Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing (SoC). He holds a B.Sc. (1st Class Honors) and Ph.D. in Computer Science from Monash University. His research focuses on database systems, large-scale analytics, and distributed computing. He has held leadership roles including Dean of School of Computing (2007–2013) and Director of Smart Systems Institute (2011–2021). Key achievements include the Singapore President’s Science Award (2011), ACM Fellow (2011), IEEE Fellow (2009), and multiple best paper awards. His work emphasizes scalable data management, blockchain systems, and healthcare data analytics. Education: Monash University (B.Sc., Ph.D.) Leadership: Dean (SoC), Director (Smart Systems Institute) Awards: Over 15 major honors including ACM SIGMOD E.F. Codd Innovations Award (2020) His research spans distributed databases, big data systems, and innovative applications of blockchain technology. Recent work includes NASI (neural architecture search) and Rafiki (ML-as-a-service).
Deval Desai serves as Reader in International Economic Law at the University of Edinburgh's Edinburgh Law School, a position he has held since 2020 after serving as Lecturer from 2020-2023. His academic career includes research positions at Harvard Law School and the Geneva Graduate Institute. Dr. Desai also brings extensive practical experience from a decade working with the World Bank on rule of law and governance in sub-Saharan Africa, as well as advising the United Nations on rule of law issues. Dr. Desai's educational background includes an MA in History and French Literature from Oxford University, followed by legal training at City University/BPP Law School (PGDipL and PGDipLP), and advanced law degrees (LLM and SJD) from Harvard Law School. At Harvard, he held prestigious fellowships including the Byse Fellowship, Program on Negotiation Next Generation Fellowship, and Institute for Global Law and Policy Fellowship. MA (Oxon), History and French Literature PGDipL, PGDipLP, City University/BPP Law School LLM, Harvard Law School SJD, Harvard Law School Dr. Desai's research centers on law and development, administrative law and regulation, theories of the state, and patterns of knowledge and authority across the Global North and South. His work examines institutional reform processes, particularly how expertise and knowledge operate within rule of law initiatives. His interdisciplinary approach draws from legal and social theory, development studies, international relations, and performance studies, as evidenced in his monograph Expert Ignorance (Cambridge University Press). His recent work focuses on fiscal sociology, administrative law in the Global South, and the politics of social welfare provision. Dr. Desai's publications span leading journals in law, political science, and development studies, revealing a consistent focus on the intersections between legal institutions, governance, and development. His work demonstrates increasing engagement with comparative methodologies and critical perspectives on knowledge production in global governance. Recent articles show particular attention to fiscal policy, welfare systems, and responses to global crises like the Covid-19 pandemic, with comparative studies between India and European contexts. Dame Muriel Spark Medal (2024, Royal Society of Edinburgh) Chancellor's 'Rising Star' Award (2023, University of Edinburgh) Member of the Young Academy of Scotland Fellow of the Royal Society of Arts Fellow of the Young Academy of Europe Dr. Desai has secured significant research funding from diverse international sources, including a £2.1 million Swiss National Science Foundation Sinergia grant titled 'Reversing the Gaze: Towards Post-Comparative Area Studies' where he serves as PI. He also leads projects funded by the British Academy, University of Edinburgh's Big Ideas Accelerator, Scottish Funding Council, and Foreign, Commonwealth, and Development Office. His commitment to mentoring is evident through his recognition with the Susan Manning Award for Inspiring Mentor and his leadership in establishing programs like the Global Scholars' Academy at the Geneva Graduate Institute and the Global Justice summer school at CEU. As editor-in-chief of the Cambridge University Press book series 'Elements in Legal Theory and the Global South' and serving on multiple editorial boards, Dr. Desai plays a significant role in shaping scholarly discourse. His current research projects examine 'loss' in legal institutions guiding transitional processes, constitutional implications of fiscal arrangements in fragile contexts, and social welfare provision in India and Italy.
