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Manolis G.H. Katevenis is a Professor at the Department of Computer Science, University of Crete, and Deputy Director and Head of the Computer Architecture and VLSI Systems (CARV) Laboratory at the Institute of Computer Science (ICS), Foundation for Research & Technology - Hellas (FORTH). He co-founded the European Research Center on Computer Architecture (EuReCCA) and is a founding partner of the European Network of Excellence on High-Performance and Embedded Architecture and Compilation (HiPEAC). PhD in Computer Science from University of California, Berkeley (1983) Co-founder of EuReCCA (2011) Contributed to RISC architecture (1980-1983), interconnection networks (1985-2011), and parallel computing (1993-2010) His research spans Scalable Multicore Systems , Interconnection Network Architecture , Packet Switch Design , Computer Architecture , and VLSI Systems . He has made foundational contributions to per-flow queueing, backpressure mechanisms, and wormhole IP over ATM, with applications in internet routers, data centers, and supercomputers. His publications focus on high-radix crossbar switches, flow control algorithms, and explicit interprocessor communication. Notable scientific awards include: ACM Doctoral Dissertation Award (1984) David J. Sakrison Memorial Prize (1983) IBM PhD Fellowship (1981-1983) Greek State Fellowship (1973-1978) He has supervised 40 graduate theses and participated in 22 R&D projects totaling €9M, including HiPEAC (coordinator of interconnection networks), SARC (FPGA prototype design), and ENCORE (cache-optimized remote DMA). His work has received over 2000 citations, with an h-index of 23.

• Computer Architecture
• VLSI Systems
• Interconnection Network Architecture
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Robert F. Tichy is a Professor at the Institute of Analysis and Number Theory , Graz University of Technology, Austria. His career spans over four decades with significant contributions to Diophantine equations , uniform distribution , and quasi-Monte Carlo methods . He has held multiple editorial board positions and administrative roles , including Dean of the Faculty of Mathematics, Physics and Geodesy (2018-2019). Research Interests : Uniform distribution, Diophantine equations, algorithmic number theory, fractal structures, quasi-Monte Carlo methods, and mathematics in finance/insurance. Awards : Austrian Mathematical Society award (1985), Honorary Doctorate (University of Debrecen, 2017), Jean-Morlet Chair (2020), and memberships in prestigious societies. Publications : Over 200 papers with recent works (2024) focusing on Diophantine problems , pseudorandom sequences , and Carlitz coefficients . Teaching : Regular courses for engineering and mathematics students, including annual lectures on insurance mathematics .

• Uniform Distribution and Discrepancy
• Diophantine Equations
• Analytic Combinatorics
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Sascha Hunold is an Associate Professor at TU Wien, affiliated with the Department of Parallel Computing within the Faculty of Informatics. He holds roles as Vice Dean of Academic Affairs for Informatics Bachelor programs and Curriculum Coordinator for the Master's program in High-Performance Computing. His research focuses on parallel computing, MPI optimization, scheduling algorithms, and reproducible HPC experiments. Education: Habilitation (venia docendi) in Computer Science from TU Wien, PhD in Computer Science from the University of Bayreuth, and MSc in Computer Science from Martin Luther University Halle-Wittenberg. Research interests include MPI collective communication performance, HPC benchmarking, algorithm selection, and task scheduling. He has contributed to tools like ReproMPI and Scheduling.jl. Key awards include Best Paper awards at IEEE CLUSTER 2020 and EuroMPI/Asia 2014, and recognition for reproducible research methodologies. His work emphasizes practical applications of parallel computing in large-scale systems. Teaching responsibilities include courses on parallel algorithms, scientific programming with Python, and HPC project supervision. Active in program committees for major conferences like IPDPS and SC.

