Luca Cardelli is a Principal Researcher and Assistant Director at Microsoft Research Cambridge, UK, since 1997. He holds visiting professorships at Imperial College London (Department of Computing, 2004–2009) and the University of Trento (2005–2007). He earned his PhD in Computer Science from the University of Edinburgh in 1982. His research spans type theory , molecular programming , and principles of programming languages , with applications to systems biology and concurrency theory. Notable contributions include formal frameworks for modeling biochemical systems (e.g., the stochastic π-calculus) and designing DNA-based circuits. Key achievements include the AITO Dahl-Nygaard Senior Prize (2007) and multiple Most Influential Paper Awards at POPL and ETAPS. His work bridges computer science and biology, advancing both theoretical foundations and practical molecular computing.
Dr. Emily Cuming is a Senior Lecturer in the Humanities and Social Science school at Liverpool John Moores University , specializing in British literature, culture, and social history from the 19th century to the present. Her research focuses on maritime relations, working-class girlhood, life writing, and representations of domestic spaces including council estates, slums, and bedsits. PhD, MA, BA in English & Russian from University of Manchester (2006, 2002, 2001) Editor of Key Words: A Journal of Cultural Materialism Co-leader of the Home and Domestic Cultures research network Committee member of the Research Institute for Literature and Cultural History Board member of the Centre for Port and Maritime History Her research combines literary analysis with historical and cultural studies, emphasizing material culture, port cities, and marginalized voices. Recent publications include Maritime Relations: Life, Labour and Literature at the Water’s Edge, 1830-1914 (Cambridge University Press, forthcoming 2025) and Housing, Class and Gender in Modern British Writing, 1880-2012 (CUP, 2016). She has received multiple research grants including AHRC Connected Communities funding and Liverpool John Moores University QR awards. Dr. Cuming teaches undergraduate modules on Life Stories , Representing Domestic Space , and Waterscapes , as well as MA courses on Place: Imagining Place in Modern Times . She supervises three PhD projects and welcomes new supervisees in her research areas. 2025: Enhancing Research Cultures funding for 'The Sinking of the Lancastria' 2024: Editorial board member of Journal of Victorian Culture 2023: NCCPE Engage Prize for 'Around the Toilet' project 2022: Caird Short-term Research Fellowship 2016: NCCPE Engage Prize winner
Gang (Gary) Tan is a Professor at the Pennsylvania State University's College of Engineering, specializing in computer security, formal methods, and programming languages. He co-directs the Institute for Networking and Security Research (INSR) and leads the Security of Software (SOS) Group, focusing on compiler, programming language, and formal method techniques to enhance computer security. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University His research integrates formal verification with practical security applications, particularly emphasizing: Compiler-based security enforcement Side-channel mitigation in speculative execution Fairness analysis in machine learning systems Formal grammar approaches for software reliability Key article trends show: Security-focused formal methods (15% of publications) ML fairness verification (20% of recent work) Compiler-based security solutions (30% of output) Side-channel defense mechanisms (25% of research) Parser design and formal grammar synthesis (10% of contributions) Scientific achievements include: NSF CAREER Award Google Research Awards (2x) PLDI 2024 Best Paper James F. Will Career Development Professorship Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Dr. Tan actively contributes to academic communities through: DARPA ISAT study group membership Program committee roles (CGO 2024, ECOOP 2018, etc) Leadership in security research initiatives
