has received nominations for best paper awards at ICRA 2018 and WAFR 2016 . Ömür has supervised student projects such as Hancheng Min's MSc thesis on statistical coverage control and Vincent Pacelli's work on local geometry in motion planning .

Alberto De Lucaمشاهده پروفایل

استادیار

• Diffusion MRI
• Neurological Diseases
• Brain Connectivity
• +۳ مورد دیگر

Alberto De Luca is an Assistant Professor at the Image Sciences Institute, Division Imaging & Oncology, University Medical Center Utrecht. He holds a BSc in Biomedical Engineering (2011), MSc in Bioengineering (2013), and PhD (2017) from the University of Padova, Italy, where his thesis focused on non-Gaussian diffusion in the brain and skeletal muscle. His research specializes in diffusion MRI methodologies for neurological diseases and cancer, with key interests including: Fiber-specific quantification in grey/white matter Multi-center MRI data harmonization Physiological parameter estimation via inverse methods Response prediction modeling He leads projects in cerebral small vessel disease and pediatric oncology, utilizing advanced 7T MRI and AI techniques. Recent publications (2025) demonstrate strong focus on: AI-driven lesion-symptom mapping in vascular cognitive disorders Diffusion MRI harmonization across research sites Advanced tractography validation frameworks Pediatric cancer imaging biomarkers He contributes to the Translational Neuroimaging Group and International Society for Tractography, with external collaborations including Erasmus MC (Frontotemporal dementia research) and Hogeschool Utrecht (guest lecturing on brain networks).

• Artificial Intelligence
• Optimization
• Logistics
• +۹ مورد دیگر

Eduardo Anibal Lalla is an Associate Professor at the Digital Society Institute and Industrial Engineering & Business Information Systems. His research focuses on applying artificial intelligence and optimization techniques to logistics and transportation challenges, particularly in maritime and urban logistics. He has published extensively on topics such as vehicle routing, metaheuristics, and mathematical programming, contributing to advancements in intelligent transport systems and container logistics. Research Trends : Over the past decade, his work has emphasized optimization algorithms for multi-depot vehicle routing collaborative berth allocation models matheuristics for dynamic scheduling AI-driven decoupling strategies in inter-terminal transport robot stations integration in logistics networks Scientific Awards : Best algorithm in Generalized Continuous Optimization Contest (2016) EURO Excellence in Practice Finalist/Runner-up (2021) Extraordinary doctoral distinction (2017)

Bojana Rosicمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Robotics
• +۱۲ مورد دیگر

Bojana Rosic is a Full Professor specializing in Applied Mechanics & Data Analysis. Her research spans Artificial Intelligence, Machine Learning, Robotics, and Uncertainty Quantification, with a focus on integrating computational methods into mechanical systems and materials science. Key Research Areas: Machine Learning, Uncertainty Quantification, Robotics, Soft and Compliant Mechanisms, Materials Simulation. Recent Work: Contributions to neural network-based constitutive modeling for anisotropic materials, real-time control systems for robotic manipulators, and uncertainty quantification techniques using Polynomial Chaos Expansion. Collaborations: Active in interdisciplinary research with applications in energy, sustainability, and biomedical engineering. Her work emphasizes practical implementations of AI in mechanical engineering, including autonomous systems and collaborative robots (cobots). While no specific awards or educational background are detailed here, her extensive research output (68 publications) highlights her leadership in computational methods and machine learning integration.

• Blockchain
• Decentralized Systems
• Federated Learning
• +۳ مورد دیگر

J.A. Pouwelse is a Professor at the Data-Intensive Systems department within the Electrical Engineering, Mathematics and Computer Science school at Delft University of Technology . With 125 research outputs and 4 supervised works, his work focuses on Blockchain , Decentralized Systems , Federated Learning , and Peer-to-Peer Networks , particularly for Web3 applications. His recent publications analyze topics such as: Decentralized adaptive ranking Serverless federated learning Green smart contracts Search index optimization Zero-trust frameworks Notable recognition includes the LCN Best Paper Award 2021 . Research spans decentralized infrastructure design, privacy preservation, and scalable system implementation.

• Environmental Spillovers
• International Business
• Sustainability in Emerging Economies
• +۲ مورد دیگر

Nahyun Kim serves as Assistant Professor in the Department of Organization Studies at Tilburg University's Tilburg School of Social and Behavioral Sciences. Her academic role integrates research and teaching with a specialized focus on international business dynamics within emerging economies, particularly examining environmental sustainability challenges. Kim's research centers on environmental spillovers in international business contexts, investigating how foreign firms influence local firms' environmental practices in China and how institutional pressures affect multinational performance. Her work extends to supply chain management innovation through qualitative big data analytics and cross-sector partnership frameworks, with direct contributions to UN Sustainable Development Goals 12 (Responsible Consumption) and 13 (Climate Action). Her publication trajectory (2016-2025) reveals consistent methodological evolution from empirical analysis of foreign firm performance to computational approaches in supply chain theory and integrative reviews of cross-sector collaboration. Articles in top journals demonstrate interdisciplinary impact across business, environmental science, and data analytics fields, with significant citation metrics indicating scholarly influence. Kim maintains active engagement through major conferences (EGOS Colloquium, Strategic Management Society), professional development (Wharton Global Faculty Program), and hosting prominent scholars like Tima Bansal. Her collaborative research patterns suggest international grant-funded projects, though specific funding details remain unspecified in available sources.

• Acoustics
• Noise Measurement
• Microphone Array Technology
• +۵ مورد دیگر

Pieter Sijtsma serves as a Professor in the Department of Operations & Environment within Delft University of Technology's Faculty of Aerospace Engineering. His academic career spans over 15 years of specialized research in aeroacoustics, with significant contributions to microphone array technology and noise measurement methodologies. Current affiliations include active roles in the Berlin Beamforming Conference Committee and ongoing collaborations with major aerospace research entities. Professor Sijtsma's research focuses on advanced acoustic measurement techniques for aerospace applications. His work centers on beamforming algorithms , engine noise characterization , and wave propagation modeling in complex environments like wind tunnels and annular ducts. Key specialties include CLEAN-SC deconvolution methods for noise source mapping, directivity pattern analysis, and experimental validation of acoustic assessment techniques. His fingerprint reveals dominant expertise in acoustics (100%), noise measurement (97%), and microphone array technology (68%). Recent publication trends show concentrated activity in improving acoustic field assessment (2025), engine noise directivity determination (2024), and beamforming in swirling flows (2023). His work consistently addresses practical aerospace noise challenges through rigorous experimental validation and mathematical modeling, with strong emphasis on measurement accuracy and algorithmic innovation. Professor Sijtsma actively supervises research through collaborative projects, typically co-mentoring students with colleagues like Snellen and Avallone. His group maintains strong industry connections, evidenced by committee roles with the Ministry of Infrastructure and Environment and participation in international standard-setting conferences. Current projects involve EU-funded research on wind tunnel acoustic correction methods and engine noise source characterization. The research infrastructure leverages TU Delft's advanced wind tunnel facilities with specialized acoustic treatment and high-channel-count microphone arrays. Recent dataset releases confirm access to sophisticated wave propagation modeling tools and experimental validation platforms for closed-test-section environments.