Ming Cao is a Full Professor at the University of Groningen (Netherlands), holding positions in the Department of Discrete Technology and Production Automation, the Engineering and Technology Institute Groningen, and serving as Chair of the Jantina Tammes School of Digital Society, Technology and AI. His academic roles include Director of the Jantina Tammes School and membership in prestigious organizations such as the International Federation of Automatic Control (IFAC) and the European Commission’s DG CNECT. Cao’s research focuses on multi-agent systems, autonomous robotics, complex networks, and cooperative control, with applications in robotics, epidemic modeling, and biomimetic sensors. Education: PostDoc in Mechanical Engineering from Princeton University (2008), PhD in Electrical Engineering from Yale University (2007). Research Interests: Multi-agent systems, distributed decision-making, cooperative control, robotic teams, seal whisker-inspired flow sensing, and privacy-preserving control systems. Recent Trends in Articles: Recent work emphasizes co-evolutionary dynamics in social-technical systems, privacy in control systems, and biomimetic robotics. Key topics include feedback mechanisms in cooperation, hypergraph-based epidemic models, and seal whisker mechanics for underwater sensing. Awards: European Control Award (2016), Manfred Thoma Medal (2017), ERC Grant (2012). Grants: Vidi Grant from NWO (2015) for agent coordination research. Labs/Teams: Jan C. Willems Center for Systems and Control, Research Center for Data Science and Systems Complexity (DSSC). Active in editorial roles for journals like Artificial Life and Robotics and the SIAM Journal on Control and Optimization .
Pascal Mettes is a tenured Assistant Professor at the University of Amsterdam within the Informatics Institute, specializing in Artificial Intelligence. He leads groundbreaking research in hyperbolic deep learning, a field he has significantly advanced through theoretical developments and practical applications in computer vision and multimodal learning. His research focuses on three primary domains: hyperbolic vision-language models that address the hierarchical nature of language-vision relationships; hierarchical deep learning using hyperbolic embeddings that naturally accommodate exponential growth patterns; and robust deep learning in hyperbolic space that improves out-of-distribution detection and network resilience. Mettes has established himself as a leading figure in this emerging field through numerous publications at top-tier conferences including CVPR, ICCV, ICML, NeurIPS, and ICLR. His recent work demonstrates how hyperbolic geometry provides natural solutions to fundamental limitations in modern deep learning, particularly regarding hierarchical data structures that cannot be adequately represented in Euclidean space. The publication trends show increasing impact and recognition in the computer vision and machine learning communities, with multiple papers receiving oral presentations and best paper nominations. Best paper nomination ESWC25 for 'Designing Hierarchies for Optimal Hyperbolic Embedding' Finalist MM 2023 Best Open-Source Software Competition (for HypLL) Multiple reviewer awards across major conferences including CVPR, ICLR, ECCV, ICML, and NeurIPS MM 2016 Best Doctoral Student Award TRECVID 2015 Winner Multimedia Event Detection Benchmark Mettes actively mentors eight PhD students working on hyperbolic learning and related topics, while also securing significant research funding including ELLIs PhD Award, NWO ClickNL, Google Perception Academic Funding, and Data Science Centre PhD Grants. He serves in prominent academic roles as Program Chair for International Conference on Multimedia Retrieval 2026 and has organized multiple workshops on hyperbolic learning at major conferences. His leadership in establishing hyperbolic deep learning as a recognized research direction is evident through his survey paper in IJCV 2024 and the development of the HypLL library for hyperbolic learning.
