Dr. Guillermo Amador is an Assistant Professor in the Experimental Zoology department at Wageningen University & Research. His research focuses on understanding how animals interact with complex environments through locomotion, adhesion, and fluid dynamics. He investigates biological systems like insects, plants, and marine organisms to inspire bio-engineered solutions for robotics, microfluidics, and material science. Amador received his PhD in Mechanical Engineering from Georgia Institute of Technology (USA), followed by postdoctoral research at the Max Planck Institute for Intelligent Systems (Germany) and a Marie Sklodowska-Curie fellowship at TU Delft (Netherlands). His expertise spans biophysics, biomaterials, and biomechanics, with a focus on self-cleaning mechanisms and bioadhesion. He collaborates with the 4TU consortium on Dutch Soft Robotics to develop bio-inspired designs. His work bridges fundamental biology with engineering applications, emphasizing interdisciplinary approaches to solve challenges in robotics and environmental science. Amador teaches courses including Biomimetics and Functional Zoology , integrating his research into education. His research highlights include studies on cuttlefish suction cups, stick insect adhesion, and pollen transport mechanisms in pollinators.
Phuong H. Nguyen is an Associate Professor at the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). He leads the digital Power & Energy Systems (digi-PES) lab, focusing on smart energy systems, distributed control, and IoT integration for future energy grids. His research addresses energy transition challenges, including microgrid optimization, flexibility markets, and data-driven grid management. Nguyen holds a PhD from TU/e (2010) and has held visiting researcher positions at Clemson University. His work contributes to UN SDG goals related to affordable and clean energy. Education: Bachelor's in Electrical Engineering, Hanoi University of Science and Technology (2002) Master's in Electrical Engineering, Asian Institute of Technology (2004) PhD in Electrical Engineering, TU/e (2010) Key Research Areas: Smart Grids and Cyber-Physical Systems Distributed Energy Resource Management Local Energy Markets and Flexibility Provision IoT and Big Data in Energy Systems Awards & Recognition: Best Paper Award SEST 2020 Projects & Grants: REACT-D: Reactive Power Management (Project Manager) Al-driven Applications to Smarten Power System Operation (Project Lead) UNIversity Campus as a Self-Regulated Network (Co-Manager) Labs & Teams: The digi-PES lab develops cyber-physical tools for energy transition, including microgrid simulations, flexibility markets, and grid resilience strategies.
Beatriz Noheda is a Full Professor of Functional Nanomaterials at the University of Groningen's Faculty of Science and Engineering, where she chairs the Solid State Materials for Electronics group at the Zernike Institute for Advanced Materials. She also serves as the founding Director of the Groningen Cognitive Systems and Materials center (CogniGron). Her academic journey began with a PhD in Physics from the Autonomous University of Madrid in 1996, followed by research positions at Brookhaven National Laboratory and various European institutions before joining Groningen through the prestigious Rosalind Franklin Fellowship program in 2004. Her research interests span the physics of functional materials with particular emphasis on ferroelectric, piezoelectric, and multiferroic thin films . She investigates the relationship between structure and functionality, focusing on nano-domain control through strain engineering and the unique properties of domain walls. Her work bridges fundamental physics with two promising application areas: piezoelectric energy harvesting for low-power electronics and the development of novel materials for neuromorphic computing . This dual focus reflects her vision of enabling the next technological revolution through materials science. Noheda's publication record shows a clear evolution from fundamental structural studies of ferroelectric materials toward cutting-edge research in hafnia-based ferroelectrics and neuromorphic computing materials. Her most recent work focuses on oxygen migration in hafnium-zirconium oxide systems, metal-insulator transitions in nickelates, and the development of novel ferroelectric phases suitable for next-generation electronic devices. These publications demonstrate her leadership in advancing the field from basic understanding toward practical applications in memory devices and cognitive computing systems. Fellow of the American Physical Society (2011) - awarded for fundamental structural studies of new phases in perovskite-type ferroelectric materials and domain nanostructures IEEE Robert E. Newnham Ferroelectrics Award (2020) - for outstanding contributions to understanding giant piezoelectricity in lead zirconate titanate Member of the Netherlands Academy of Technology and Innovation (AcTI) (2022) Elected Senior member IEEE (2021) Rosalind Franklin Fellowship (2004) - enabling her successful academic career in Groningen Noheda has secured substantial research funding throughout her career, including a Rosalind Franklin Fellowship (2004-2009), VIDI-NWO Fellowship (2004-2008), TOP-NWO project on Functional Nanowalls (2007-2012), multiple Zernike Institute Dieptestrategie grants, and a significant TOP-PUNT grant (2016-2021). She has supervised numerous students and early-career researchers, contributing to the development of the next generation of materials scientists. Her leadership extends to editorial roles on prestigious journals including Science, Physical Review Applied, and npj Quantum Materials. As Director of CogniGron, Noheda leads an interdisciplinary center focused on developing materials and systems for cognitive computing. Her team combines expertise in functional oxides, nanoelectronics, and neuromorphic engineering to create novel computing paradigms inspired by the human brain. The center represents a strategic initiative at the University of Groningen to position itself at the forefront of cognitive systems research.
