Adhitya is a PhD candidate at the Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, specializing in Geo-information Processing. His research, in collaboration with The Center of Expertise in Big Geodata Science (CRIB), focuses on energy-efficiency on earth observation big data processing within cloud computing environmet. He holds an M.Sc. in Logistics Information Technology from Pusan National University, Korea (2013) with the focus on vehicle-to-vehicle wireless communication. For the past 10 years, Adhitya has worked as a lecturer and researcher at the Faculty of Computer Science, Universitas Brawijaya, Indonesia. His experience includes collaborating on national and international projects such as the Indonesia Matching Fund Project, Erasmus+ Micro-Credential, and NICT ASEAN IVO Project. Beyond his primary research, Adhitya has developed a keen interest in the intersection of cloud computing service orchestration and scientific big data processing, particularly in the geospatial domain.

Ahmad has a background in Physics and Computer Engineering at the TU Delft. He worked for several years as a software engineer at CERN in the core development team of BioDynaMo: a modular high-performance agent-based simulation platform. He later applied this software in Statistics Netherlands (CBS), where he was tasked to create an agent-based digital twin of the Dutch population to model various socio-economic behaviors. He firsthand experienced the challenges of working with sensitive data using high-performance computing resources. This experience highlighted the need for a smoother, more accessible process, inspiring him to drive improvements in infrastructure and services at SURF to facilitate research with sensitive data for others in the field. Currently, Ahmad is leading various projects at SURF that aim to support researchers in securely accessing and working with sensitive data, including medical, social, and commercial datasets.

Allan Francis Beechinor is an experienced professional, with over 20 years of technology experience, primarily known for his expertise in the field of Artificial Intelligence (AI), Quantum computing, data analytics, and digital transformation. He has an extensive background in leading and developing AI-driven technologies and solutions across various industries.

Key Areas of Experience:
1. Artificial Intelligence and Machine Learning:
o Allan F. Beechinor has a deep understanding and experience in AI and machine learning technologies. He has worked on developing and deploying
AI-driven solutions that optimize business processes, enhance decision-making, and drive innovation.

1. Data Analytics:
   o His experience includes significant work in data analytics, where he has helped organizations leverage data to gain actionable insights, improve operational efficiency, and support strategic initiatives.

2. Digital Transformation:
   o Allan F Beechinor has played a crucial role in guiding businesses through digital transformation journeys. His expertise lies in helping companies adopt new technologies and methodologies to stay competitive in the digital age.

3. Entrepreneurship:
   o He is also recognized for his entrepreneurial skills, having co-founded and led successful startups focused on AI and technology solutions. His leadership and vision have been instrumental in driving these ventures forward.

4. Leadership and Strategic Vision:
   o Allan F Beechinor has held various leadership positions, where he has demonstrated his ability to set strategic directions, build high-performing teams, and manage large-scale projects.

5. Industry Impact:
   o Through his work, Allan F Beechinor has contributed significantly to the advancement of AI and digital technologies, making a notable impact on industries such as finance, healthcare, and manufacturing.

Notable Positions:
• CEO and Co-Founder of Quantum Gen LTD and EmergeGen AI: Allan F Beechinor is the CEO Quantum Gen, a company specializing in AI-driven solutions for data driven solutions and security. Under his leadership, Quantum Gen has grown rapidly, gaining recognition for its innovative approaches to quantum computing use cases.
Achievements:
• Awards and Recognition: Allan Beechinor's work has earned him several accolades in the tech industry. He is known for his contributions to the development of AI solutions that prioritize ethical considerations and data privacy.
• Public Speaking and Thought Leadership: He is also a sought-after speaker and thought leader, often participating in conferences and panels on AI, data privacy, and the future of technology.
Educational Background:
• Allan F Beechinor has a strong educational foundation in technology and business, which has supported his career in AI and entrepreneurship. His experience has provided him with the theoretical and practical knowledge necessary to innovate and lead in his field.
Allan Francis Beechinor's experience and expertise make him a prominent figure in the AI, Quantum computing and digital transformation space, with a track record of driving significant advancements in technology and business strategy.

PhD student in the group of Zeila Zanolli in the Condensed Matter & Interfaces group at Utrecht University. My project focuses on first-principles simulation methods to study superconductor-magnet heterostructures.

