Holger Wittges is the Managing Director of the SAP University Competence Center (UCC) at the Technische Universität München (TUM) . His work focuses on Digital Transformation , Next Generation ERP , and Hybrid Cloud infrastructure. He is affiliated with the KrcmarLab and collaborates with IBM via the OpenPOWER@TUM initiative. Educational Background: 2004: Dr. rer. oec. (Promotion), Universität Hohenheim 1996: Diplom Wirtschaftsinformatiker, Universität Bamberg Research Interests include Digital Transformation, Cloud Computing, Enterprise Resource Planning (ERP), XaaS (Everything as a Service), and Service-Oriented Architecture (SOA). His work bridges academic innovation with industry needs through SAP UCC TUM, which provides 40+ educational service bundles like SAP HANA and S/4HANA for teaching and research. Recent Publications highlight advancements in machine learning for ERP support ticket systems, energy efficiency in SAP S/4HANA, and educational frameworks for cloud-based enterprise software. Articles emphasize collaboration with institutions across Europe and contributions to digital ecosystems like the SAP University Alliances. Key Projects include the OpenPOWER@TUM initiative with IBM, focusing on accessible AI/ML infrastructure for academia, and the SAP UCC TUM, which drives Education as a Service (EaaS) strategies for digital business ecosystems.
Shantanu Bhattacharya is a Lee Kong Chian Professor of Operations Management, Deputy Dean (Education), and Academic Director of the PhD in Business (General Management) at the Lee Kong Chian School of Business, Singapore Management University (SMU). He holds a PhD in Operations Management from The University of Texas at Austin (1998), an M.S. in Electrical and Computer Engineering from Louisiana State University (1993), and a B.Tech. in Electrical Engineering from IIT Bombay (1991). His research focuses on Operations Management , Supply Chain Strategy , Sustainable Operations , and New Product Development . He has pioneered studies on closed-loop supply chains, remanufacturing systems, and lifecycle pricing strategies. His work also explores digital business innovation, healthcare R&D partnerships, and energy sector operations. His recent work addresses strategic challenges in everything-as-a-service models (XaaS), battery-as-a-service strategies for automotive industries, and humanitarian logistics optimization. Earlier contributions include seminal studies on milestone-based R&D contracts, gain-share coordination mechanisms, and infrastructure investment in disaster relief. He has received awards including the 1996 Alden G. Clayton Dissertation Fellowship (top 5/57 entries) and multiple teaching nominations at INSEAD. Beyond academia, his research bridges operational efficiency with societal impact, particularly in sustainability and Asian market dynamics. He advises doctoral candidates such as SHEN Ya (CKGSB-SMU DBA). His career spans roles at INSEAD (2002-2014) and visiting positions at SMU-LKCSB (2014-2017), with leadership in curriculum design and PhD programs.
Uwe Zdun is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice-Director of Studies for Computer Science and Head of the Research Group Software Architecture. His teaching portfolio includes core courses such as Software Engineering 2, Advanced Software Engineering, and Practical Software Courses for Bachelor's and Master's theses across multiple semesters (2024W-2025S). His research spans software architecture with emphasis on microservices, cloud computing, and DevOps. Key focus areas include architectural design decisions, infrastructure-as-code conformance, security in distributed systems, and the integration of machine learning operations (MLOps/RLOps). He investigates cognitive aspects of architecture practices through controlled experiments and develops model-driven approaches for quality assessment in complex systems. Recent publications (2024-2026) reveal three dominant trends: (1) Security and coupling analysis in infrastructure-as-code deployments, (2) MLOps/RLOps integration for Industry 4.0 cyber-physical systems, and (3) Performance optimization patterns for CI/CD pipelines and autoscaling. His work bridges theoretical architecture models with industrial practice, particularly in microservice ecosystems and reinforcement learning applications. Professor Zdun leads the Research Group Software Architecture at the University of Vienna's Faculty of Computer Science. The group focuses on empirical validation of architectural patterns, tool development for conformance checking, and advancing design decision methodologies in cloud-native and AI-driven systems.