Huamin Qu is a Chair Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST). He serves as the Founding Dean of the Academy of Interdisciplinary Studies (AIS), Founding Head of the Division of Emerging Interdisciplinary Areas (EMIA), and was the Founding Acting Head of Computational Media and Arts (CMA) at HKUST(GZ). Qu directs the VisLab and coordinates the Human-Computer Interaction (HCI) group. He obtained his BS in Mathematics from Xi'an Jiaotong University and MS/PhD in Computer Science from Stony Brook University. Qu's research integrates Data Visualization , Human-Computer Interaction , and Human-Centered AI , with applications in urban informatics, social networks, and explainable AI. His work focuses on developing interactive systems for big data analytics, visual storytelling, and AI-driven decision support. Research extends to multimodal communication, fintech, and augmented reality applications. His publications emphasize visual analytics for complex datasets (mobility, social media, financial), interaction techniques for immersive environments, and AI-enhanced visualization tools. Recent works explore explainable AI interfaces and large-scale data communication frameworks. IEEE Visualization Academy (2020) IEEE VGTC Technical Achievement Award AI 2000 Most Influential Scholar (2019, 2023, 2024) 21 Best Paper/Honorable Mention awards IBM Faculty Award (2009) APICTA Merit Award (2015) Yelp Dataset Grand Prize (2018) Qu has advised 48 PhD graduates (21 now faculty at institutions like UC Davis, University of Minnesota, Texas A&M) and 30 MPhil students. He secured major grants including RGC theme-based projects (digital citizenship, air pollution), UGC AoE (slope safety), and China's 973 Program. As VisLab director, he leads 20+ researchers in visualization/HCI projects adopted by Microsoft, IBM, Huawei, and Tencent.
Institute of Science and Technology AustriaAustria
Christoph H. Lampert is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Machine Learning and Computer Vision (MLCV) Group. His research spans machine learning, computer vision, and trustworthy AI with emphasis on robustness and fairness. He serves as ELLIS Fellow and Unit Director for ISTA's ELLIS unit. His research program focuses on foundational challenges in machine learning including robustness against distribution shifts, fairness in algorithmic decision-making, and verification of neural networks. Key contributions include work on 1-Lipschitz networks for robust classification, multi-source learning frameworks, and federated learning architectures. The group maintains strong output in top-tier venues through theoretical and empirical approaches. Recent publications (2023-2025) demonstrate consistent focus on verification, robustness, and multi-source learning, with notable recognition including the DARPA Disruptive Ideas award for logic gate neural network verification. Work frequently bridges computer vision and machine learning theory, with applications in safety-critical systems. Scientific Awards: ELLIS Fellow DARPA Disruptive Ideas award at NeuS (2025) for "Logic Gate Neural Networks are Good for Verification" Professor Lampert has supervised 12+ PhD students including recent graduates Alex Peste (2023), Nikola Konstantinov (2022), and Mary Phuong (2021), with current advisees including Max Cairney-Leeming and Egor Zverev. His group secures consistent publication placements at NeurIPS, ICML, and ICLR while editing major volumes like "Advanced Structured Prediction" (MIT Press 2015). The MLCV group comprises 10+ members including postdocs and PhD students, operating within ISTA's ELLIS unit (approved 2019). The team maintains active collaborations across Europe through the ELLIS network and regularly hosts visiting researchers.
Gene Tsudik is a Distinguished Professor of Computer Science at the University of California, Irvine (UCI), with a career spanning over two decades. He obtained his Ph.D. in Computer Science from the University of Southern California (USC) in 1991, focusing on access control in the Internet. His research spans multiple areas including computer and network security, applied cryptography, and digital privacy, with a recent emphasis on database privacy, genomic privacy, and usable security. His notable contributions include the Inter-Domain Policy Routing (IDPR) protocol, KryptoKnight for network security, and Tree-Based Group Key Agreement protocols. He has over 210 publications and 8 patents. From 2002 to 2007, he served as Associate Dean of Research and Graduate Studies at UCI's School of Information and Computer Sciences and currently directs the UCI Secure Computing and Networking Center (SCONCE). Research Keywords : Cybersecurity, Cryptography, Privacy, Network Security, Digital Signatures, Genomic Data Protection. Scientific Awards : IEEE Fellow (2012), ACM Fellow (2014), AAAS Fellow (2016), Fulbright Senior Scholar (2007), and IFIP Fellow (2020). Professor Tsudik has supervised 18 PhD students and held visiting positions at universities across Europe and Asia. His recent publications focus on secure hardware attestation, biometric authentication, and social media data privacy.