Ata Onur Başkaya is currently a fourth-year PhD candidate in the Aerodynamics Group of the Faculty of Aerospace Engineering at TU Delft. In this field, he has obtained a BSc degree from METU in 2018 and an MSc degree from TU Delft in 2020. He then completed the diploma course at VKI in 2021. His current research is focused on high-fidelity numerical simulations of atmospheric entry flows with gas-surface interactions.

Athanasios Trantas is an Artificial Intelligence Research Scientist, working at TNO in the department Advanced Computing Engineering. He holds a BSc in Mathematics from University of Ioannina in Greece and a MSc in Artificial Intelligence from University of Groningen in The Netherlands. He has a 5+ year experience designing and deploying large-scale AI systems in hyperscale infrastructures for various industries. His research interests lie in Computational Intelligence, with a particular focus on advanced Decision-Making, Modelling, and Optimisation techniques.

Carlos obtained his PhD degree in Theoretical & Computational Chemistry from the University of Coimbra. His doctoral research focused on developing quantum chemistry protocols to generate high-fidelity data for molecules relevant to atmospheric and combustion chemistry. He also contributed to the development of open-source software for fitting molecular potential energy surfaces.

In 2020, Carlos joined the Laboratory for Astrophysics group at the Leiden University as a Marie Skłodowska-Curie fellow to pursue his post-doctoral studies in molecular astrophysics. During this time, he developed computational methodologies to predict the chemical reactivity, spectroscopy, and thermodynamic stability of elusive astromolecules.

With a deep passion for scientific research and software development, Carlos joined the Netherlands eScience Center in 2023 as a Research Software Engineer. His current research interests revolve around the development and application of quantum computing and machine learning algorithms to general problems in chemistry and physics.

For the past 10 years I have been a visualization advisor at SURF. During my time at SURF, I came in touch with the many categories of visualization, through many educational and research fields. The one thing that stuck out to me the most and proved to be the most useful, was creating web-based 3D visualizations. Naturally, due to curiosity, interest from our members and my affinity to 3D content, XR grew to be a part of the work I do at SURF.

Cees G.M. Snoek is a full professor in computer science at the University of Amsterdam, where he leads the Video & Image Sense Lab. Additionally, he serves as the director of three public-private AI research labs: the QUVA Lab in collaboration with Qualcomm, the Atlas Lab with TomTom, and the AIM Lab with Core42. At University spin-off Kepler Vision Technologies he acts as Chief Scientific Officer. Professor Snoek also directs the ELLIS Amsterdam Unit and is the scientific director of Amsterdam AI, a collaboration between government, academic, medical and other organisations in Amsterdam to study, develop and deploy responsible AI.

He received his M.Sc. degree in business information systems (2000) and the Ph.D. degree in computer science (2005) both from the University of Amsterdam, The Netherlands. Previously, he held roles as an assistant and associate professor at the University of Amsterdam, as well as Visiting Scientist at Carnegie Mellon University in the U.S., and Fulbright Junior Scholar at UC Berkeley. He also headed R&D at University spin-off Euvision Technologies and worked as Managing Principal Engineer at Qualcomm Research Europe.

Professor Snoek's research centers on understanding video and image content. He has published over 250 peer-reviewed book chapters, journal and conference papers, and frequently serves as an area chair of leading conferences in computer vision, machine learning, and multimedia. He is currently an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence.

More information
LinkedIn:http://nl.linkedin.com/in/cgmsnoek
Visit Cees Snoek's website: https://www.ceessnoek.info/

Claartje Barkhof is a scientist and integrator in the Advanced Computing Engineering group at TNO. Her work focuses on machine learning research, its integration into computational systems, and its application to societal use cases. She earned a master’s degree in Artificial Intelligence from the University of Amsterdam in 2021, where she also worked as a research assistant at the Institute for Logic, Language, and Computation, focusing on deep generative latent variable modeling.

Claudia is a dedicated professional who combines a passion for ICT, Big Data, and Open Science with a mission to empower researchers and institutions. As a domain manager of SURF, she leads six specialized teams addressing technical challenges in high-throughput computing, cloud computing and storage, and data management, ensuring researchers have access to the tools and expertise they need to advance scientific discovery. Claudia is actively engaged in European initiatives, including serving as co-chair of EUDAT, where she contributes to shaping collaborative solutions for data infrastructure across Europe.

Driven by the belief that nothing is impossible, Claudia is building bridges between technology and research. She thrives on creating user-centered solutions, streamlining workflows, and optimizing resources to enhance productivity and enable groundbreaking discoveries. Her leadership inspires interdisciplinary collaboration, making her a promotor in advancing Open Science and ICT innovations.