Professor Jasper van Wezel is a distinguished academic in the field of Condensed Matter Theory at the University of Amsterdam's Faculty of Science, where he serves as Professor in the Institute for Theoretical Physics (ITFA) within the Institute of Physics. With a career spanning over two decades, he has progressed from Assistant Professor (2014-2016) to Associate Professor (2016-2024) and currently holds the position of Professor since 2024. His academic journey began with a PhD in theoretical condensed matter physics from Leiden University in 2007, followed by prestigious fellowships at Argonne National Laboratory and Homerton College, Cambridge. PhD in theoretical condensed matter physics (cum laude), Leiden University, 2007 Master's diploma in theoretical condensed matter physics (cum laude), Leiden University, 2003 Dutch VWO Diploma (cum laude), Dalton Scholengemeenschap, Den Haag, 1997 US High School Diploma (cum laude), Sanford High School, Maine, USA, 1998 Professor van Wezel's research focuses on several interconnected areas within Condensed Matter Theory. His work explores competing instabilities in Charge Density Wave materials, including Superconductivity and Charge Order, Combined Charge and Orbital Order, and Transition-metal dichalcogenides. He has made significant contributions to Topology in Condensed Matter, particularly examining the Role of crystal symmetries and Topology in non-Hermitian systems. A major theme in his research involves investigating the Connections between Quantum and Classical behaviour, with special emphasis on Spontaneous Symmetry Breaking both in equilibrium (The role of the Thin Spectrum) and dynamically (Spontaneous loss of Unitarity). Analysis of Professor van Wezel's recent publications reveals a strong focus on quantum phenomena in condensed matter systems, with particular attention to topological aspects, symmetry breaking, and connections to fundamental physics concepts like black hole thermodynamics. His work often bridges theoretical concepts with potential experimental realizations, as evidenced by studies on electron patterns in materials like TaS2 and theoretical frameworks for understanding quantum phase transitions. Bristol Physics Teaching Award (2014) Students' Award for Outstanding Teaching (2014) Fellow of the Higher Education Academy (2014) Aneesur Rahman Fellowship at Argonne National Laboratory (2010-2012) Junior Research Fellowship at Homerton College, Cambridge (2007-2010) Physics 'Discovery of the year' by Leiden University Physics department (2005) 'Onderwijsprijs Natuurkunde' teaching award (2004/2005) Professor van Wezel has secured numerous research grants including an ENW-M grant (2023), an ENW-Groot project with Leiden University (2021), and a prestigious VIDI personal grant from NWO (2014). He has supervised over 50 students at various levels, including PhD candidates, MSc students, and BSc students, fostering the next generation of physicists. His leadership extends to organizing conferences, serving on PhD committees, and holding administrative roles such as chair of the educational committee for the Dutch Research School in Theoretical Physics. His research group at the University of Amsterdam's Institute for Theoretical Physics maintains active collaborations with institutions worldwide, including Leiden University, University of Cambridge, University of Bristol, and research centers in France, Germany, and Poland. The group's work combines analytical theoretical approaches with computational methods to tackle fundamental questions in quantum condensed matter physics.