Dr. Julia Kamenz is an Assistant Professor (Rosalind Franklin fellow) at the University of Groningen's Faculty of Science and Engineering, where she leads research in the Molecular Systems Biology group within the Groningen Biomolecular Sciences and Biotechnology Institute (GBB). Her work focuses on understanding the molecular mechanisms that regulate cell cycle progression and cell division. Dr. Kamenz received her undergraduate training in Biochemistry at the University of Tuebingen, completed her PhD at the Friedrich Miescher Laboratory of the Max Planck Society under Dr. Silke Hauf (defended February 2015 with highest honors), and conducted postdoctoral research at Stanford University with Prof. James E. Ferrell. Her PhD work was supported by a Boehringer Ingelheim Fonds fellowship, and her postdoc was funded by a German Research Foundation (DFG) Postdoctoral Fellowship. Her research expertise spans cell cycle regulation and dynamics, post-translational modifications, Xenopus laevis model systems, and live cell microscopy. Dr. Kamenz investigates how kinases and phosphatases intricately regulate cell proliferation and division, with particular interest in the molecular mechanisms that ensure faithful chromosome segregation during mitosis. Her recent work has revealed novel insights into mitotic checkpoint signaling, particularly in early embryonic development where these checkpoints appear to function differently than in somatic cells. Dr. Kamenz's publication record demonstrates a strong focus on the dynamics of cell cycle transitions, with recent papers appearing in high-impact journals including Nature, The Journal of Biological Chemistry, and The Journal of Cell Biology. Her research integrates experimental biochemistry, live-cell imaging, and computational modeling approaches to understand complex regulatory networks. ERC Starting Grant (November 2022) NWO Vidi Grant (July 2021) Mansour Postdoctoral Travel Award (2019) Dr. Kamenz has secured significant research funding including an ERC Starting Grant (€1.5 million) and an NWO XS grant (€50,000) for her project "What limits mitotic checkpoint signaling in the early embryo?" Her research contributes to understanding fundamental biological processes with implications for developmental biology and cancer research. She collaborates extensively within the University of Groningen and with international partners, particularly in the areas of cell cycle research and biophysical approaches to biological problems. Dr. Kamenz leads a research group focused on cell cycle regulation within the Molecular Systems Biology division of the Groningen Biomolecular Sciences and Biotechnology Institute. Her lab combines biochemical approaches using Xenopus egg extracts with live-cell imaging and computational modeling to dissect the molecular mechanisms controlling cell division.
Prof. Casper Hoogenraad is a full professor in Molecular Neuroscience at the Department of Cell Biology, Faculty of Science, Utrecht University. His research focuses on understanding how intracellular protein trafficking underlies neuronal development and function, with particular emphasis on the microtubule cytoskeleton, synaptic cargo trafficking, and synaptic plasticity. He leads an active research group within Utrecht University's Cell Biology department and collaborates extensively with other neuroscience research groups. Education: PhD, Erasmus University Rotterdam (1996-2001) Postdoc, Massachusetts Institute of Technology (2002-2005) Hoogenraad's research spans three main themes: cytoskeleton dynamics during neurodevelopment and synaptic plasticity, motor proteins and adaptors as regulators of synaptic transport, and psychiatric and neurologic disease disorders linked to intracellular transport. His work combines genetics, biochemistry, molecular, and cellular biology methods in in vitro (neuron cultures), ex vivo (brain slices), and in vivo (mice) systems, along with advanced microscopy techniques including immunofluorescent confocal microscopy, high-resolution live cell imaging, and photo-activated localization microscopy (PALM). Analysis of Hoogenraad's recent publications reveals a strong focus on microtubule organization, neuronal polarity, and the molecular mechanisms underlying synaptic function and dysfunction. His work frequently explores how disruptions in intracellular transport contribute to neurological disorders including Alzheimer's disease, schizophrenia, and autism spectrum disorders, with particular attention to the relationship between cytoskeletal organization and cargo transport in neuronal compartments. Scientific Awards and Memberships: ZonMW-VIDI (2004) European Young Investigators (EURYI) award (2005) NWO-ALW VICI (2011) ERC Consolidator grants (2013) FENS-Kavli Network of Excellence (2014) European Molecular Biology Organization (EMBO) (2015) Young Academy of Europe (YAE) (2015) IBRO Kemali Prize (2016) Hoogenraad leads a research group studying neuronal development and function, with a particular focus on how intracellular transport mechanisms contribute to both normal brain function and neurological disorders. His laboratory employs a multidisciplinary approach combining molecular, cellular, and systems neuroscience techniques to investigate the molecular basis of neuronal polarity, synaptic plasticity, and the pathogenesis of neurological disorders. He has secured significant research funding through prestigious grants including ERC Consolidator grants. The Hoogenraad lab operates within the Cell Biology department at Utrecht University, collaborating with other research groups focusing on cellular dynamics, biophysics, and neurobiology. The lab utilizes advanced microscopy techniques including immunofluorescent confocal microscopy, high-resolution live cell imaging (spinning disc microscopy and total internal reflection fluorescence microscopy), and quantitative analysis using advanced high-resolution microscopy (photo-activated localization microscopy). Current lab technicians include Phebe Wulf and Bart de Haan.