Damiano Casalino, PhD in fluid-dynamics (Turin Polytechnic) and acoustics (Ecole Centrale de Lyon) has research interests in aeroacoustics that cover frequency-domain CAA for duct acoustics and installation effects, sound propagation in sheared flows, integral methods, stochastic noise generation, advanced experimental techniques for space launcher noise, helicopter trajectory optimization, vortex-airfoil interaction noise, acoustic liners and porous treatments

Damiano is currently R&D director at Dassault Systèmes and chair of aeroacoustics in the aerospace faculty of Delft University of Technology. His main focus is on the industrial exploitation of the lattice Boltzmann method for airframe and engine noise prediction. More recently, he has started developing methodologies for Urban/Advanced Air Mobility and Wind-Energy applications. His current research goal is to integrate computational aeroacoustics in system engineering frameworks for aircraft, rotorcraft and wind-turbine community noise prediction in realistic operational scenarios.

Damiano has co-authored about seventy archival journal publications in the field of aeroacoustics, scoring an H-factor of 33. He has also co-authored 5 patents and has obtained the Aeroacoustics Award in 2023 from the Council of European Aerospace Societies.

David studied physics at LMU Munich before graduating from TU Delft working on simulating quantum networks. Since 2023 he has worked for SURF as a quantum technology advisor and is leading the QCINed testbed deployment in the Utrecht-Amsterdam area.

Dr. Ravindra Shinde is a research scientist at the University of Twente, the Netherlands. He is also the editor-in-chief and founder of The Science Dev. His research interests include computational physics, computational materials, quantum chemistry, and exascale computing.

Professor in the Physics of Fluids group on “Numerical simulations of turbulence” who strives to develop novel simulation methods to simulate turbulent flows using large eddy simulations and direct numerical simulations. Large eddy simulations simulate the dynamics of extended wind farms in turbulent atmospheric boundary layers. In contrast, direct numerical simulations of thermal convection and sheared convection are used to increase our fundamental understanding of turbulent flows. The goal is to use the simulations to improve our physical insight into turbulent flows and develop further state-of-the-art simulation methods to simulate more complicated physics. You can find more information at my website https://stevensrjam.github.io/Website/

Dr. Serkan Girgin has established and is currently leading the activities of the Center of Expertise in Big Geodata (CRIB) at Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, which is an overarching facility collecting, developing, and sharing operational know-how on the geospatial big data technologies. He performs research on big data, cloud computing, and research data management technologies, and provides advice and consultancy on adoption of these technologies for education, research, and capacity development activities. He is also an expert on the design and development of geocomputing platforms, GIS and RS applications, environmental information systems, and large-scale web applications. He has designed and developed ITC's Geospatial Computing Platform, and European Commission's Natech Database (eNatech) and Rapid Natech Risk Assessment and Mapping System (RAPID-N). He has more than two decades of research and consultancy experience in academic, private, and scientific organizations. He is an eScience Center Fellow and 2022 SURF Research Support Champion in the Netherlands.

https://linkedin.com/in/serkan-girgin

Enkhzol Dovdon is a postdoctoral researcher in the Mathematics and Computer Science department at Eindhoven University of Technology, specializing in Applied Data Science. His research focuses on the intersection of data-driven animal science and technology, leveraging AI models for the IMAGEN program to enhance livestock health, welfare, and ecological footprint. The program aims to advance animal well-being and sustainable practices through innovative software solutions.

With over 16 years of experience in IT projects, research, and teaching, he has worked as a Software Engineer and researcher at universities and companies. He has led several software and system development projects. His expertise includes high-performance computing (HPC) clusters, public cloud platforms, and AI models.

https://nl.linkedin.com/in/enkhzol-dovdon-65019b92

Evert is an assistant professor at Leiden University, where is a group leader in the Applied Quantum Algorithms (aQa) division. His research focuses on the application of machine learning techniques to quantum physics, in order to design, optimize and control quantum systems. He also researches practical benefits of quantum machine learning in the form of collaborations with industrial or governmental parties. The framework of gamification is prominent in his research group, serving as an excellent playground for developing quantum control and interpretable quantum AI questions.