Dr. Prasanth Venugopal is an Associate Professor specializing in Power Electronics with a focus on advanced energy transfer systems and battery technology. His research spans wireless power transfer, electric vehicle charging, and electrochemical impedance spectroscopy for battery diagnostics. Primary research areas: Wireless Power Transfer (100%), Harmonics (88%), Inductive Power Transfer (87%), Battery Engineering (48%) Recent publications demonstrate expertise in transformerless converter designs, multi-level architectures, and AI-driven battery capacity estimation. He has pioneered meander coil topologies for harmonic mitigation and developed computation-light models for battery aging analysis. His work includes collaborations on Li-ion battery degradation, onboard chargers for electric vehicles, and hybrid power systems for electric aircraft. Despite significant output in IEEE Transactions, no explicit awards or student mentoring data appears in the provided texts.
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.
Dr. Martin Rohde is a Professor and Group Leader at the Radiation Science & Technology department within the Faculty of Applied Sciences at Delft University of Technology (TU Delft) in the Netherlands. He leads the Transport Phenomena & Nuclear Applications research group, focusing on advanced nuclear reactor technologies, particularly molten salt reactors, and their associated transport phenomena. Professor Rohde's research interests span across several critical areas in nuclear engineering and fluid dynamics. His work primarily focuses on understanding transport phenomena in nuclear applications, with particular emphasis on molten salt reactors for sustainable and safe nuclear power generation, innovative production techniques of medical isotopes, and advanced energy storage systems like flow batteries. His research group actively investigates complex physical phenomena occurring under extreme conditions such as high pressures, high temperatures, and interactions with radioactive processes. His publication record demonstrates a strong focus on computational methods for nuclear applications, particularly the Lattice Boltzmann Method (LBM), which is used to model fluid flow, heat transfer, and phase change phenomena in nuclear systems. Recent work has concentrated on freezing and melting processes in molten salt reactors, microfluidic separation techniques for medical isotopes, and advanced modeling of flow batteries. His research shows a clear progression toward increasingly sophisticated numerical methods applied to real-world nuclear engineering challenges. Professor Rohde has secured significant funding through multiple European Commission projects including ENDURANCE, MIMOSA, and ReZilient, demonstrating the international recognition of his research. He has supervised numerous PhD and MSc students, many of whom have gone on to complete theses on topics related to molten salt reactors, microfluidics, and flow battery technology. His research group includes several technicians, post-doctoral researchers, and PhD candidates working collaboratively on cutting-edge nuclear technology. The Transport Phenomena & Nuclear Applications laboratory operates several specialized facilities including the ESPRESSO facility for measuring melting and solidification under convective boundaries, and experimental setups for studying molten salt behavior, microfluidic purification, and flow battery technology. The group maintains strong collaborations with international partners including TRIUMF (Canada), NRG, and URENCO (The Netherlands).
Dr. Ben Harvey is an Associate Professor (with Ius Promovendi) in the Perception Group of the Department of Experimental Psychology at Utrecht University, Netherlands, within the Faculty of Social and Behavioural Sciences. He is based at the Helmholtz Institute and can be contacted at b.m.harvey@uu.nl. Harvey completed his DPhil at Oxford University with Professor Oliver Braddick in 2009, followed by postdoctoral work with Professor Serge Dumoulin at Utrecht. In 2015, he moved to Coimbra on a starter grant from the Portuguese Foundation for Science and Technology before returning to Utrecht in 2016 as an Assistant Professor. He was promoted to Associate Professor in 2019 and has led his own research group since 2015. Harvey's research focuses on characterizing sensory and cognitive systems in the human brain, particularly neural responses and computations within these systems. His work combines cutting-edge neuroimaging approaches with computational modeling and behavioral experiments. Initially studying the early visual system as a model of neural processing, he extended invasive animal neurophysiological approaches to non-invasive human neuroimaging. His recent work investigates neural responses underlying cognition in the human association cortex, examining how visual space and number processing differs between cultures and in clinical disorders. His fingerprint reveals expertise in Functional Magnetic Resonance Imaging, Numerosity, Receptive Field, Visual Cortex, Population Receptive Field, Nerve Potential, Early Visual Cortex, and Topographic Maps. His publication record demonstrates significant impact, with works like 'Topographic representation of numerosity in the human parietal cortex' (2013) receiving over 360 citations. His research spans visual neuroscience, with emphasis on how the brain processes visual information, attention mechanisms, and numerical cognition, revealing generalized quantity processing systems in the human brain. Award for highest-rated abstract (2013) Brain Centre Rudolph Magnus Research Award (Best Paper of the Year) (2014) Causal link between cortical organization and conscious perception: human fMRI and electrophysiology (2009, 2010) Harvey has been actively engaged in knowledge dissemination, with multiple invited talks at institutions including INSERM in Paris (2016) and the University of Parma (2015). His research has received significant media attention, with interviews on National Public Radio (NPR) USA, Livescience.com, and Science Magazine in 2013. Beyond academic publications, he writes popular science articles exploring the relationship between visual neuroscience and visual arts. As part of the Helmholtz Institute Experimental Psychology research program, Harvey collaborates widely to investigate visual space and number processing across different populations, contributing to our understanding of how these cognitive functions vary between cultures and in clinical disorders.