Dr. Yunjie Yang is an Associate Professor at the University of Edinburgh's School of Engineering, with affiliations at the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL), and the Edinburgh Centre for Robotics. He previously held the Chancellor's Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024) positions. His research focuses on AI-powered sensing and imaging, machine learning, and soft sensors & electronics for robotics. Yang received his PhD in Engineering Electronics from the University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. After his PhD, he worked as a Postdoctoral Research Associate in Chemical Species Tomography before securing his lectureship. His research interests center on developing intelligent sensing systems that replicate human perception capabilities for robotics and intelligent systems. He pioneers flexible sensing and imaging technologies across various scales through innovative multi-modal sensors, soft electronics, and their modeling using machine learning approaches. His work aims to enable autonomous physical artificial intelligence by bridging the gap between robotic systems and human-like perception. Analysis of his recent publications reveals a strong focus on soft robotics perception, particularly through electrical impedance tomography (EIT) and transformer-based architectures. His research spans medical imaging applications, digital twin modeling for industrial processes, and machine learning approaches for sensor data interpretation. The trend shows increasing integration of physics-informed deep learning with traditional tomographic techniques to achieve higher accuracy and efficiency. European Research Council (ERC) Starting Grant (2024) IEEE J. Barry Oakes Advancement Award (2024) IEEE I&M Society Graduate Fellowship Award (2015) Multiple Best Paper Awards Senior Member of IEEE Fellow of the International Society for Industrial Process Tomography Fellow of the Higher Education Academy ESI highly cited papers Dr. Yang serves as Associate Editor for IEEE Transactions on Instrumentation and Measurement and holds editorial positions with Scientific Reports and IEEE Sensors Journal. His research has been licensed to overseas research institutes and industry partners and received wide media coverage including BBC, EFE, USA Today, and STV. He has secured significant grant funding including the prestigious ERC Starting Grant. He leads the Edinburgh SMART Lab (Sensing/imaging + Machine Learning + Robotics), which aims to replicate human perception capabilities for robotics and advance flexible sensing technologies through innovative multi-modal sensors and machine learning approaches. The lab focuses on enabling autonomous physical artificial intelligence with applications spanning medical diagnostics, industrial monitoring, and advanced robotics systems.
Karl Michael Göschka is an Associate Professor at Vienna University of Technology (TU Wien) in the Department of Distributed Systems (E194-02) within the Faculty of Computer Science. His academic title of Privatdozent indicates he has completed habilitation, the highest academic qualification in the German/Austrian system. He maintains an active research and teaching profile with courses scheduled through 2026S, including Bachelor Thesis supervision, Computer Science Projects, and PhD Seminars. His research spans over two decades with consistent publications from 2004 to 2022. Göschka's primary research interests focus on Dependable Distributed Systems, Web Engineering, and the convergence of voice and data technologies. His work demonstrates particular expertise in middleware, service-oriented architecture, wireless sensor networks, and fault tolerance mechanisms. He has supervised numerous master's and diploma theses since 2006, with his most recent doctoral supervision completed in 2022. Göschka's publication record shows a clear evolution from foundational work in distributed systems and replication (2004-2013) to more recent contributions in wireless sensor networks and dependable computing (2020-2022). His research consistently addresses the challenge of balancing dependability, performance, and security in distributed environments, with notable contributions in temporal decoupling techniques and adaptive systems. GIT-Preis des Österreichischen Vereins für Elektrotechnik (1999) Würdigungspreis des Ministeriums für Wissenschaft und Forschung (1998) GIT-Förderpreis des Österreichischen Vereins für Elektrotechnik (1994) Göschka has led and participated in multiple significant research projects including TRADE (2008-2011) on adaptive performance optimization, COMPASS (2005-2007) for automotive software systems, S-Cube (2008-2012), ALL-TIMES (2007-2010), and DeDiSys (2004-2007) on dependable distributed systems. His research has strong practical applications in automotive systems, online auctions, and critical infrastructure monitoring.