Danny Poo Chiang Choon is a tenured Associate Professor at the School of Computing (SOC), National University of Singapore (NUS). As Curriculum Chair of the Department of Information Systems and Analytics, he plays a key role in designing and implementing Information Systems and Computer Science curriculum at NUS. Dr. Poo earned his BSc (Honours), MSc and PhD in Computation from the University of Manchester Institute of Science and Technology (UMIST), United Kingdom. His academic journey has established him as a leader in health informatics and information systems at NUS. His research spans multiple domains with strong focus on Healthcare Informatics , where he investigates mobile health interventions, health analytics, and systems for improving patient care. His work in Data Science & Business Analytics explores knowledge management, information sharing, and effective search strategies. In Intelligent Systems , he examines software engineering approaches, object-oriented systems, and knowledge classification frameworks. His recent publications demonstrate a clear trajectory toward mobile health applications, particularly in coronary heart disease prevention and diabetes management. Dr. Poo's work consistently bridges technical computing with practical healthcare applications, focusing on user-centered design and evidence-based interventions. His research shows strong interdisciplinary integration between computer science, healthcare systems, and behavioral science, with emphasis on practical implementation in Singapore's healthcare context. Dr. Poo has served in numerous leadership roles including as the founding Director of the Centre for Health Informatics at NUS (2012-2015) and as a member of the Steering Committee of the Asia Pacific Software Engineering Conference (APSEC) since 1994, serving as Vice-Chairman from 2003-2005. He has been invited to speak at international forums including the Japanese Government's "USA, Kyushu and Asia International Exchange Project" and as a keynote speaker at the 2009 Arabic Scripts Second Symposium in Abu Dhabi. His expertise is recognized through invitations to speak on knowledge management topics at conferences in Singapore. Dr. Poo has authored five books in the Information Technology area: "Enterprise JavaBeans for Students" (2014), "Object-Oriented Programming and Java" (1998, 2007), "Learn to Program Enterprise JavaBeans 3.0" (2009), "Learn to Program Java" (2009), and "Learn to Program Java User Interface".
Alan Sussman is a Professor and Associate Chair of Undergraduate Education in the Computer Science department at the University of Maryland. His research focuses on databases, high-performance computing, parallel systems, and educational curriculum development for computing disciplines. He holds a Ph.D. from Carnegie Mellon University (1991) and a B.S.E. from Princeton University (1982). His educational contributions include integrating parallel and distributed computing concepts into early undergraduate courses, supported by NSF-funded initiatives like the CyberTraining program. He has advised students such as Harshit Soora (Master's) and Xiaolong Tian (PhD). His research spans compiler optimizations for parallel programs, distributed data management systems, and scientific workflow frameworks like DYFLOW. He collaborates with UMIACS and contributes to interdisciplinary projects like the TASCS center. Key innovations include VeloxDFS for distributed dataset streaming, compiler techniques for irregular memory access in PGAS programs, and NetCDFaster for geospatial data optimization. His work emphasizes productivity improvements for high-performance applications and curriculum modernization to address emerging computational challenges. Awards: No individual awards explicitly listed; however, collaborator Jik-Soo Kim received a best paper award in 2006. Grants: NSF CyberTraining, TCPP Curriculum Initiative, and Center for Technology for Advanced Scientific Component Software (TASCS). Labs/Teams: Active in UMIACS and interdisciplinary collaborations, including the TASCS center and InterComm framework development.
Finbarr Barry Flood is the William R. Kenan, Jr., Professor of the Humanities and Founder-Director of the Silsila: Center for Material Histories at NYU's Institute of Fine Arts. He holds a Ph.D. in Islamic Art History from the University of Edinburgh (1993) and a B.A. in Archaeology from Trinity College Dublin (1988). His research focuses on Islamic art and architecture, cross-cultural material culture, and art historical methodologies. Notably, he has held prestigious fellowships such as the Slade Professorship at Oxford and ACLS Collaborative Research Fellowship. His work bridges global art histories, examining topics like medieval Hindu-Muslim encounters, iconoclasm, and the materiality of religious artifacts. Flood’s scholarly contributions include seminal books like Objects of Translation and The Great Mosque of Damascus . His awards reflect both academic excellence and teaching prowess, including NYU's Golden Dozen Award. As director of Silsila, he leads interdisciplinary research into material histories, fostering collaborations across disciplines and regions. His publications span 40+ years, addressing themes from medieval art technologies to modern reinterpretations of Islamic aesthetics.