Ivana Nikoloska is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). She is affiliated with the Center for Quantum Materials and Technology Eindhoven and BIASlab (Bayesian Intelligence and Stochastic Agents Lab). Her academic career includes prior roles as a Research Associate at King’s College London and a Visiting Researcher at Aalborg University. PhD: Monash University, Australia (2023) MSc & Dipl.-Ing.: University of Ss. Cyril and Methodius, North Macedonia Research Interests span foundational and applied machine learning, quantum computing, and information/communication engineering. Her work focuses on integrating Bayesian inference, variational methods, and quantum technologies for tasks like signal processing, channel estimation, and power control optimization. Quantum Machine Learning Bayesian Simulation-Based Inference Meta-learning for Wireless Systems Hybrid Quantum-Classical Architectures Stochastic Signal Processing Quantum Sensing & Metrology Notable Trends in Publications include quantum recurrent neural networks with adaptive gating, Bayesian frameworks for quantum sensing, and meta-learning applications in communication systems. She explores variational inference for planning and robust algorithms for channel estimation under non-ideal conditions.
Prof. Freek J. Beekman is a Full Professor and head of the Biomedical Imaging section within the Department of Radiation Science & Technology at Delft University of Technology (TU Delft), Faculty of Applied Sciences. He is a leading figure in biomedical imaging, with extensive contributions to nuclear imaging technologies, including SPECT, PET, and CT. His research spans detector development, image reconstruction algorithms, hybrid photonic imaging, and the application of artificial intelligence in medical imaging. Research Interests: His work focuses on advancing imaging modalities through innovations in hardware (e.g., multi-pinhole collimators) and software (e.g., deep learning for attenuation correction). He has pioneered ultra-high-resolution imaging systems, particularly for preclinical and clinical SPECT, and has developed integrated platforms like U-SPECT-BioFluo. His recent research explores glymphatic delivery of nanoparticles, infection imaging, and AI-driven reconstruction techniques, reflecting a strong translational focus. Publication Trends: His most recent publications (2021–2023) emphasize deep learning in SPECT, multi-isotope imaging, high-resolution ex vivo systems, and applications in neuroimaging and oncology. The articles demonstrate a consistent focus on improving image quality, resolution, and clinical utility through physics-informed and AI-enhanced methods. Scientific Awards: NWO Physics Valorization Prize Innovation of the Year Award by the World Molecular Imaging Society (2015, 2018) Edward Hoffman Memorial Award (2017) Bruce Hasegawa Memorial Award (2021) FOM Valorization Award (2013) TU Delft Entrepreneurial Award (2010) Advising and Grants: While specific student names are not listed, his leadership in large collaborative projects and supervision of numerous publications suggests active mentoring. He has secured significant funding through national and international grants, evidenced by his invention of over 20 patent families and successful technology transfer. His founding and leadership of MILabs BV (sold to Rigaku) highlights his impact on commercialization and industry-academia collaboration. Labs and Teams: He leads the Biomedical Imaging research group at TU Delft, which develops cutting-edge imaging systems such as VECTor (SPECT-PET) and EXIRAD-HE. His teams have produced technologies used globally in academic and pharmaceutical research, contributing to tracer development and therapeutic innovation.