Peter Druschel is a Professor and founding Director of the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. He holds adjunct professorships at Saarland University and the University of Maryland. His research focuses on distributed systems, operating systems, and privacy-preserving technologies. He earned his Ph.D. from the University of Arizona in 1994 and has held roles at Rice University since 1994, including Professor of Computer Science (2002–2005). Education: Ph.D. in Computer Science, University of Arizona (1994) Research Interests: Distributed systems, operating systems, network security, accountable computing, and privacy technologies. Current projects include privacy compliance in data systems (Thoth), secure communication (EbN), and privacy-aware image capture (I-Pic). Awards: SIGOPS Mark Weiser Award (2008) NSF CAREER Award (1995) Member of Academia Europaea and German Academy of Sciences Leopoldina Grants & Leadership: Leads the ERC Synergy Project imPACT, chairs the Max Planck Society’s Chemistry, Physics, and Technology Section, and collaborates with institutions like Cornell and Google. Advises on policy issues related to technology and privacy. Labs/Teams: Distributed Systems Group at MPI-SWS, collaborations with Microsoft Research and MIT. Current team includes students and postdocs working on privacy, security, and distributed systems.
Andrea C. Ferrari is a Professor of Nanotechnology at the Department of Engineering, University of Cambridge, UK. He holds multiple leadership roles, including Director of the Cambridge Graphene Centre and EPSRC Centre for Doctoral Training in Graphene Technology, and serves as Science and Technology Officer for the EU Graphene Flagship. Education: PhD, University of Cambridge (2001) Laurea in Nuclear Engineering, Politecnico di Milano (1997) Ferrari’s research focuses on graphene, 2D materials, and their applications in nanotechnology, photonics, optoelectronics, and Raman spectroscopy. His work bridges fundamental studies and industrial translation, emphasizing scalable synthesis and characterization techniques. His publications span over 390 peer-reviewed articles, including groundbreaking studies on graphene photonics, quantum emitters, and advanced optoelectronic devices. These works are highly cited, with an H-index of 115 and over 116,000 total citations. Scientific Awards: IMR-Lee Hsun Lecture Award (2018) Nanosmat Award (2017) Knight Officer of the Order of the Star of Italy (2017) ERC Synergy Grant (2013) EU-40 Materials Prize (2011) Royal Society Wolfson Research Merit Award (2010) ERC Starting Grant (2008) Philip Leverhulme Prize (2005) Ferrari has secured over £60M in research funding, including leadership roles in the EU Graphene Flagship and the EU Quantum Technology Flagship. He is a Fellow of the Optical Society, Materials Research Society, Institute of Physics, and American Physical Society.