Jacob Krüger is an Assistant Professor at Eindhoven University of Technology , specializing in the development and evolution of variant-rich software systems. He holds a PhD from Otto-von-Guericke University Magdeburg (2021) and has held academic and research positions at institutions including Ruhr-University Bochum, Chalmers University of Technology, and the University of Toronto. His research focuses on the interplay between human cognition and software quality, particularly in complex systems requiring frequent adaptation. Education: PhD in Computer Science, Otto-von-Guericke University Magdeburg (2021) MSc Business Informatics, Otto-von-Guericke University Magdeburg (2016) Research Interests: Variant-Rich Systems Program Comprehension Software Product Lines Human Factors in Software Engineering Architecture Smells and Quality Assurance Articles Trends: Recent work emphasizes fork ecosystem visualization (VisFork tool), the impact of AI on scientific practices, and crisis-driven software development (e.g., Corona-Warn-App). Key themes include empirical studies, tool development, and industry collaboration. Awards: Best Dissertation Award (2022) Frank Anger Memorial Award (2019) Multiple conference best-paper and review awards Advising & Grants: Supervises 12+ PhD students across multiple institutions. Active in funding projects like INKleSS (German Research Foundation) and FOSD Meeting 2024 (NWO). Leads collaborations with ASML, Danfoss, and Axis AB. Labs/Teams: Member of the Software Engineering and Technology (SET) group at TU Eindhoven, focusing on industrial-strength software systems and cognitive aspects of development.
Mykola Pechenizkiy is a Full Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), holding the Data Mining Chair. He also serves as an Adjunct Professor in Data Mining for Industrial Applications at the University of Jyväskylä. His research focuses on predictive analytics, data mining, and responsible AI, addressing real-world challenges in industry, healthcare, and education. He leads the Customer Journey research program at the Data Science Center Eindhoven, emphasizing ethical and transparent analytics. Academically, he holds a PhD from the University of Jyväskylä (2005) and has held visiting researcher positions at institutions like Columbia University and NYU. He has co-authored over 300 peer-reviewed publications and serves on editorial boards and committees for leading conferences (e.g., AAAI, IJCAI). He is the President of the International Educational Data Mining Society (IEDMS). His research interests include concept drift adaptation, sparsity techniques in neural networks, and fairness-aware AI. He has led projects such as the TKI PPS KPN Smart Two initiative and collaborates with industries like ASML, Philips, and Rabobank. His work contributes to UN SDGs, particularly in sustainable development through AI-driven solutions. Awards: Best Demo Paper Award (IEEE ICDE 2023), Best Paper Awards (ALA 2022, LoG 2022), and SensorKDD 2009 recognition. Grants/Projects: Active projects include TKI PPS KPN Smart Two (2019–2025) and Smart One W&I TKI KPN Flagship (2018–2022). Labs/Teams: Affiliated with EAISI Health, SIKS Scientific Board, and the University of Waikato’s AI Institute.
Serge Fehr is a Senior Researcher in the Cryptology Group at CWI (Centrum Wiskunde & Informatica) in Amsterdam and a part-time Professor at the Mathematical Institute of Leiden University. His research focuses on foundational aspects of cryptology, including post-quantum cryptography, information-theoretic security, zero-knowledge proofs, and secure multiparty computation. He participates in AMSec (Amsterdam Cyber Security Center) and leads work packages in the NWO-funded HAPKIDO consortium. Education: M.Sc. in Mathematics from ETH Zürich (1998) Ph.D. in Cryptography from ETH Zürich and University of Aarhus (2003) Postdoc at Macquarie University (2003-2004) Research Interests: Post-quantum cryptographic primitives (e.g., digital signatures, lattice-based schemes) Quantum-resistant protocols (e.g., non-resignable signatures, Fiat-Shamir transforms) Foundational security proofs in the quantum random oracle model (QROM) Secure multiparty computation and privacy-preserving healthcare systems Key Activities: Editorial Board Member: Journal of Cryptology , IEEE Transactions on Information Theory Program Committee Co-Chair: EUROCRYPT 2025 Steering Committee Member: Beyond IID Information Theory, QCrypt Co-organizer: Symposium Series on Post-Quantum Cryptography Grants/Awards: NWO Cybersecurity consortium grant (HAPKIDO - 2021) NWO Veni Grant (2005) NWO Open & Free Competition Grants (2008, 2013) Students/Advising: Supervised or served on committees for over 15 Ph.D. students, including work on post-quantum signatures, MPC applications, and lattice-based cryptography. Labs/Teams: Active in CWI’s Cryptology Group and Leiden’s Mathematical Institute, collaborating with industry partners (e.g., KPN, Microsoft) in cybersecurity initiatives.