My name is Francisco Vazquez de Sola. I am currently based at Nikhef (Netherlands), working within the computing group of the KM3NeT neutrino telescope. My role is to ensure the integration of the collaboration's data processing into the European Grid Infrastructure resources. Its growing annual data output will require Petabytes of storage and tens of MCPUh of computing by the end of the decade. The current KM3NeT computing solutions, based on local scientific computing clusters, cannot be scaled up to that extent. By interfacing with the maintainers of computing centers and developers of middleware software, we are developing a solution using both DIRAC and RUCIO to harness European grid resources for the collaboration.

I have previously worked as analysis coordinator for the NEWS-G collaboration at IMT-Atlantique (France), bringing together the work of scientists from across two continents. My direct contributions to the group were mainly in the domain of Monte Carlo simulations and optimization of our data processing to search for Dark Matter, culminating in World-leading results for low mass searches. This was the continuation of my work as a PhD with the group, performed at Queen's University (Canada); which also included providing collaborators with data analysis and visualization tools, as well as lab work with gas handling systems, vacuum pumps, and electronics.

Frits de Prenter is an assistant professor at the department of Aerospace Engineering of TU Delft. His research focuses on the development of computational methodologies in the field of aeroacoustics. He studied Applied Mathematics and Mechanical Engineering at the Eindhoven University of Technology and holds an PhD in Mechanical Engineering from the same university. Prior to joining TU Delft in 2022, he worked on various numerical simulation techniques as a researcher at the engineering consultancy firm Research Development Netherlands.

I’m an assistant professor at the University of Amsterdam, my research focuses on the interdisciplinary domain of high-performance multi-scale models, with the primary applications derived from biomedical research.
I maintain active collaborations with several experimentalist groups and medical professionals. I lead the development of HemoCell, the open-source high-performance cellular blood flow simulation, that enables large-scale blood simulations over hundreds of thousands of cores. I also participate in multiple national and EU projects as co-PI, Task leader and Work Package leader (e.g., National Brain Research Program, CompBioMed2, GEMINI).

Gijs van den Oord, born in Leuven (Belgium) in 1981, studied theoretical physics and mathematics at Utrecht University. After his master thesis in string theory, he did a PhD in particle physics at the Radboud University and Nikhef, during which he developed Monte Carlo simulations for weak boson scattering at the Large Hadron Collider. Subsequently, Gijs worked as a consultant in scientific software development for Alten Netherlands, primarily focusing on couplings for environmental and hydrodynamical models at Deltares. Gijs joined the Netherlands eScience Center in 2016 and has mainly been involved in research projects in weather & climate, fluid dynamics and high-energy physics using his expertise in high-performance computing, GPU acceleration and machine learning. On 1 March 2024, Gijs became the Section Head for the Natural Sciences & Engineering team.

https://www.linkedin.com/in/gijs-van-den-oord-9538b712/

Amazon
Gilles Tourpe is a technology leader with over two decades of experience in the field of High-Performance Computing (HPC). His journey began with his first work experience on a trading floor, which instilled in him a commitment to delivering practical and usable solutions for customers and partners. Prior to joining Amazon Web Services (AWS) in September 2019, Tourpe held various positions in technology companies, where he honed his expertise in HPC/HTC. At AWS, he covers multiple verticals, including Oil & Gas, Research, Automotive, Manufacturing, Financial Services, and Life Sciences, leveraging his deep understanding of the industry's needs. Gilles's passion for collaboration and partnership has been a driving force throughout his career. He represents AWS in the ETP4HPC organization (European Technology Platform for High Performance Computing), fostering cooperation within the HPC ecosystem. Additionally, he played a pivotal role in initiating the TERATEC Hackathon, a platform for developing HPC engineers. Recognizing the value of academic collaborations, Gilles has developed partnership agreements with the University of Luxembourg, enabling the Uni researchers to access latest AWS Graviton technology.

https://www.linkedin.com/in/gtourpe/

HPC Advisor at SURF and member of the LUMI User Support Team

Hizirwan Salim is XR advisor at Surf. His experience is in integrating new technologies in existing workflows. He has a background in biomedical engineering with practical experience working in an AR startup and an medical research institution.