Wolfgang Kunz is a Full Professor (C4, W3) and Chair of Electronic Design Automation at the Technische Universität Kaiserslautern since 2001. His academic career spans multiple prestigious institutions, including Goethe-University Frankfurt/Main and the University of Massachusetts, Amherst. He has held leadership roles such as Dean (2005-2007) and Vice-Dean (2007-2009) at TU Kaiserslautern. Habilitation (Dr. rer. nat. habil.), Computer Science, University of Potsdam (1996) Doctoral degree (Dr.-Ing.), Electrical Engineering, University of Hannover (1992) Dipl.-Ing. degree, Karlsruhe Institute of Technology (1989) His research focuses on hardware verification, security, and optimization, particularly in embedded systems and processors. His work on formal verification methods has been commercialized by companies like Synopsys, Mentor Graphics, and Siemens EDA. His 2016-2021 publications address critical security issues such as Spectre/Meltdown and introduce innovative verification frameworks adopted by industry leaders like Infineon and OneSpin Solutions. Scientific awards include the IEEE Fellow (2006), German IT Society Award (2005), and TU Kaiserslautern Distinguished Teaching Award (2016). He has served on editorial boards of major journals and coordinated the Erasmus Mundus European Master Program in Embedded Computing Systems since 2010. Key students: Jörg Bormann, Raik Brinkmann, Tobias Ludwig Collaborations: Siemens EDA, Infineon, AbsInt, Intel SCAP Spin-offs: LUBIS EDA, OneSpin Solutions
Nori Franco serves as Professor in the Department of Physics at the University of Michigan and Chief Scientist at RIKEN's Theoretical Quantum Physics Laboratory in Japan. His dual appointments reflect his significant contributions to both American and Japanese academic communities, with continuous service at Michigan since 1990 and at RIKEN since 2002. His research spans quantum information, condensed matter physics, and quantum optics, with particular focus on light-matter interactions, superconducting qubits, optomechanics, and quantum open systems. Franco's work bridges theoretical foundations with experimental implementations, especially in circuit quantum electrodynamics and quantum computing applications. Analysis of his recent publications reveals a strong emphasis on non-Hermitian quantum systems, quantum control techniques, and applications of quantum information science to fundamental physics problems. His research group consistently produces highly cited work, with publications appearing in top journals across quantum physics and condensed matter disciplines. Scientific Awards: Charles Hard Townes Medal (2024) - sole recipient for fundamental contributions to quantum optics and quantum information processing Research Doctorate Honoris Causa from University of Messina (2024) Highly Cited Researcher for eight consecutive years (2017-2024) Member of Academia Europaea (2023) Willis E. Lamb Medal (2023) for quantum electronics research Throughout his career, Franco has secured significant research funding and mentored numerous students and postdoctoral researchers. His work has received international recognition through invitations to deliver prestigious lectures including the Stanislav Ulam Lecture and Sir Nevill Mott Lecture in 2024. His research group maintains strong collaborations across multiple continents, reflecting his global impact on quantum physics. At RIKEN, Franco leads the Quantum Information Physics Theory Research Team within the Quantum Computing Center, directing cutting-edge theoretical work that complements experimental efforts in quantum computing hardware development.
Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.
Massimiliano Di Ventra is a Professor of Physics at the University of California, San Diego, holding this position since 2006 after serving as Associate Professor (2004-2006) and moving from Virginia Tech where he was Assistant Professor (2000-2002) and Associate Professor (2003). His academic journey includes research roles at IBM T.J. Watson Research Center and Vanderbilt University. Education: Undergraduate degree in Physics, summa cum laude, University of Trieste, Italy (1991) PhD in Physics, Swiss Federal Institute of Technology, Lausanne (1993-1997) Di Ventra's research bridges theoretical physics with practical applications, focusing on quantum transport in nanoscale systems, non-equilibrium statistical mechanics, and DNA sequencing/polymer dynamics in nanopores. His pioneering work on memory effects in nanostructures has driven innovations in unconventional computing and biophysics, resulting in over 300 refereed publications and significant commercial impact through memcomputing technologies. His scientific awards include: Senior member, National Academy of Inventors (2025) Humboldt Research Award (2024) Fellow, American Association for the Advancement of Science (2022) IEEE Nanotechnology Council Distinguished Lecturer (2022) Fellow, IEEE (2022) George W. and Carol A. Lattimer Research Fellow (2021) Member of Academia Europaea (2020) Feynman Prize for Theory in Nanotechnology (2020) APS Outstanding Referee (2019) Highly Cited Researcher (2018) Di Ventra has secured major research funding including an NSF CAREER Award and Ralph E. Powe Award, holds 11 granted patents, and co-founded MemComputing, Inc. His mentorship extends to numerous graduate students and postdoctoral researchers within his active research group at UCSD. He maintains a globally recognized research presence through visiting professorships at institutions including École Normale Supérieure of Paris (2024), Technion (2017), and Technical University of Dresden (2015), and has delivered over 350 invited talks including 20 plenary/keynote presentations worldwide.