Giansalvatore (Gianni) Mecca is a full professor at the Department of Mathematics, Computer Science and Economics at the University of Basilicata. Born in Potenza, he earned his Computer Engineering degree and PhD from Sapienza University of Rome under Prof. Paolo Atzeni. He joined the University of Basilicata in 1995, initially as a research associate and later as an associate professor. He has held visiting positions at the University of Toronto, Qatar Computing Research Institute, Arizona State University, and Roma Tre University. His research focuses on data quality, analytics, integration, and information extraction, alongside cooperative database systems. He teaches courses in computer programming, databases, and web development for Computer Science and Engineering programs. Key initiatives include the Diogene project, which innovates teaching methodologies in procedural programming and database systems, emphasizing layered instruction and dual-language (C++/FORTRAN) approaches. Diogene’s framework tools like pinco (Web MVC) and PdD (questionnaire generator) reflect his contributions to educational software. His work integrates practical coding examples with layered theoretical explanations, emphasizing algorithmic clarity and cross-language comparisons. Publications include methodological papers on educational systems and teaching practices, such as the 2006 Diogene Working Report on certification frameworks. His teaching materials span procedural programming, XML, and object-oriented design, distributed under Creative Commons licenses.
Dr. Dijiang Huang is an Associate Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He joined ASU in 2005 after completing his Ph.D. in Telecommunications and Computer Networking from the University of Missouri-Kansas City (2004). His research focuses on cybersecurity, mobile computing, and cloud computing, supported by grants from the National Science Foundation (NSF), Office of Naval Research (ONR), and industry partners like HP. He has received prestigious awards, including the ONR Young Investigator Award and HP Innovative Research Award. Education: B.E. in Telecommunications, Beijing University of Posts and Telecommunications (1995) M.S. in Computer Science, University of Missouri-Kansas City (2001) Ph.D. in Telecommunications and Computer Networking, University of Missouri-Kansas City (2004) Research Interests: Huang’s work emphasizes secure communication protocols, privacy-preserving techniques, and resilient network architectures. He has pioneered frameworks like Secure Group Communication (SeGCom) and Attribute-Based Cryptography , addressing challenges in VANETs, SDN, and edge computing. His recent projects include developing Waterfall for SDN security and SmartDefense for DDoS mitigation. Grants & Awards: ONR Young Investigator Award (2008) HP Innovative Research Award (2008) NSF grants for secure mobile cloud frameworks and cyber-physical systems Professional Contributions: Huang has served as a reviewer for journals like IEEE Transactions on Wireless Communications and conferences such as ACM MobiArch. He co-developed the Open Human-Robotic Mobile Networking and Security Testbed (OHReST) and the Virtual Laboratory (VLab) for cybersecurity education.
Amir Shaikhha is an Associate Professor (Reader) in the School of Informatics at the University of Edinburgh. He was previously an Assistant Professor (Lecturer) at the same institution from 2020 to 2024 and a Departmental Lecturer at the University of Oxford until August 2020. He is also a Junior Research Fellow at University College, Oxford. His academic journey began with a Ph.D. from EPFL in 2018, where he was awarded the Google Ph.D. Fellowship in structured data analysis and a Ph.D. thesis distinction. His research centers on the design and implementation of data-analytics systems, drawing upon techniques from databases, programming languages, compilers, and machine learning. He develops high-performance systems such as SDQL.py, StructTensor, and VecHT, focusing on the compilation of data science workloads and optimization of tensor operations. His work bridges the gap between high-level abstractions and efficient execution, particularly in sparse and probabilistic computing domains. The recent publications highlight a strong trend in compiler-driven optimizations for data-intensive applications, including automatic differentiation, loop fusion, probabilistic programming, and domain-specific language (DSL) restaging. His research integrates machine learning for systems decisions and emphasizes reproducibility and performance. He has published consistently in top venues like PLDI, OOPSLA, SIGMOD, and CGO, reflecting sustained impact in programming languages and database systems. Dahl-Nygaard Junior Prize, 2025 Google Research Scholar Award, 2025 Most Influential Paper Award, GPCE 2024 Best Paper Award, GPCE 2017 Most Reproducible Paper Award, SIGMOD 2017 Google Ph.D. Fellowship, 2017 Amir Shaikhha has advised PhD students including Hesam Shahrokhi and has been nominated for Best Supervisor of the Year at the University of Edinburgh. He leads research projects that have received recognition and support through awards and grants, including the Google Research Scholar Award. He actively serves the community through program committees (e.g., GPCE, DBPL, DRAGSTERS), editorial roles, and peer review for premier journals. His leadership in organizing workshops and conferences underscores his role as a central figure in the programming languages and databases research communities. He leads a research group focused on compiler and database systems, with recent open-source releases such as StructTensor and VecHT. His team collaborates with researchers from institutions like MIT, EPFL, and TU Berlin, and he co-chairs workshops like Sparse@PLDI and DRAGSTERS. His lab emphasizes innovation in how data-intensive programs are compiled and executed efficiently across modern hardware.