• Parallel Computing
• High-Performance Computing (HPC)
• MPI Collective Communication
• +4 more

Prof. Jesper Larsson Träff is a Full Professor and Head of the Research Unit in Parallel Computing at Technische Universität Wien (TU Wien). His academic role is centered within the Department of Computer Engineering. He holds an MSc and PhD, and has contributed extensively to the field of parallel computing through his research and leadership in international projects. His research focuses on parallel algorithms, scheduling, and optimization of the Message Passing Interface (MPI), with emphasis on high-performance computing (HPC) systems and distributed architectures. Key projects include the Process Mapping initiative (2019–2024), Autotune (2021–2025), and contributions to Exascale Programming Models. He has also led efforts in evaluating MPI performance tools and their reproducibility challenges. Research Areas: Parallel Algorithms, MPI Optimization, HPC, Process Mapping, Collective Communication, and Memory Models. Notable Achievements: Awarded the Best Paper at EuroMPI 2014 and recognized by the Innovation Radar for his work on PGAS-based MPI interoperability in 2018. Teaching: Teaches courses such as Advanced Multiprocessor Programming, Bachelor/Master Thesis supervision, and seminars in Computer Engineering and Theoretical Computer Science. Prof. Träff’s advising includes students researching topics like lock-free data structures, MPI datatype optimization, and task scheduling. His grants span Austrian and EU funding bodies, addressing challenges in exascale computing and reproducible experimental research. He is affiliated with the Vienna Mapping and Sparse Quadratic Assignment (Vienna Mapping) project and actively contributes to international workshops and conferences.

• Parallel Algorithms
• Parallel Computing
• High-Performance Computing (HPC)
• +4 more

Marianna Giancaterino is a postdoctoral research associate at the Institute of Food Technology, University of Natural Resources and Life Sciences, Vienna (BOKU). Her work focuses on integrating innovative non-thermal technologies like Pulsed Electric Fields (PEF) and Ohmic Heating into traditional food processing workflows to enhance efficiency and product quality. Institution: BOKU Vienna Department: Institute of Food Technology Research Period: 2018–Present Research Interests: Giancaterino's research combines non-thermal technologies with fruit and vegetable processing to modify plant material structures. Key areas include: Cellular permeabilization via PEF for improved drying/extraction Ohmic heating for rapid, uniform thermal processing Freeze-drying optimization with pre-treatment strategies Energy consumption reduction in food manufacturing Tailored process development for quality preservation Waste minimization through process intensification Scientific Contributions: Her work demonstrates how PEF alters cellular structures to enhance mass transfer during processing, with applications in peeling, cooking, and drying. She explores synergies between PEF and ohmic heating for vegetable processing. 2024: 4 major conference presentations 2023: 5 conference posters and talks 2022: 4 presentations at international events Education: 2016–2019 M.Sc. in Food Science and Technology, University of Teramo (Italy) 2013–2016 B.Sc. in Food Science and Technology, University of Teramo

• Food Technology
• Fruit and Vegetable Processing
• Non-Thermal Technologies
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Thomas Gold is a researcher at the Institute of Hydraulic Engineering, Hydraulics and River Research, within the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). He earned his Doctorate in Agricultural Engineering and Water Management with distinction from BOKU in 2025, following a Master’s (2020) and Bachelor’s (2017) from the same institution. His research focuses on hydraulic engineering and river systems, particularly sediment transport, reservoir sedimentation in run-of-river hydropower plants, gravel augmentation, and flushing efficiency. His work combines experimental hydraulics with numerical modeling, including CFD simulations using advanced techniques like the immersed boundary and level-set methods. He has presented findings at major international conferences such as the IAHR World Congress. His recent publications indicate a strong trend in understanding sediment dynamics in regulated rivers, with emphasis on environmental impacts and engineering solutions for sustainable water management. He actively contributes to the scientific community as a reviewer for journals including Physics of Fluids , Water , and Geophysical Research Letters . Scientific Engagement: Reviewer, Water (2025–present) Reviewer, European Journal of Mechanics B-Fluids (2025–present) Reviewer, Physics of Fluids (2022–present) Reviewer, Geophysical Research Letters (2021–present) Thomas Gold is actively involved in research and academic service. There is no indication of teaching supervision or funded projects at this time, but his scholarly output and peer review roles confirm his active status in the field of hydraulic and environmental engineering.