Matteo Maffei is a Full Professor at TU Wien, leading the Security and Privacy group. He joined in 2017 after 11 years at Saarland University's CISPA. He holds a Ph.D. in Computer Science from Ca’ Foscari University of Venice (2006). He coordinates the TU Wien Cybersecurity Center, the SecInt Doctoral School, and the FWF Special Research Program SPyCoDe. His research focuses on formal methods for security and privacy, blockchain technologies, and web security. Roles: Full Professor, Coordinator of TU Wien Cybersecurity Center, Module Head of Christian Doppler Lab for Blockchain Technologies (CDL-BOT), Board Member of Vienna Cybersecurity and Privacy Research Cluster (ViSP). His work emphasizes formal verification of cryptographic protocols, smart contracts, and decentralized systems. Key achievements include ERC Advanced (2024) and Consolidator (2018) Grants, and leadership roles in conferences like IEEE Computer Security Foundations Symposium (CSF). Research Interests: Formal methods, smart contracts, blockchain scalability, web security, privacy-preserving protocols, and decentralized systems. His recent projects include optimizing Lightning Network channels, secure multi-hop payments, and AI-driven robustness verification. Publications: Over 200 publications in top venues like CCS, IEEE S&P, and CRYPTO. Recent work includes advancements in blockchain interoperability (e.g., Alba bridges), light client protocols (Blink), and neural network verification techniques. Grants & Awards: ERC Advanced Grant (2024), ERC Consolidator Grant (2018), DFG Emmy Noether Fellowship (2009). Led projects funded by EU Horizon, FWF, and industry partners like ABC Research GmbH. Advising & Labs: Supervised over 20 PhD/Master theses. Active in the Christian Doppler Lab for Blockchain Technologies and the SPyCoDe SFB. Collaborates with institutions like SBA Research and Stanford University.
Vienna University of Economics and BusinessAustria
Gerald Reiner serves as Head of the Institute for Production Management at the Vienna University of Economics and Business (WU), within the Department of Information Systems and Operations Management. He holds a Magister Degree, doctorate, and Habilitation in Business Administration from WU. His academic career includes positions as full professor in Production Management and Logistics at the University of Neuchatel (Switzerland, 2007-2014) and Universitaet Klagenfurt (Austria, 2014-2018), where he also served as head of the department of Operations, Energy, and Environmental Management. Dr. Reiner has held visiting professorships at Aston Business School (UK), HEC Lausanne (Switzerland), University of Bergamo, and Università Cattolica del Sacro Cuore in Milan (Italy). His research spans several critical areas including Industry 4.0 implementation, integrated capacity and inventory management, humanitarian logistics operations, circular supply chains, and operations management for base of the pyramid contexts. His work particularly focuses on practical applications addressing food waste reduction, sustainable manufacturing, and blockchain technology in supply chains. His publication portfolio demonstrates a clear evolution toward digital transformation in operations, with recent focus on hydrogen production systems, AI integration in manufacturing, and blockchain applications for food supply chain transparency. The research shows increasing emphasis on sustainability integration within traditional operations management frameworks, particularly addressing European manufacturing challenges and food system inefficiencies. Publication Excellence Award 2021 (2023) Researcher of the month (January 2023) Highly Commended paper in the 2017 Emerald Literati Network Awards for Excellence ISIR Service Award (2014) Emerald Outstanding Paper Award (2013) Dr. Reiner coordinates multiple significant international research projects including EU-project 'Keeping Jobs in EU', EU/Ecsel-project 'Power Semiconductor and Electronics Manufacturing 4.0', 'Integrated Development 4.0', and 'Artificial Intelligence in Manufacturing leading to Sustainability and Industry 5.0'. His current projects focus on FOODIS (cross-border ecosystem for innovation in food supply chains), Circular Design implementation, and blockchain applications for banana supply chains. He actively supervises research teams working on food waste reduction, sustainable packaging systems, and AI applications in operations management.