George Vosselman is a Full Professor at the University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), specializing in Geo-Information Extraction with Sensor Systems. Educated with honours at Delft University of Technology (1986) and PhD in Photogrammetry from Rheinische Friedrich Wilhelms University of Bonn (1991), he has held academic roles at the University of Stuttgart, University of Washington, and Delft University of Technology (1993–2004). Since 2004, he has been a key figure at ITC, serving as department head (2012–2018, 2023–). Education: Delft University of Technology (BSc with honours, 1986), Rheinische Friedrich Wilhelms University of Bonn (PhD with honours, 1991) His research focuses on leveraging sensor technology advancements for large-scale geo-information production. Key expertise includes quality analysis of laser altimetry data, point cloud segmentation/classification, 3D building/road modeling, and model-driven imagery analysis. He has published over 220 papers and co-edited the textbook Airborne and Terrestrial Laser Scanning (2010). Recent work integrates deep learning with geospatial data, addressing semantic segmentation, visual question answering, and drone-based mapping. Recent publications (2025–2023) highlight trends in deep learning for remote sensing , including multimodal question answering benchmarks (HRVQA), vectorized building extraction (RoIPoly), latent diffusion for road modeling (LDPoly), and drone obstacle avoidance systems. His work bridges photogrammetry , computer vision , and robotic mapping , with applications in urban planning, disaster management, and informal settlement monitoring. Scientific Awards : Hansa Luftbild (1993), ISPRS Otto von Gruber (2000), Schwidefsky Medal (2012), Karl Kraus Medal (2012), ASPRS Fairchild Award (2015), ISPRS Fellow (2020) As an educator, Vosselman has taught photogrammetry, remote sensing, and laser scanning at Delft University of Technology and globally. He chaired the ITC Examination Board (2015–2023) and modernized geo-information education in Asia/Africa. His software for point cloud processing is commercialized in Europe, and he currently leads ISPRS working groups on point cloud methodologies. Labs/teams include the Earth Observation Science Chair Group at ITC, collaborating on UAV-based datasets (UAVid, UAVPal) and indoor laser scanning systems. Recent activities (2025) involve invited talks on pulse matching limitations in laser scanning and deep learning for point cloud classification.
Réka Szabó is an Assistant Professor at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Netherlands, since October 2022. Her academic trajectory includes a postdoctoral fellowship at Université Paris-Dauphine (2019–2022) and a Ph.D. in Mathematics (2015–2019) at the University of Groningen under Daniel Valesin. Education: B.Sc. in Mathematics, Budapest University of Technology and Economics (2008–2011) M.Sc. in Applied Mathematics, Budapest University of Technology and Economics (2011–2015) M.Sc. in Computer Science, University of Trento and Eötvös Lóránd University (2012–2014) Ph.D. in Mathematics, University of Groningen (2015–2019) Réka’s research focuses on Interacting Particle Systems and Percolation Theory , with significant contributions to understanding phase transitions, critical behavior, and stochastic dynamics in models like the Contact Process, Oriented Percolation, and Bootstrap Percolation. Her work combines rigorous mathematical analysis with applications to statistical physics and complex networks. She is actively involved in academic service, including organizing the Workshop On Randomness and Discrete Structures (WORDS 2025) and co-organizing the Probability and Statistics Seminar in Groningen. Réka teaches advanced courses such as Stochastic Processes, Interacting Particle Systems, and Mathematics and its Environment.
Anuj Pathania serves as an Assistant Professor in the Parallel Computing Systems (PCS) group within the Informatics Institute at the University of Amsterdam's Faculty of Science. His research pioneers sustainable computing systems operating under severe power, thermal, and reliability constraints, with significant contributions to energy-efficient hardware design and embedded systems. Education: PhD in Computer Science (2018), Karlsruhe Institute of Technology MSc in Computer Science (2012), National University of Singapore B.Tech in Computer Science (2009), Maharaja Agrasen Institute of Technology Pathania's research centers on low-power design and sustainable systems for constrained environments, with particular expertise in thermal management of 3D-stacked architectures and energy-efficient machine learning inference . His work bridges electronic design automation with real-world reliability challenges, developing novel power budgeting techniques like T-TSP that incorporate transient temperature effects ignored by conventional methods. Current projects include EU-funded initiatives on energy labeling for digital services, addressing ecological impacts through technological, behavioral, and legal frameworks. His publication trajectory reveals a strategic evolution toward zero-waste computing , with recent work (2023-2025) focusing on hardware-software co-design for edge AI, energy modeling across computing continua, and parameter-efficient neural adaptation. Key themes include thermal-aware scheduling for S-NUCA many-cores, cooperative processor utilization in heterogeneous systems, and sustainability metrics for digital services. Scientific Recognition: Best Paper Award Nomination at IEEE Computer Society Annual Symposium on VLSI 2023 for 3D-TTP power budgeting technique Pathania actively mentors 4 PhD students (Ehsan Aghapour, Saeedeh Baneshi, Sudam Wasala, Yixian Shen) and has successfully supervised 5 Master's theses (including Cum Laude defenses by Joris op ten Berg and Jurre Wolff). His research is supported by major grants including Energy Labels for Ecologically Sustainable Digital Services (2023-2024) and Towards Zero-Waste Computing (2021-2025), developing simulation frameworks like HotSniper and CoMeT for thermal analysis. The PCS group maintains strong industry collaborations with ARM and NVIDIA, particularly through tools like ARM-CO-UP for heterogeneous processor utilization.