Danfeng Zhang is a faculty member at Duke University whose research sits at the intersection of programming languages and security. Active across the premier PL conferences since 2015, Zhang has served on more than two-dozen program committees and currently co-chairs the POPL Student Research Competition. Education & Affiliation: Home page: users.cs.duke.edu/~dz132 Affiliation: Duke University, United States Research Interests: Zhang’s work spans programming-language design, static and dynamic analysis, formal verification, and security. A recurring theme is developing language-based techniques that guarantee strong security and privacy properties—ranging from side-channel resistance and constant-time execution to differential-privacy proofs—while preserving performance and usability. His recent projects combine type systems, program logics, and automated reasoning to build practical verification tools for concurrent, speculative, and approximate software. Publication Trends: Across nine representative papers (2015-2024) Zhang has advanced static detection of cache side channels, automated proofs of differential privacy, and relaxed concurrency models. The trajectory shows deepening integration of security concerns into language infrastructure, with tool-building (CtChecker, SpecSafe, LightDP) that bridge formal guarantees and real-world systems. Service & Leadership: 2024 POPL Student Research Competition Co-Chair 2025 POPL Program Committee member Repeated reviewer/PC member: PLDI, SPLASH/OOPSLA, ISSTA, ECOOP, APLAS, PriSC, PASS Zhang regularly mentors student researchers through SRC sessions and workshop panels, fostering diversity and early-career participation in the programming-languages community.
Harald C. Gall is a Professor of Software Engineering and Dean of the Faculty of Business, Economics, and Informatics at the University of Zurich (UZH). He leads the Software Evolution and Architecture Lab, focusing on software evolution analysis, mining software repositories, and cloud-based software engineering. His research emphasizes improving software development productivity through data-driven insights. He has held visiting positions at Microsoft Research and the University of Washington. Education: PhD (Dr. techn.) and Master's (Dipl.-Ing.) in Informatics from TU Vienna Research Interests: Software evolution, mining software archives, cloud-based tools, developer productivity, and empirical software engineering. Notable contributions include the Evolizer , ChangeDistiller , and SOFAS systems. Key Contributions: Established the Mining Software Repositories (MSR) research area, program chair for ICSE 2011 and ESEC/FSE 2005, associate editor of leading journals like Empirical Software Engineering and IEEE Software. Awards: Most Influential Paper Award, Test of Time Award, and multiple Best Paper Awards. Recognized for contributions to SE research methodologies and tool development. Professional Activities: ACM SIGSOFT awards chair, board member of Informatics Europe, and executive committee member of CHOOSE (Swiss SIG for OO Systems). Labs/Teams: Director of the Software Evolution and Architecture Lab at UZH, leading projects like SURF-MobileAppsData (SNSF-funded) and DevCloud (Hasler Foundation).
Keith D. Koper is a Professor in the Department of Geology & Geophysics at the University of Utah and serves as Director of the University of Utah Seismograph Stations (UUSS). He is also the editor-in-chief of The Seismic Record . His work integrates academic research with operational seismic monitoring and public safety initiatives across Utah and the Intermountain West. Education: PhD in Geophysics, Washington University, 1998 BA in Math, Geology, and ISP, Northwestern University, 1993 Dr. Koper's research focuses on array seismology, forensic seismology, deep Earth structure (especially the inner core), earthquake rupture imaging, ambient seismic noise, and seismic hazards in the Intermountain West, including mining-induced and urban earthquakes. His work combines observational seismology with advanced signal processing and machine learning techniques to improve detection, discrimination, and imaging capabilities. He has led or contributed to major projects involving the Wasatch Front, Yellowstone, and regional seismic networks. His recent research emphasizes machine learning for earthquake detection, high-resolution relocation of aftershock sequences (e.g., Magna 2020, Bluffdale 2019), microseism generation in lakes, and fine-scale imaging of the Earth's inner core using seismic reflections. His studies often involve interdisciplinary collaboration, particularly with mining engineering and geodesy. Dr. Koper's research has been consistently funded by federal and state agencies, including the National Science Foundation (NSF), U.S. Geological Survey (USGS), Department of Energy (DOE), Air Force Research Laboratory (AFRL), and the Utah Department of Public Safety. His publications reflect a strong trend toward integrating computational methods with traditional seismological analysis to tackle complex problems in both natural and induced seismicity. Scientific Service and Leadership: Editor-in-Chief, The Seismic Record Director, University of Utah Seismograph Stations Secretary, U.S. Air Force Seismic Review Panel Former Chair and Vice-Chair, Utah Seismic Safety Commission Dr. Koper mentors graduate students in seismology and geophysics, including recent advisees Sean Hutchings and Alysha Armstrong. His research group actively engages in both fundamental and applied seismological research, with strong ties to national labs such as Sandia. The group is involved in deploying portable seismic arrays, analyzing large datasets, and developing new algorithms for event detection and classification. The University of Utah Seismograph Stations, under his leadership, plays a critical role in monitoring seismicity in Utah and Yellowstone, producing real-time earthquake information, ShakeMaps, and public outreach materials. The station also contributes to national and international efforts in nuclear test monitoring and volcanic hazard assessment.