As doctoral candidate, Jasper van de Kraats works on the theoretical analysis of strongly interacting quantum systems. Such systems are interesting since they provide a platform for realising a quantum simulator, which allows researchers to study exotic physical phenomena with high precision. Examples include Bose-Einstein condensation, fermionic cooper pairing, Efimov trimer states and emergent collective behaviour. While a strongly interacting quantum gas is often characterized by universal behaviour, independent of the precise detail of the gas, Jasper's research focuses especially on novel cases in which experiment has shown this universality to be violated. The ultracold regime is paramount to furthering our understanding of the fundamental building blocks of the natural world
More information: https://www.tue.nl/en/research/researchers/jasper-van-de-kraats

Lucas Esclapez is a Research Software Engineer at the Netherlands eScience Center. He obtained his PhD in Fluid Mechanics from INP Toulouse, France in 2015, then held post-doctoral researcher positions in the United State and France, focusing on reactive flow simulations. In 2018, he joined the Berkeley National Laboratory and took over the development of the PeleLMeX software under the umbrella of the ExaScale Computing Project, eventually transitioning to the National Renewable Energy Laboratory in 2021. Lucas joined the Netherlands eScience Center in 2023, further expanding his interests for high performance and accelerated scientific computing.

I have been a member of the Data Management Services (DMS) team at SURF since 2021, where I focus on developing and integrating data management solutions. My work primarily involves leveraging iRODS and Yoda to optimize data workflows, ensure integration with SURF’s infrastructure, and incorporate existing SURF services within iRODS.

During my PhD research on cancer therapy resistance, I experienced firsthand the data management challenges faced by researchers. In my presentation at Advanced Compute Day, I will discuss the solutions developed by DMS to bring data and compute together using SURF's infrastructure. This initiative is a collaborative effort among three groups: DMS, SURF Research Cloud, and SRAM.

Matthias Möller is Associated Professor in the Department of Applied Mathematics at Delft University of Technology. His research focusses on numerical methods for the computational analysis and optimisation of problems that are modelled by partial differential equations (PDE). He is particularly interested in the combination of classical numerical methods with modern scientific machine learning techniques. A second pillar of his research is the development of quantum and quantum-inspired numerical methods for PDE analysis and optimization.

Modhurita Mitra is a Research Engineer in the Research and Data Management Services department at Utrecht University.

She earned bachelor's and master's degrees in physics from the Indian Institute of Technology, Kharagpur in India, and a PhD in astronomy from the University of Illinois at Urbana-Champaign in the United States. She held postdoctoral positions at Rhodes University in South Africa and the University of Groningen in the Netherlands. She has extensive experience in processing, analysis, and simulation of astronomical data.

Her current work focuses on the application of generative AI in research data processing. She has demonstrated the utility of generative AI as a powerful new general-purpose technology by applying this tool to data from diverse research domains - botany, pharmaceutical sciences, economic geography, and history, to perform a wide range of complex data processing tasks - information extraction, natural language understanding, text classification, and sentiment analysis.

I am a Marie Skłodowska-Curie postdoctoral individual fellow at the Electrochemical Materials and Systems lab at TU/e (the Netherlands), exploring the role of porous electrodes in increasing the efficiency of novel electrochemical systems such as redox flow batteries, fuel cells, and CO2 electrolyzers. My expertise is in computational modeling, machine learning, and high-performance computing. My academic journey encompasses various fields of engineering sciences, including materials science, biomedical engineering, mechanical engineering, and chemical engineering, in which I focused on research themes related to computational sciences that have been applied to different disciplines.

Nicolas Renaud is the Director of Technology of the Netherlands eScience Center. He is responsible for technology developments in all the research projects of the eScience Center.  Aside from these activities, he his affiliated with the Quantum Application Lab,  a cross institution initiaive that aims at devloping near-term quantum computing applications in the public and private sector.

Nicolas Valle is an Assistant Professor at the Mechanical Engineering faculty of Delft University of Technology. His research interest are on the development of gas-evolving electrodes, with particular emphasis on the bubble detachment dynamics in water electrolysis systems. His approach is essentially computational, and heavily relies on Direct Numerical Simulations for unveiling the complex mechanisms arising from the interaction of mass, momentum, energy and charge transfer in flowing electrochemical systems. His most recent areas of activity are on the design of structure-preserving numerical methods for multiphase flows and the development of High Performance Computing numerical codes for scientific computing.

Paul Melis is senior visualization advisor in the High-Performance Computing & Visualization group at SURF, having worked at SURFsara and SARA since 2009. He provides data visualization support for HPC users on Snellius, works on visualization projects (both internal and external) and still occasionally finds the time to do some C++/Python/Javascript/Julia/ development.