Francesca Grisoni serves as an Assistant Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), where she currently leads the Molecular Machine Learning team. She additionally holds appointments as an ICMS Core member and Associate Professor at EAISI (Eindhoven Artificial Intelligence Systems Institute), reflecting her cross-disciplinary role at the intersection of computational science and biomedical applications. Academic Background : Grisoni completed her Environmental Sciences degree and earned a Ph.D. in 2016 from the University of Milano-Bicocca, where her dissertation focused on interpretable machine learning for molecular property prediction. During doctoral studies, she conducted research at ETH Zurich's Department of Chemistry and Applied Biosciences and the U.S. EPA's National Center for Computational Toxicology. Ph.D., University of Milano-Bicocca, 2016 (Dissertation: Interpretable machine learning for molecular property prediction) Environmental Sciences, University of Milano-Bicocca Her research integrates artificial intelligence, chemistry, and biology to develop computational methods for drug discovery, emphasizing wet-lab experimental validation alongside algorithmic innovation. Key focus areas include overcoming activity cliffs in molecular machine learning, generative modeling for scaffold hopping, and AI-augmented decision-making in therapeutic development, with the ultimate goal of achieving 'better decisions faster' in drug discovery pipelines. Analysis of her recent 2025 publications reveals a concentrated trend toward chemical language models and generative deep learning frameworks, specifically addressing low-data drug discovery challenges through active learning and neural network architectures. These works bridge computer science with pharmacology, targeting bioactivity prediction, molecular representation, and enzyme design while maintaining strong ties to experimental validation. Scientific Awards : Lush Young Researcher Prize Early Career Award 2022 from the Dutch Royal Netherlands Academy of Arts and Sciences (KNAW) ERC Starting Grant (2022) Grants and Supervision : Dr. Grisoni secured the prestigious ERC Starting Grant in 2022 to advance her molecular machine learning research. Institutional records indicate she has supervised 7 students (as shown in TU/e's 'Supervised Work (7)' repository section), though specific names aren't provided in the source material. Her group maintains active industry collaborations, including past engagement with Bracco Pharmaceuticals. Laboratory and Team : The Molecular Machine Learning team operates under the ICMS and EAISI frameworks, merging computational AI development with experimental wet-lab validation. This collaborative unit focuses on fragment-based molecular design, chirality representation (evidenced by fragSMILES work), and high-throughput nanoparticle identification using machine learning, as highlighted in recent press coverage and datasets.
Professor Roland J. Pieters is a distinguished academic at Utrecht University's Faculty of Science, where he serves as a full Professor in the Department of Chemical Biology and Drug Discovery. With over two decades of experience at the institution, he has progressed from Assistant Professor (1998) to Associate Professor (2005) and ultimately to Full Professor (2010-present). His research group is internationally recognized for groundbreaking work at the intersection of carbohydrate chemistry, chemical biology, and drug discovery, with particular emphasis on developing novel therapeutic approaches against bacterial infections and pathogenic mechanisms. Full Professor, Utrecht University (2010-present) Associate Professor, Utrecht University (2005-2010) Assistant Professor, Utrecht University (1998-2005) NWO Talent Post-doctoral Fellow, ETH-Zürich (1995-1996) Postdoctoral Researcher, University of Groningen (1996-1998) Professor Pieters earned his M.Sc. in Organic Chemistry from the University of Groningen in 1990, where he worked with Professor Ben Feringa, and completed his Ph.D. at MIT in 1995 under the supervision of Professor Julius Rebek Jr. His doctoral research focused on molecular recognition and template effects in bisubstrate systems, establishing the foundation for his lifelong interest in molecular interactions. Professor Pieters' research primarily centers on glycodrugs and the strategic interference with protein-carbohydrate interactions using multivalent systems of varying architectures. His laboratory has made significant contributions to understanding how rigid spacers in multivalent ligands can dramatically enhance binding affinity to target proteins, with applications against viral and bacterial adhesion proteins, toxins, galectins, and glycosidases. A particular focus has been on developing inhibitors for Pseudomonas aeruginosa lectin LecA, cholera toxin, influenza virus hemagglutinin, and more recently, SARS-CoV-2 spike protein interactions with host cell receptors. His group also pioneered the use of glyco- and peptide-microarrays for high-throughput screening of carbohydrate-protein interactions and drug discovery, particularly in the area of O-GlcNAcylation research. The publication record of Professor Pieters demonstrates consistent innovation in the field of multivalent carbohydrate-based therapeutics. His recent work (2020-2024) shows a strategic expansion into viral