• Hydraulic Engineering
• River Research
• Sediment Transport
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Lukas Steinberger serves as Associate Professor for Statistical Machine Learning in the Department of Statistics and Operations Research at the University of Vienna's Faculty of Business, Economics and Statistics. He is also affiliated with the university's Data Science research network. Prior to his current position, he was a post-doctoral researcher with Angelika Rohde at the University of Freiburg and held a temporary Full Professorship in the Department of Mathematics at the Technical University of Munich. Steinberger's research program centers on statistical inference under differential privacy, high-dimensional data analysis, and uncertainty quantification in statistical learning. His work bridges theoretical statistics with practical machine learning applications, particularly focusing on how to perform valid statistical inference while preserving data privacy. His research has significant implications for fields requiring sensitive data analysis including healthcare, finance, and social sciences where privacy constraints are paramount. His publication record demonstrates consistent contributions to top-tier statistics journals including multiple papers in the Annals of Statistics. His recent work shows a clear trajectory toward developing theoretically sound methods for privacy-preserving data analysis that maintain statistical efficiency. The research themes across his publications reveal strong connections between differential privacy mechanisms, high-dimensional statistical theory, and practical machine learning applications. Scientific Awards: Award for dissertations in the field of theoretical statistics (2016) Steinberger maintains an active research agenda with numerous conference invitations and seminar presentations internationally, reflecting his standing in the statistical community. His current research project "Classification - Preprocessed and high-dimensional data" (2021-2025) indicates ongoing funding and research direction. He serves as Vice-Director of Studies for the Business, Economics and Statistics program and teaches courses including Statistics 2, Computational Statistics, and Classification, Clustering and Discrimination at the master's level. As part of the Data Science research network at University of Vienna, Steinberger collaborates with interdisciplinary teams working at the intersection of statistics, computer science, and domain-specific applications. His research group focuses on developing theoretically grounded approaches to statistical machine learning problems under privacy constraints.

• Statistical Machine Learning
• Differential Privacy
• High-dimensional Data Analysis
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Wolfgang Faber is a researcher at Vienna University of Technology (TU Wien) specializing in Knowledge-Based Systems within the Faculty of Informatics. Holding the position of Privatdozent, he has completed his habilitation and is qualified to teach at the university level. His academic work centers on Answer Set Programming (ASP), Logic Programming, and Knowledge Representation, with significant contributions to theoretical foundations in these fields. Dr. Faber's research spans multiple areas of computational logic: Answer Set Programming and its theoretical underpinnings Epistemic logic programs and equivalence properties Knowledge representation and reasoning systems Nonmonotonic reasoning formalisms Integration of logic programming with external data sources His publication history reveals a sustained focus on theoretical aspects of ASP, with particular emphasis on program equivalence concepts (strong equivalence, uniform equivalence), computational complexity analysis, and applications to knowledge representation. Over two decades, his research has evolved from foundational work in disjunctive logic programming to specialized topics in epistemic reasoning within ASP frameworks. Dr. Faber has led and participated in numerous research projects including START (2014-2022) on Uniform Equivalence of Epistemic Logic Programs, SemDat (2012-2016), and multiple projects related to hybrid knowledge bases and Answer Set Programming from 2005-2015. His collaborative research extends across European institutions, evident through extensive co-authorship with researchers like Thomas Eiter and Stefan Woltran. While specific awards aren't documented in the available information, his sustained research output and leadership in multiple projects indicate significant recognition within his field. Dr. Faber has made substantial contributions to major systems in the field, most notably the DLV system for knowledge representation and reasoning, which has influenced both academic research and practical applications of Answer Set Programming.