Besides supporting HPC users with visualization, he spends part of his time on XR innovation for education and research, including co-organizing National XR Day and coordinating the XR Developer Network.

I work in HPC user support and development at the University of Groningen (RUG) HPC team. Through RUG, I am also involved in the EESSI project where I collaborate in support and development.

My background is in Evolutionary Biology and most of my research and work prior to my current role revolved around scientific software development in one way or another.

Peter Michielse holds a PhD in numerical mathematics from Delft University of Technology (1990). Since then, has been working in the HPC arena in various technical and management roles at computer vendors (Silicon Graphics/Cray), the Dutch Research Council (NWO) and since 2011 at SARA/SURFsara and now at SURF. Currently, he is the strategic advisor of the COO of SURF for a range of subjects. He is also still involved in HPC subjects, is member of the Infrastructure Advisory group of EuroHPC and guest teacher on scientific computing in practice at Fontys University of Applied Sciences in Eindhoven.

Alexandre Bonvin (1964) studied Chemistry at Lausanne University, Switzerland and obtained his PhD at Utrecht University in the Netherlands (1993). After two post-doc periods at Yale University (USA) and the ETHZ (CH) he joined Utrecht University in 1998 where he was appointed full professor of computational structural biology in 2009. In 2006, he received a prestigious VICI grant from the Dutch Research Council. He was director of chemical education (2009-2012), vice head of the Chemistry Department (2010-2012) and Scientific Director of the Bijvoet Centre for Biomolecular Research (2019-2023). He has and is participating to several EU projects including the BioExcel Center of Excellence in Biomolecular Simulations.
Research within his group focuses on the development of reliable bioinformatics and computational approaches to predict, model and dissect biomolecular interactions at atomic level. To this end they develop the widely used HADDOCK integrative modelling software (https://bonvinlab.org/software; https://wenmr.science.uu.nl)

Zeila Zanolli is leading the “Quantum Materials by Design” group at the Chemistry Department/Debye Institute for Nanomaterials Science, Utrecht University. Previously (2018 – 2020) she was a Ramon y Cajal Fellow at ICN2, Barcelona (Spain), an excellence program of the Spanish Ministry for Economy, Industry and Competitiveness (MINECO). In 2016 – 2018, she leaded the Nanospintronics Group at the Physics Dept of RWTH Aachen University, funded by the DFG. In 2015 – 2012 she was Marie Curie Intra-European Fellow at Forschungszentrum Jülich (Germany).
Her researc focus is on Quantum Materials, a class of materials in which quantum mechanical effects are visible at the macroscopic scale. They provide unprecedented opportunities to enable a new technology based on quantum effects, with impact on low-dissipation electronics, photovoltaics, quantum information and, in general, quantum engineering. Her major contribution are in developing and using first-principles theory and computational methods to investigate topological materials, superconductors, quantum transport, (magnetic) proximity interaction, and spectroscopy. Her group is core developer of the open source code SIESTA https://gitlab.com/siesta-project/
She serves in the Psi-k working group “Quantum materials driven by correlations, topology or spin", in the Steering Committee of the European Theoretical Spectroscopy Facility (ETSF), and in the board of the “Semiconductor and Quantum Materials” session of the European Physical Society. Since 2019 Dr. Zanolli serves in the Editorial College of SciPost Physics, a Diamond Open Access publication portal. In 2018-20, Dr. Zanolli served in the Executive Committee of the MaX (MAterials design at the eXascale) European Centre of Excellence which enables materials modelling, simulations, discovery and design at the frontiers of the current and future High Performance Computing (HPC), High Throughput Computing (HTC) and data analytics technologies. In 2017 she has been elected Fellow of the Young Academy of Europe (YAE), a pan-European network of scientists active in science policy, where she served as a board member and treasurer in 2028-22.