pathogenesis (particularly influenza and SARS-CoV-2), immune modulation through glycan recognition, and novel approaches to vaccine development. A notable trend is the increasing sophistication of multivalent architectures, moving from simple divalent systems to tetra- and hexavalent ligands with precisely engineered spatial arrangements. His research bridges fundamental chemical principles with practical therapeutic applications, maintaining strong connections to pharmaceutical development while advancing basic science understanding of carbohydrate-mediated biological processes. Professor Pieters' scientific achievements have been recognized with prestigious awards including a Fellowship from the Royal Netherlands Academy of Arts and Sciences (KNAW) in 1999 and a VICI personal grant from the Netherlands Organisation for Scientific Research (NWO) in 2008. These competitive awards reflect the significance and innovation of his research program. He has also served on editorial advisory boards, notably as Section Editor-in-Chief for Chemical Biology in the journal Molecules (2018-2022), contributing to the scholarly community through peer review and academic leadership. Fellowship of Royal Netherlands Academy of Sciences (KNAW), 1999 VICI, personal grant, NWO, 2008 Section Editor-in-Chief Chemical Biology for Molecules (2018-2022) Throughout his career, Professor Pieters has coordinated significant research projects including the EU project POLYCARB and secured competitive funding that has sustained his innovative research program. His laboratory has fostered numerous collaborations across Europe and internationally, creating a vibrant research environment that has trained many scientists now working in academia and industry. His research on multivalent carbohydrate systems represents a sustained intellectual contribution to chemical biology with direct relevance to developing new anti-infective strategies and therapeutic approaches. Professor Pieters leads an active research group within Utrecht University's Department of Chemical Biology and Drug Discovery, situated in the David de Wied Building. His laboratory maintains strong connections with other research groups both within Utrecht University and internationally, particularly in the fields of glycobiology, infectious diseases, and drug discovery. The research environment he has cultivated emphasizes interdisciplinary approaches, combining synthetic chemistry, biophysical analysis, and biological testing to address fundamental questions in carbohydrate-mediated biological processes with therapeutic applications.
Konrad Kollnig is an Assistant Professor at Maastricht University’s Faculty of Law, specializing in the intersection of law and technology. He leads the RegTech4AI project, which combines legal and technical methods to address challenges in the AI and digital platforms sector. His academic background includes a PhD and MSc from the University of Oxford and a BSc from RWTH Aachen, with his PhD thesis winning the prestigious Stefano Rodotà Award 2024. Research focuses on market power analysis in digital platforms, ethical AI governance, and privacy-preserving technologies. He developed the TrackerControl app (200,000+ downloads) to expose app tracking practices. His work has influenced EU, OECD, US FTC, and other regulatory bodies, and been featured in Forbes, Wired, and New Scientist. Key achievements include winning the United Nations Privacy Competition 2022 and the Best Student Privacy Paper Award 2022. He holds a five-year RegTech4AI project grant (€2.1M) funding six researchers. Talks and collaborations span institutions like Georgetown University, CNIL, and the Council of Europe. His interdisciplinary approach bridges computer science, law, and policy to address systemic risks in digital ecosystems.
Nezihe Merve Gürel is an Assistant Professor in Computer Science at Delft University of Technology (TU Delft), affiliated with the Pattern Recognition & Bioinformatics Group within the Intelligent Systems Department of the Faculty of Electrical Engineering, Mathematics and Computer Science. Her research focuses on developing robust, reliable, and efficient machine learning methods with enhanced reasoning capabilities, bridging theoretical rigor and practical applications. She emphasizes data-centric approaches to improve ML systems. Education: PhD in Computer Science from ETH Zurich, MSc from EPFL (Switzerland). Research Interests: ML robustness, reliability, reasoning, data-centric ML, federated learning, and explainable AI. Her recent work includes certified robustness for retrieval-augmented models and time-efficient learning algorithms. She has contributed to the Journal of Data-centric Machine Learning Research as an executive editor and served as a reviewer for top ML conferences (NeurIPS, ICML, ICLR). She previously held roles at IBM Research, Stanford University's Human-Centered AI Lab, and Westlake Institute for Advanced Study. Her awards include the Generation Google Scholarship and Cisco Research Funding . Scientific Awards : Generation Google Scholarship (2021) Cisco Research Center University Funding Labs & Teams : She leads research in the Pattern Recognition Laboratory at TU Delft and collaborates with international institutions like Stanford and Westlake Institute for Advanced Study.
Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.