• Answer Set Programming
• Logic Programming
• Knowledge Representation
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Stephan Holzer is a computer scientist and mathematician currently affiliated with the Massachusetts Institute of Technology , where he works within the Computer Science and Artificial Intelligence Laboratory (CSAIL) . He has held postdoctoral positions at MIT (2013–2017) and visiting roles at Harvard and ETH Zurich. His expertise lies in the theory of distributed systems, with a focus on efficient algorithms for networks. Education: Stephan earned his Diplom (M.Sc.) and B.Sc. from TU Munich within Germany’s TopMath excellence program (2006–2008), followed by a Ph.D. in Computer Science from ETH Zurich (2009–2013) under the supervision of Prof. Roger Wattenhofer. Research Interests: His work spans distributed algorithms , graph theory , wireless communication , communication complexity , and network optimization . He particularly explores how devices in large-scale networks can compute distances, disseminate information, and coordinate despite interference and limited resources. Publications & Impact: Stephan has published extensively in premier venues such as PODC, DISC, SODA, and TCS. His recent work addresses security of crypto-currencies, leader election in wireless models, and approximation algorithms for shortest-path problems, reflecting a blend of theoretical rigor and practical relevance. Scientific Awards & Honors: Best Paper Award, 24th SIROCCO 2017 Member, Young Academy | Mainz 2016 Nominated delegate, Global Young Scientist Summit 2016 Participant, Heidelberg Laureate Forum 2013 Teaching & Mentoring: Stephan co-created and lectures the MIT graduate course 6.S899 Distributed Graph Algorithms with Profs. Mohsen Ghaffari and Nancy Lynch. He has mentored numerous undergraduate and master’s students through UROP, UAP, and thesis projects at MIT and ETH Zurich. Service: He has served on the program committees of SPAA, ICDCN, SSS, SOFSEM, and ALGOSENSORS, and regularly reviews for top-tier journals and conferences in distributed computing and algorithms.

• Distributed algorithms
• Graph theory
• Wireless networks
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Uwe Schmock is a Full Professor at the Vienna University of Technology , leading research in Financial and Actuarial Mathematics within the Institute for Statistics and Mathematical Methods in Economics. His work bridges theoretical probability with practical financial and insurance risk modeling. Research interests include large deviations theory , risk aggregation , credit risk models , and stochastic integration . He has contributed to insurance mathematics through catastrophe bond analysis (e.g., WinCAT coupons) and annuity valuation tables. His recent publications focus on U-empirical measures , Panjer's recursion , and exotic options under market constraints. Scientific awards include the Charles A. Hachemeister Prize and the David Garrick Halmstad Memorial Prize . He actively collaborates with institutions like ETH Zurich and the American Casualty Actuarial Society.

• financial mathematics
• actuarial mathematics
• insurance mathematics
• +7 more

Keith Martin Ball is a leading mathematician specializing in functional analysis, convex geometry, and information theory. He holds the Professorship at the University of Warwick since 2010 and previously held prominent positions at University College London, Texas A&M University, and the International Centre for Mathematical Sciences (ICMS) in Edinburgh. Alma Mater: Trinity College, Cambridge (PhD 1987 under Béla Bollobás) Key Contributions: Extension theorems for Lipschitz functions, reverse isoperimetric inequalities, Banach-Steinhaus Theorem advancements, and entropy-driven central limit theorem proofs. His research spans high-dimensional geometry, discrete geometry, and applications to information theory. He has authored the popular mathematics book Strange Curves, Counting Rabbits, & Other Mathematical Explorations . Recent Publications focus on zeta function irrationality, entropy inequalities, and geometric functional analysis, reflecting his interdisciplinary approach combining pure mathematics with probabilistic and information-theoretic methods. Scientific Honours Fellow of the Royal Society (FRS) (2013) Fellow of the American Mathematical Society (AMS Fellow) (2013) Shephard Prize (2015) Whitehead Prize (1992) Leverhulme Fellow (2003-2004) Member of Academia Europaea (2023)

• Functional Analysis
• Convex Geometry
• High-dimensional Geometry
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Univ.Prof. David Preinerstorfer is a Professor at the Department of Statistics and Mathematics at WU Vienna University of Economics and Business. His research focuses on econometric theory, statistical methodology, and high-dimensional testing. He has published extensively in top journals such as Econometrica , Journal of Econometrics , and Annals of Statistics . Key research areas include heteroskedasticity and autocorrelation robust testing, high-dimensional statistical inference, bootstrap methods, and optimal policy learning. His work addresses challenges in econometric testing under complex data conditions and develops methods to enhance statistical power and validity. Recent publications analyze topics like modern Gauss-Markov theorems, superconsistency in high dimensions, and treatment allocation with distributional targets. Preinerstorfer collaborates frequently with researchers such as A. B. Kock and B. M. Pötscher on projects addressing robust testing procedures and statistical methodology advancements.