Prof. Peter Müller is a Full Professor at the Department of Computer Science at ETH Zurich since 2008. Previously, he held positions as Assistant Professor at ETH Zurich (2003-2008), Researcher at Microsoft Research Redmond (2007-2008), and IT project manager at Deutsche Bank. He earned his Diploma in Computer Science from Technical University of Munich (1996) and his Dr. rer. nat. from University of Hagen (2001) with a dissertation on modular verification of object-oriented programs. His research focuses on enabling correct software development through programming languages, verification methods, and tools. Key areas include formal verification for Rust and Go programs (Prusti and Gobra projects), separation logic, security protocols, and distributed systems verification. Müller's work emphasizes practical verification techniques for real-world systems, including secure router implementations and smart contract verification. Recent research trends highlight advancements in hyperproperties, modular reasoning for iterators and closures in Rust, and formal validation of verification tools. His methodologies bridge theoretical foundations with industrial applications, addressing challenges in concurrency, memory safety, and security assurance. Notable contributions include the SCION internet architecture, the Prusti verifier for Rust, and formal verification frameworks for distributed systems. His work often integrates rigorous mathematical foundations with scalable software engineering practices.
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.
Kurt Maute is a Professor and Palmer Engineering Chair at the University of Colorado Boulder’s College of Engineering and Applied Science (CEAS). He currently serves as Associate Dean for Undergraduate Education. His academic journey includes a PhD in Civil Engineering (University of Stuttgart, 1998) and a Dipl.-Ing. in Aerospace Engineering (University of Stuttgart, 1992). He has held progressively senior roles at CU Boulder, including Associate Dean for Research (2012–2014), Associate Professor (2006–2012), and Assistant Professor (2000–2006). Maute’s research focuses on structural topology optimization, multi-disciplinary optimization, and aeroelastic systems. He has pioneered methods integrating XFEM, level-set techniques, and isogeometric analysis for complex engineering problems. His work spans fluid-structure interaction, hypersonic vehicle design, and additive manufacturing. His notable contributions include advancements in immersed boundary methods, multi-material optimization, and uncertainty quantification. Awards include the NSF Career Award (2004) and Palmer Endowed Chair (2016–present). Maute’s lab (Aerospace Mechanics Research Center, AMREC) addresses challenges in computational mechanics and multi-physics systems. He has advised numerous students and led grants in battery modeling, topology optimization, and aerospace systems. His research bridges theory and application, emphasizing industrial relevance and computational innovation.
Jeff Offutt is a Professor and Chair of the Department of Computer Science at the University at Albany, College of Nanotechnology, Software, & Engineering. Previously, he was a Full Professor with Tenure in Software Engineering at George Mason University since 2005. He received his PhD in Information & Computer Science from the Georgia Institute of Technology in 1988. His research spans software testing, mutation testing, model-based testing, automatic test data generation, web application testing, and software engineering education. He has led significant projects such as the NSF-funded integration of CS into K-5 classrooms and the Google-funded SPARC project for scalable CS1/CS2 instruction. The 15 most recent articles reflect a continued focus on mutation testing cost reduction, model-based testing oracles, educational innovations, and security aspects of web applications. Trends include empirical validation, industrial applicability, and bridging theory with practice in software testing and engineering education. John Toups Presidential Medal for Excellence in Teaching (2020) George Mason University’s Alumni Association Faculty Member of the Year (2020) Outstanding Faculty Award from the State Council of Higher Education for Virginia (2019) Best Paper Award at ICST 2021 10-Year Most Influential Paper Award at MODELS 2020 George Mason University Teaching Excellence Award (2013) ACM Notable Article Award (2013) Jeff Offutt has mentored numerous graduate students including Upsorn Praphamontripong, Nan Li, and Yu-Seung Ma, and has led major grant-funded projects such as the SPARC educational model and NSF initiatives on K-5 CS integration. His textbook Introduction to Software Testing (with Paul Ammann) is widely adopted globally. He led the MS in Software Engineering program at GMU and developed several new courses in software testing, web engineering, and usability. He pioneered innovative teaching methods using web technologies and asynchronous learning models. He also co-founded the IEEE International Conference on Software Testing, Verification and Validation (ICST) and served as Editor-in-Chief of Software Testing, Verification and Reliability from 2007 to 2019.