Tim Baarslag is a Senior Researcher and group leader of the Intelligent and Autonomous Systems group at CWI (The Dutch research institute for Mathematics and Computer Science). He holds the title of Professor of Mathematics of Cooperative AI at Eindhoven University of Technology and serves as a Visiting Associate Professor at Nagoya University of Technology, Visiting Fellow at the University of Southampton, and Visiting Scholar at MIT. His research focuses on automated negotiation systems for collaborative decision-making in smart energy trading, IoT, autonomous vehicles, and digital privacy. Education : MSc (cum laude) and BSc (cum laude) from Utrecht University; PhD (cum laude) from Delft University of Technology Tim pioneered the COMBINE project (NWO Vidi grant) for coordinating multi-deal negotiations and developed the widely-used Genius negotiation environment. His work appears in prestigious venues like Science Magazine , Artificial Intelligence , and MIT Technology Review . He also leads the International Automated Negotiating Agent Competition and contributes to policy through memberships in The Young Academy and Netherlands Academy of Engineering . Recent research trends emphasize multi-deal negotiation protocols (2024), preference uncertainty modeling in privacy negotiations (2022), and scalable algorithms for handling outcome spaces as large as 10²⁵⁰ possibilities. His 2023 work on search algorithms for large negotiation domains has applications in energy trading and supply chain management. Scientific Awards : Cor Baayen Young Researcher Award (2017), Springer Theses Award (2016), multiple Best Paper Awards (AAMAS 2022, WI-IAT 2015, IJCAI 2014), and recognitions as Science Talent (2018), Academic Pioneer (2020), and Young Talent (2019) As a grant recipient , Tim leads NWO Vidi project COMBINE and previously held a Veni grant for preference uncertainty research. He mentors through organizing competitions, serving on conference PCs (AAAI, IJCAI), and reviewing in top journals like Artificial Intelligence . His work bridges theory and practice through the Genius framework and real-world implementations in smart grid and vehicular platooning.
Nathan van de Wouw is a Full Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e), affiliated with ICMS, EAISI Mobility, EAISI High Tech Systems, EAISI Foundational, and EIRES. He also holds an adjunct Full Professor position at the University of Minnesota and a part-time Full Professorship at Delft University of Technology. His research focuses on dynamics and control of mechanical systems, including mechatronics, robotics, smart manufacturing, energy systems, and networked control. He has supervised over 150 students and led numerous projects funded by industry partners like ASML, Philips, and Shell. Education: M.Sc. (with Honors) in Mechanical Engineering, TU/e (1994) Ph.D. in Mechanical Engineering, TU/e (1999) Research Interests: Nonlinear systems and control Model reduction and complexity analysis Data-driven and networked control strategies Applications in high-tech systems, autonomous vehicles, and energy systems Awards: IEEE Control Systems Technology Award (2015) for variable-gain control in motion systems Grants & Projects: Lead projects on mechatronic design, lithography systems, and thermodynamic optimization Collaborations with TNO, ASML, and industrial partners Labs & Teams: Member of TU/e’s Dynamics and Control group Affiliated with EAISI (Eindhoven AI Systems Institute)
Dr. Farhad Merchant is an Assistant Professor of Innovative Computer Architecture at the Bernoulli Institute, University of Groningen, since July 2024. Previously, he served as a Lecturer (Assistant Professor) at Newcastle University (2022–2024) and held research roles at Bosch Research, NTU, and RWTH Aachen University. His research focuses on emerging technology-based computing and hardware-oriented security, including neuromorphic architectures, in-memory computing, and secure hardware design. Education: PhD in Electronics Engineering from the Indian Institute of Science, Bangalore, with a DAAD-funded visit to RWTH Aachen University. He also holds industry experience from Bosch Research. Research Interests : - Hardware Security - Neuromorphic Computing - Algorithm-Architecture Co-design - Reconfigurable Computing - Computer Arithmetic Projects : - Coordinator for the REACT project (2025–2029): Focuses on self-aware neuromorphic architectures. - Principal Investigator for Privacy-Preserving Computer Architectures (CogniGron, 2025–2029). - Completed BioNanoLock project (DFG-funded, focusing on bio-nanoelectronic security). Awards : - Best Paper Awards at ISQED 2022, NEWCAS 2023, and VLSI-DAT 2024. - Minerva Fellowship (Technion, Israel), HiPEAC Technology Transfer Award (2019). He co-founded the SeHAS workshop (since 2019) and serves on editorial and program committees for major conferences like DAC, ISLPED, and VLSI-SoC.