• Econometrics
• Statistical Theory
• High-Dimensional Testing
• +4 more

Robert Tichy is a full Professor at the Institute of Analysis and Number Theory, Technische Universität Graz. His research spans number theory, stochastic analysis, and computational mathematics. He has held significant administrative roles including Department Head (1994-2000), Dean of Mathematical and Physical Sciences (2003-2009), and Vice-Dean (2010-2017). Tichy is a Corresponding Member of the Austrian Academy of Sciences and has served on editorial boards for journals like the Journal of Number Theory and The Ramanujan Journal .

• Uniform Distribution
• Discrepancy Theory
• Diophantine Equations
• +7 more

Jürgen Beck is a researcher in Bioprocess Engineering at the University of Natural Resources and Life Sciences, Vienna (BOKU), affiliated with the Department für Biotechnologie und Lebensmittelwissenschaften and the Institut für Bioverfahrenstechnik. He is actively engaged in research related to biopharmaceutical purification, particularly continuous chromatography and process modeling. His research focuses on advancing integrated continuous manufacturing in biopharma, with emphasis on multi-column chromatography, protein adsorption dynamics, mass transfer mechanisms, and hybrid modeling combining mechanistic equations with machine learning. His work addresses challenges in parameter estimation, flow non-uniformities, and resin performance, aiming to improve separation efficiency and scalability. The recent publications and conference presentations (2018–2024) demonstrate a strong trend in bioprocess intensification , chromatographic modeling , and continuous biomanufacturing , particularly for recombinant proteins and monoclonal antibodies. His work bridges experimental characterization with computational modeling to optimize bioprocesses. He has not received any scientific awards listed in the provided data. Jürgen Beck has delivered numerous lectures at international conferences such as PREP, Recovery of Biological Products, and ECAB. He collaborates closely with researchers including R. Hahn and E. von Lieres. No information is available about student supervision or external funding. He is involved in knowledge transfer through conference presentations and scientific dissemination. He is part of a research group focused on bioprocess development and modeling, contributing to advancements in industrial biopharmaceutical production processes.

• Bioprocess Engineering
• Protein Chromatography
• Continuous Manufacturing
• +7 more

Kate Waldert is a Doctoral Student and Research Assistant in the Institute of Food Technology within the Department of Biotechnology and Food Sciences at the University of Natural Resources and Life Sciences, Vienna (BOKU). She holds an M.Sc. in Food Technology from Berlin University of Technology and a B.Sc. from Berliner Hochschule für Technik. Her research is centered on innovative electrical processing technologies in food engineering. Research Interests: Her work focuses on ohmic heating, ohmic baking, and pulsed electric field (PEF) applications for microbial inactivation and food quality enhancement. She investigates thermal and non-thermal preservation techniques, food microbiology, and chemical food analysis. Her research aims to improve energy efficiency, product quality, and sustainability in industrial food processing through electrical technologies. Publication Trends: Her recent publications (2024–2025) emphasize the optimization of ohmic processing for wheat bread and vegetables (carrots, beetroot), exploring process parameters, chamber design, power input, and synergistic effects with PEF. The studies are published in leading journals like Journal of Food Engineering and Innovative Food Science and Emerging Technologies , highlighting advancements in electrical food processing and process characterization. Scientific Awards: Three Minute Thesis (3MT®) Competition 2024 Anerkennungspreis für außergewöhnliche Leistungen in der Lehre an der Universität für Bodenkultur Wien (2022) Advising and Community Engagement: She has supervised two master’s theses on PEF applications in yeast metabolism and growth. She is actively involved in the scientific community as a reviewer for Food Hydrocolloids and as a member of professional organizations including the European Hygienic Engineering & Design Group (EHEDG), the Verein Österreichischer Lebensmittel- und Biotechnologen (VÖLB), and the International Society for Electroporation-Based Technologies and Treatments (ISEBTT). She has presented her research at numerous international conferences such as EFFoST, IUFoST, and the World Congress on Electroporation. Laboratory and Research Context: Her work is conducted in collaboration with leading research institutions, including the Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) in Potsdam, where she completed a research stay. Her projects are embedded within BOKU’s strong research environment in food technology and bioeconomy.

• Food Technology
• Food Process Engineering
• Ohmic Heating
• +6 more