Ross J. Kang is a Canadian mathematician currently serving as an Associate Professor at the Korteweg–de Vries Institute for Mathematics within the Faculty of Science at the University of Amsterdam since 2022. He is an active member of the Discrete Mathematics and Quantum Information group and the NETWORKS consortium. Previously, he held positions as Assistant/Associate Professor at Radboud University Nijmegen (2014-2022), Assistant Professor at Utrecht University (2013), and Researcher at Centrum Wiskunde & Informatica (2012-2013). His academic journey includes postdoctoral positions at Durham University (2010-2012) and McGill University (2008-2010), where he was advised by Bruce Reed and Louigi Addario-Berry. DPhil in Mathematics, University of Oxford (2008) - Thesis: 'Improper colourings of graphs', advised by Colin McDiarmid BSc (Hons) in Mathematics and Computer Science, University of Victoria (2003) - Governor General's Silver Academic Medal recipient Ross J. Kang's research focuses on probabilistic and extremal combinatorics, random discrete structures, graph coloring, geometric graphs, and algorithms. His work bridges theoretical mathematics with practical applications, exploring fundamental questions in discrete mathematics. He has made significant contributions to understanding graph coloring problems, particularly in the contexts of list coloring, distance coloring, and strong coloring. His research often employs probabilistic methods to establish bounds and structural properties in graph theory. Kang's work on the hard-core model, local occupancy method, and triangle-free graphs has advanced our understanding of the interplay between local constraints and global structure in discrete systems. Analysis of his recent publications reveals a strong emphasis on graph coloring problems, particularly list coloring variants and their extensions. His work frequently explores the relationship between graph structure (such as degree constraints, girth, or forbidden subgraphs) and coloring properties. A notable trend is his development and application of the local occupancy method to establish improved bounds for chromatic numbers in various graph classes. His research also demonstrates a consistent interest in extremal problems, seeking optimal configurations under specific constraints, particularly in the context of triangle-free graphs and geometric representations. NWO Open Competition M-1 grant entitled 'Asymptotic triangle-free structure (3Free)', 2022-2026 NWO Vidi grant entitled 'On the edge: theory and techniques at the frontiers of edge-colouring', 2017-2023 NWO Veni grant entitled 'Generalised colouring for random graph models', 2012-2015 Van Gogh travel grants (2020-2021 with Marthe Bonamy; 2016-2017 with Louis Esperet) Governor General's Silver Academic Medal (2003) Ross J. Kang has successfully supervised multiple PhD students including Eoin Hurley (defending May 2025), Stijn Cambie (defended April 2022), and François Pirot (winner of 2020 prix Charles Delorme). His research is supported by significant grants from the Netherlands Organisation for Scientific Research (NWO), including the prestigious Open Competition M-1 grant. Kang is actively involved in the academic community through his editorial role at Combinatorial Theory, co-organization of conferences like the Dutch Days of Combinatorics, and leadership in initiatives such as Innovations in Graph Theory, a diamond open access journal he helped launch in August 2023. As a member of the Discrete Mathematics and Quantum Information group at the University of Amsterdam and the NETWORKS consortium, Kang collaborates with researchers across various institutions. He has established strong international connections through his Van Gogh travel grants and participation in collaborative projects like the Sparse (Graphs) Coalition sessions. His research group focuses on theoretical aspects of discrete mathematics with connections to quantum information science, and he maintains active collaborations with researchers across Europe and North America.