James Lawler is a Professor in the Seidenberg School of Computer Science and Information Systems at Pace University, focusing on Information Technology. He has dedicated his career to advancing Disability Studies and STEM technologies for individuals with developmental and intellectual disabilities (IDD), while also contributing to e-Business strategies and social entrepreneurship. His work bridges technology and inclusivity, with a strong emphasis on community engagement and equity. Education: DPS, School of Computer Science and Information Systems, Pace University (2002) MBA, Graduate School of Business, Pace University (1974) BBA, Business Administration, Saint Francis College (1971) APC in Computer Applications (Audited), New York University (1979) Research Focus: Professor Lawler's research spans Customer Relationship Management (CRM) technologies, service-oriented architecture, and web services. He has pioneered initiatives for neurodiverse students in STEM, developed multisensory environments using virtual reality, and created programs like the Disability Film Festival to promote inclusion. His work often involves partnerships with AHRC New York City and other organizations. Awards: National Jefferson Award for Community Service (2024) Pace University Golden Graduates Reunion 50th Year of Service (2024) SEINFORMS Certificate of Recognition (2021) ISECON Meritorious Paper Award (2013) Grants & Professional Contributions: He has secured multiple grants for projects like the Disability Film Festival, robotics for elderly people with disabilities, and mobile app development for food waste reduction. His professional service includes roles with AHRC NYC, IEEE Education Society, and editorial boards for academic journals. He also teaches courses on design thinking, information systems, and e-commerce strategies.
Adrian Priest is a Senior Lecturer in the School of Mathematics and Computer Science within the Faculty of Science and Engineering at the University of Wolverhampton. He plays key roles in academic quality assurance, apprenticeship development, and international education partnerships. His responsibilities include serving as a University Quality Panel Member, School Apprenticeships Champion, Link Tutor for Degree Apprenticeships, and Personal Tutor for Computing students. His educational background includes a degree in Business Information Systems from Staffordshire University and postgraduate qualifications from the University of Wolverhampton, such as a Postgraduate Certificate in Learning and Teaching in Higher Education, and studies in Business Information Technology and Strategic Information Technology Management. Adrian's research and teaching focus on critical areas in modern computing and management, particularly Cyber Security, Project Management, Change Management, Risk Management, and Degree Level Apprenticeships . His work bridges academic theory and industry practice, informed by prior professional experience as an IT Manager and IS Consultant in the financial sector. The available publication highlights his interest in the integration of change management within project management frameworks, reflecting a broader trend in organizational and technological adaptation. His work suggests a strong applied research orientation with relevance to both academic and industrial contexts. Chartered IT Professional, British Computer Society (Member) Fellow of the Higher Education Academy Member of the Institute of Leadership and Management Adrian has extensive experience in academic leadership and student supervision, having served as Module Leader for numerous undergraduate and postgraduate courses, supervised MSc and BSc projects, and led curriculum development initiatives. He has also contributed to institutional growth through roles in course validation, transnational education (Sri Lanka and Malaysia), Knowledge Transfer Partnerships, and vocational training facilitation (Prince2). While no specific grants are mentioned, his involvement in KTP and international programs indicates engagement with funded collaborative projects. He is actively involved in professional service, including health and safety representation, union activities, wellbeing advocacy, and fire safety. These roles reflect a strong commitment to the broader university community beyond teaching and research.