Rob van Nieuwpoort is full professor “Efficient Computing and eScience” at the Leiden Institute of Advanced Computer Science (LIACS) at Leiden university, The Netherlands. His research involves ways in which large-scale computing power can be used more efficiently in achieving scientific breakthroughs in various scientific fields. He develops new programming models that make the use of large-scale systems (so-called exascale computers) simpler and more efficient. In addition, energy efficiency plays a crucial part. For large-scale scientific experiments such as the Square Kilometre Array (SKA) telescope, energy use is a limiting factor and a major expense. In these cases, software that uses energy more efficiently will have the immediate effect of increasing the sensitivity of the instruments. His second research interest is eScience. The field of eScience promotes the use of digital technology in research. eScience brings together IT technology, data science, computational science, e-infrastructure and data- and computation-intensive research across all disciplines, from physics to the humanities. He works on bridging fundamental computer science research and its application in exciting scientific disciplines.

https://www.linkedin.com/in/rob-van-nieuwpoort-132918/

Roy is a doctoral candidate affiliated with the Computational Biology research group at Eindhoven University of Technology and the Anesthesiology department at the Catharina Hospital Eindhoven. He contributes to the ACACIA (Advancing Cardiac Care through Interpretable AI) project, focusing on the development of AI-driven clinical decision support systems for the intensive care unit.

Sagar Dolas is a member of the Innovation Labs at SURF, where he leads and manages various programs and initiatives focused on Future Infrastructure and Applications, Advanced Computing, and Networking. In recent years, he has concentrated on energy as a design principle for the future of computing. He has led projects to integrate energy management tools with the Dutch supercomputer Snellius. Sagar has a background in High-Performance Computing (HPC), computational engineering, and applied mathematics, having completed his graduate-level studies at TU Delft and FAU Erlangen before joining SURF.

https://nl.linkedin.com/in/sagardolas

I am a quantum chemistry researcher specializing in heterogeneous catalysis and surface chemistry, with a focus on applying quantum algorithms to practical challenges. My expertise lies in computational and theoretical chemistry, particularly in studying molecule-surface reaction dynamics. I collaborate with industry partners to tackle real-world problems and am currently dedicated to implementing quantum algorithms in quantum chemistry and broader chemical applications.

Sergio Andreozzi is the Head of Strategy, Innovation, and Communications at the EGI Foundation, which coordinates the EGI Federation to deliver advanced computing services to global research communities. In this role, Sergio leads EGI’s strategy development, innovation management, and governance initiatives. He also serves as Project Director of the EC-funded SPECTRUM project. Sergio holds an Executive Master in Research Infrastructure Management from the University of Milano-Bicocca, a PhD in Computer Science from the University of Bologna, and an MSc in Computer Science Engineering from the University of Pisa.

As a member of the high-performance machine learning team at SURF, Thomas focuses on streamlining AI model architectures in terms of scaling, speed and model expressivity. Within machine learning, Thomas has notable experience in LLMs (from training until inference), computer vision (computational photography, satellite imagery, video processing, image generation), data formats, etc. Ideally and ambitiously, doing all of this in a responsible way from the perspective of privacy, energy-awareness and open way.

Thomas Wolf is the co-founder and Chief Science Officer (CSO) of Hugging Face, where he has been a pivotal figure in driving the company’s open-source, educational, and research initiatives. A prominent advocate for open science, Thomas has played a crucial role in making cutting-edge AI research and technologies widely accessible. He spearheaded the development of the Hugging Face Transformers and Datasets libraries, which have become foundational tools for researchers and developers in the machine learning community.

His contributions go beyond software development; Thomas is deeply invested in bridging the gap between academic research and industrial applications through projects like the BigScience Workshop on Large Language Models (LLM), which led to the creation of BLOOM, a large-scale open-source LLM.

With a diverse academic background spanning Physics, AI, and Intellectual Property, Thomas brings a unique interdisciplinary perspective to the field of advanced computing. He holds a Ph.D. in Statistical/Quantum Physics from Sorbonne University and has worked across both research and legal domains. Today, his research interests revolve around LLM accessibility and overcoming current limitations in AI. Outside of research, Thomas enjoys creating educational content, authoring the book Natural Language Processing with Transformers and sharing insights on the future of AI through blogs and videos.

With a background in computer architecture, accelerated computing, and machine learning, Valeriu is committed to empowering researchers with the tools and resources they need to drive scientific discovery. During his work as Head of High Performance Computing and Visualization at SURF, he is optimizing computing resources and leveraging cutting-edge technologies, he ensures that researchers can analyze vast amounts of data efficiently, enabling them to push the boundaries of their respective fields.

Driven by a passion for collaboration and innovation, he fosters an environment that encourages knowledge exchange and interdisciplinary cooperation. He continuously stay abreast of emerging trends in high-performance computing and visualization to provide innovative solutions that streamline workflows and optimize resource allocation. His goal is to revolutionize the research process by delivering user-centered computing solutions that enhance productivity and facilitate groundbreaking research.

Supercomputing Advisor at SURF