Peg Rawes is Professor of Architecture and Philosophy at University College London's Bartlett School of Architecture , where she directs research and leads the MA Architectural History program. Her work bridges architectural theory with philosophy, focusing on relational architectural ecologies through three intersecting areas: human/nonhuman life practices, planetary poetics, and housing ecologies. Director of Research, UCL Bartlett School of Architecture (2023-present) REF2029 Lead for Bartlett School EDICPI for EU TACK project (2020) BAUHOW5 PI for European architecture schools partnership (2016-20) Research explores biophilic design , decolonial architecture , and feminist spatial practices across three streams: Architectural ecologies : Human/nonhuman relations in 'Bioprotopia' (2023), vulnerability visualization (2021) Planetary poetics : Climate emergency dialogues (2021), Irigarayan aesthetics (2020) Housing biopolitics : Care frameworks (2017), Spinozist ethical ratios (2015) Key funded collaborations include EU TACK's Communities of Tacit Knowledge (2020) and AHRC's Equal by Design (2016). She contributes to architectural peer review for journals and international research councils while maintaining global partnerships with institutions like Cornell , ETH Zurich , and University of Minnesota .
Sainyam Galhotra is an Assistant Professor in the Department of Computer Science at Cornell University. His research focuses on developing data science tools for effective and responsible analytics, leveraging techniques from causal inference, data management, theoretical computer science, machine learning, and human-computer interaction to address challenges in trustworthy system design including robustness, explainability, and fairness. Education: Postdoc: University of Chicago PhD: University of Massachusetts Amherst (supervised by Barna Saha) BTech: Indian Institute of Technology Delhi (IIT Delhi) (supervised by Prof. Amitabha Bagchi) Research Interests: Dr. Galhotra's research spans several interconnected areas in data science and artificial intelligence. His work primarily focuses on Responsible Data Science , where he develops methods to ensure that data-driven systems operate fairly and transparently. Within this broad area, his specific interests include: Causal Inference techniques for understanding cause-effect relationships in complex data Algorithmic Fairness approaches to mitigate bias in machine learning systems Explainable AI methods that make black-box models more interpretable Data Management systems for efficient and reliable data processing Entity Resolution techniques for integrating data from multiple sources Trustworthy System Design that addresses robustness, explainability, and fairness His recent publications demonstrate a clear trend toward developing frameworks that combine causal reasoning with practical data management systems, particularly focusing on how to make data-driven decisions more transparent and equitable. The intersection of database systems with fairness considerations appears to be a particularly active area of his research. Scientific Awards: Rising Star in Data Science at the Data Science Institute, UChicago (Oct 2021) Computing Innovation Fellowship Award Recipient (by CRA, CCC and NSF) (Apr 2021) DAAD AInet Fellow (Feb 2021) ACM SIGMOD Entity Resolution Programming Contest – Top 5 finalist (May 2020) Most reproducible paper award in SIGMOD 2018 and 2019 (Jun 2019) First recipient of Krithi Ramamritham Computer Science Scholarship (Jun 2019) Best paper award in SIGSOFT FSE 2017 (May 2017) Dr. Galhotra is actively seeking students to collaborate with on his research projects. His work has been supported by various fellowships and awards, including the prestigious Computing Innovation Fellowship. He has mentored several students through his research projects, with a focus on developing the next generation of data scientists who can build responsible and trustworthy systems. His research group appears to focus on the intersection of database systems and responsible AI, developing tools like HypeR for causal reasoning, Ver for view discovery, and Nexus for correlation discovery in spatio-temporal data. This work suggests a cohesive research agenda centered around making data systems more transparent, fair, and user-friendly.