Timothy Harris is an Affiliated Lecturer at the University of Cambridge's Department of Computer Science and Technology, where he jointly teaches courses on multicore semantics and programming. Currently, he works at OpenAI, focusing on performance optimization for GPU inference of large language models, including the Azure OpenAI Service. Previously, he held roles at Microsoft, AWS, Oracle Labs, and was a faculty member at the University of Cambridge (2000–2004). His research spans distributed systems, runtime systems, operating systems, and high-performance computing, with an emphasis on scalability and performance. He contributed to projects like the Xen hypervisor and the Barrelfish research OS. Key research interests include distributed training of PyTorch models in the ONNX runtime, large-scale storage performance with Amazon S3, and runtime systems for in-memory graph analytics. His work often bridges 'big data' and high-performance computing techniques. Notable contributions include the book Transactional Memory (2010) and the Barrelfish OS, alongside numerous publications in top-tier conferences like SOSP, ASPLOS, and EuroSys. He has served as PC chair for ISMM 2025, VEE 2017, and EuroSys 2015, reflecting his leadership in the systems research community. His awards include a Best Paper Award at PACT 2010. Beyond academia, Harris is an avid hiker, aiming to complete the UK coastline, and maintains a photography portfolio at tlhphotography.uk .
Matteo Brunelli is Associate Professor of “Mathematical Methods of Economics and Actuarial and Financial Sciences” at the University of Trento , Department of Industrial Engineering, and Adjunct Professor (docent) at Lappeenranta University of Technology , Finland. He is nationally habilitated as Full Professor in Italy and has held long-term visiting positions at Berkeley, Turku, Auckland, JAIST and Binghamton. Education: Ph.D. (Doctor of Science) in Information Technologies, Åbo Akademi University, Finland, 2011 – graded Eximia cum laude approbatur M.Sc. in Economics, University of Trento, 2007 – grade 110/110 cum laude B.Sc. in Economics, University of Trento, 2005 Research focus: Brunelli’s work sits at the intersection of multi-criteria decision analysis , operations research and computational optimisation . He develops axiomatic foundations and algorithms for pairwise comparison matrices , consistency indices , the best-worst method and fuzzy preference relations , and applies them to energy planning, sustainable inventory, maintenance scheduling, 3-D printer selection, and blockchain governance. His 2023-2025 articles reveal intensified interest in uncertainty modelling (Dempster-Shafer theory), bi-objective optimisation of inventory and maintenance, and group decision protocols that integrate probabilistic or active-learning components, demonstrating both methodological depth and practical relevance. Scientific awards & grants: Academy of Finland Postdoctoral Researcher grant (€254 670, 2014-2017) Claudio Dematté Research Grant (€19 000, 2008) Teacher of the Year Award, Aalto University (2013 – both Spring & Autumn semesters) Bernard Roy Award 2021 for outstanding contribution to Multiple Criteria Decision Aiding (under-40 category) Supervision & funding: While specific doctoral students are not listed, Brunelli currently supervises graduate theses at Trento and has continuously held competitive national grants. His Academy of Finland project “Consistency of valued preference relations for decision analytics methods” financed three years of full-time research and international collaboration. Editorial & community roles: He serves on the editorial boards of International Journal of General Systems and Mathematical and Computational Applications , and acts as area editor for Journal of Multi-Criteria Decision Analysis , positioning him among the key gatekeepers of the MCDA community.
Dr. Vivek Nallur is an Assistant Professor in the School of Computer Science at University College Dublin. His research focuses on Machine Ethics, Multi-Agent Systems, emergence in socio-technical systems, and decentralized adaptation mechanisms. He holds a PhD from the University of Birmingham and advanced certifications in university teaching from UCD. Education: BBS, Delhi University Post-Graduate Diploma in Advanced Software Technology, National Centre for Software Technology MS, Carnegie Mellon University PhD, University of Birmingham Prof Cert University Teaching & Learning, University College Dublin Research Interests: Machine Ethics explores ethical decision-making in autonomous systems, while Multi-Agent Systems (MAS) are his primary tool for studying self-adaptation and emergence. He serves on key committees like IEEE P7008 (Ethically Driven Nudging) and the AAAI 2021 Spring Symposium on AI Ethics. His work bridges computer science with philosophy, law, and social sciences. Advising & Grants: Supervises three PhD students focusing on ethical AI, elder-care robotics, and AI governance. Leads the Machine Ethics Research Group and participates in the ML-Labs SFI grant (2019–2027). Professional Roles: Senior Member of IEEE, organizer for AAAI ethics symposia, and contributor to OpenAAL's ELSI panel. Teaches modules on Machine Learning, Operating Systems, and Web Development.
Yonghwi Kwon is a Visiting Assistant Professor in the Department of Computer Science at the University of Virginia. His research focuses on software systems security, cyber forensics, and software engineering. He received the CAREER Award for developing dynamic defenses against cyber threats. His work emphasizes securing software from cyber attacks, recovering forensic evidence, and improving software testing and reverse engineering techniques. Key research areas include memory safety mechanisms, automated vulnerability detection in web applications and mobile systems, and forensic analysis of phishing campaigns. He has pioneered frameworks like CMASan for memory allocator-aware sanitization and Racedb for detecting race conditions in database-backed systems. His contributions span cloud security automation, kernel exploitation analysis, and embedded system fuzzing. Notable achievements include the 2025 CAREER Award supporting his dynamic defense research, and impactful publications in areas like Android information leakage detection (DryJIN), Bluetooth protocol fuzzing (BTFuzzer), and autonomous driving bug discovery (Drivefuzz). His work bridges theoretical computer science with practical cybersecurity solutions.
Emin Gün Sirer is an Associate Professor at the Department of Computer Science , College of Engineering , Cornell University . He co-directs the Initiative for Cryptocurrencies and Smart Contracts and leads the Meridian and HyperDex projects. Research in operating systems, networking, and distributed systems Focus on secure operating systems, high-performance cloud infrastructure, and peer-to-peer networks Developed systems like Nexus (secure OS), OpenReplica (Paxos implementation), and Trickles (stateless network protocol) Prominent Projects : Meridian - Lightweight network location service without virtual coordinates Cubit - Decentralized peer-to-peer search Kimera - Network-centric Java verification SPIN - Extensible microkernel for application-specific services Scientific Contributions : Leading work in blockchain security and peer-to-peer systems Patents in executable content rewriting and distributed virtual machines Advising & Collaborations : Advises projects in network positioning and content distribution Collaborates with institutions like Usenix , SIGCOMM , and NSDI Personal Background : Ph.D. and M.S. in Computer Science from the University of Washington B.S.E. in Computer Science from Princeton University High school at Robert College
Vassilios Tzerpos is an Associate Professor at the Lassonde School of Engineering, York University, where he has been since 2001. He holds a Ph.D. in Computer Science from the University of Toronto (2001). His research focuses on audio processing for musical applications, deep learning, digital signal processing, machine listening, and software engineering education. He directs the APTLY lab exploring music-technology intersections and leads the LaSSoftE lab developing socially-oriented software solutions. Education: Ph.D. in Computer Science, University of Toronto, 2001 Research Highlights: Dr. Tzerpos' work spans music information retrieval (e.g., automatic music classification), synthetic speech detection using neural networks, and software engineering pedagogy. His recent projects include Music-STAR for audio re-instrumentation and OER-based learning path creation systems. He has pioneered methods in design pattern detection and software clustering evaluation. Grants & Labs: Leads two research groups: APTLY (music-tech) and LaSSoftE (social impact software). Active in developing adaptive cybersecurity solutions against DoS attacks and refining software architecture recovery techniques. Key Themes in Publications: Recent work emphasizes machine learning applications in music technology and cybersecurity, with foundational contributions to software clustering methodologies and design pattern detection algorithms. His work bridges theoretical computer science with practical applications in education and creative industries.
Carlo A. Furia is an Associate Professor at the Software Institute within the Faculty of Informatics at Università della Svizzera italiana (USI). He leads the ATOM research group and is actively involved in advancing formal methods in software engineering. His work bridges theoretical rigor with practical applicability, particularly in verification, automated repair, and empirical analysis of software systems. PhD in Computer Science, Politecnico di Milano Master of Science in Computer Science, University of Illinois at Chicago Laurea in Computer Science and Engineering, Politecnico di Milano His research focuses on making formal methods practical through automation, combining diverse techniques, and conducting thorough empirical evaluations. He is particularly interested in using Bayesian data analysis to assess software engineering data. His work spans program verification (e.g., AutoProof), contract inference, API usability, and multilingual program analysis. His recent publications highlight trends in automated program repair, JVM bytecode analysis, Android security, and empirical methodologies. These works reflect a consistent emphasis on correctness, reliability, and empirical validation in software development. Scientific service includes: Associate Editor, Empirical Software Engineering (EMSE) journal Program Committee member, FM 2026, FormaliSE 2026, ASE 2025, iFM 2025 He has advised students and leads the ATOM group, which develops tools for software analysis. He teaches courses such as Software Analysis, Programming Fundamentals, and Software Design & Modeling. Current research directions include improving empirical evaluation rigor and enhancing verification at lower code levels like bytecode.
