Roy Hermanns is a Researcher at RWTH Aachen University, affiliated with the Department of Computer Science. He is part of the Software Modeling and Verification Group led by Professor Joost-Pieter Katoen and collaborates closely with the Quantum Technology Group under Professor Hendrik Bluhm. His research focuses on quantum compilation, specifically addressing the generation, scheduling, and optimization of operations for quantum processors, particularly those employing shuttling-based qubit architectures. Key research interests include qubit routing via multi-agent pathfinding methods, quantum error correction, and device-level optimization for quantum processors. He is open to supervising Bachelor’s/Master’s theses in quantum compiler optimization, though no current openings are listed. Roy is not currently involved in formal teaching activities. His work contributes to advancements in quantum computing infrastructure, aiming to improve the practical implementation of quantum algorithms through hardware-aware compilation techniques.
Edwin Brady is a Reader in the School of Computer Science at the University of St Andrews. His research focuses on dependent types, programming languages, and their application to verification, DSLs, and compiler design. He is a key contributor to the Idris programming language, emphasizing type-driven development and formal methods. Brady supervises PhD students including Thomas Hansen, Ellis Kesterton, Bhakti Shah, and Constantine Theocharis. His work spans foundational research in type systems, practical compiler implementation, and tool development for dependently typed languages. Notable contributions include frameworks for resource-dependent DSLs and type-level property-based testing. Brady has led projects such as the EPSRC-funded 'Type-Driven Verification of Communicating Systems' and contributed to the EU-funded ADVANCE initiative on concurrency engineering. Research Interests: Dependent types, functional programming, program verification, DSLs, compilers. Tools Developed: Idris programming language, type-level testing frameworks. Professional Activities: Organized Doors Open @ Computer Science events (2023–2025), presented at Lambda World and Idris workshops. His publications emphasize practical applications of type theory to ensure correctness in concurrent systems, session protocols, and refactoring tools. Brady’s work bridges theoretical foundations with real-world software development challenges.
Professor Michael Ruzhansky is a faculty member at Queen Mary University of London, where he holds the position of Professor of Mathematics in the School of Mathematical Sciences. His research focuses on advanced areas such as partial differential equations, harmonic analysis, fractional calculus, and pseudo-differential operators. He is affiliated with the Centre for Geometry, Analysis, and Gravitation, reflecting his interdisciplinary research interests. Affiliations: School of Mathematical Sciences, Department of Mathematics Key Research Areas: PDEs, harmonic analysis, fractional calculus, functional inequalities, and mathematical physics His work spans theoretical contributions to operator theory, spectral analysis, and applications in mathematical physics. Recent research emphasizes fractional dynamics, non-local equations, and inequalities on Lie groups. He has published extensively in leading journals, with a focus on advancing core mathematical analysis and its applications. Notable research includes studies on inverse problems for fractional equations, Schatten classes on noncommutative spaces, and Hardy-type inequalities. His expertise intersects pure and applied mathematics, contributing to both foundational theory and real-world modeling challenges.
Chao Li is a Lecturer of Chinese at the Georgia Institute of Technology's School of Modern Languages, part of the Ivan Allen College of Liberal Arts. He has been with Georgia Tech since 2001, focusing on teaching Chinese language at all proficiency levels and co-directing the Chinese Language for Business and Technology (LBAT) Program since 2006. His expertise includes developing online Chinese language courses, creating multimedia content, and compiling grammatical notes for effective language learning materials. Chao Li holds a Master of Arts in International Relations from Beijing Institute of Foreign Affairs and a Bachelor of Arts in Economics and Chinese from Yunnan University, China. He is a key figure in advancing online Chinese language education at Georgia Tech, emphasizing the integration of technology into language pedagogy. His work bridges language instruction with business and technology contexts, reflecting his commitment to practical, industry-relevant language training. His professional contributions include pioneering efforts in online course development, particularly in designing interactive and adaptive learning environments. While no formal awards are listed, his role in shaping Georgia Tech's Chinese language program highlights his significant impact on language education innovation. Chao Li’s teaching philosophy centers on student engagement through culturally immersive and technologically enhanced methodologies.
Dr.-Ing. Volkmar Sieh is a researcher at the Chair of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg. His work focuses on fault-tolerant systems, real-time embedded systems, and virtualization technologies. He leads the FAUmachine project, developing advanced virtualization techniques for system simulation and fault injection. His research also includes energy-efficient real-time systems and hardware/software co-design. Research Activities: Design of Virtual Machines (FAUmachine) Restoration of Zuse Z23 computer Real-Time Systems with Mixed Criticalities WCET and WCEC Analysis Toolchains Energy-Neutral Real-Time System Kernels Key Contributions: He has published extensively on fault tolerance mechanisms, embedded system reliability, and energy-aware real-time systems. His work on the UMLinux tool and FAUmachine framework has advanced techniques for testing fault tolerance in networked systems and comprehensive system simulation. Technical Expertise: Virtualization and Hardware Simulation Real-Time OS Design WCET Analysis Energy Efficiency in Embedded Systems Fault Injection and Reliability Validation Labs/Projects: He is part of the FAUmachine research group, pioneering virtualization tools for complex system analysis and fault tolerance evaluation. His work integrates VHDL-based hardware models with software systems for comprehensive testing environments.
Tobias Klaus is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg. His work focuses on real-time systems, distributed systems, and operating systems, with a particular emphasis on embedded real-time control and multicore processing. He has contributed to projects such as qron OS, AORTA, and the RTSC compiler framework. His research addresses challenges in real-time scheduling, job-level dependencies, and quality-aware system design. Education and Background: No explicit education details provided in the text. Research Interests: Klaus’s research spans real-time systems, distributed architectures, and embedded control systems. He explores topics such as deadline-driven scheduling, static analysis for job migration optimization, and tool-supported design of time-triggered systems. His work often bridges theoretical foundations with practical implementation in embedded and robotics domains. Grants and Funding: No specific grants or funding opportunities are mentioned in the text. Awards: No scientific awards explicitly listed. Teaching and Advising: Klaus has been involved in teaching courses such as Real-Time Systems, System Programming, and Distributed Systems. He has advised multiple theses, including projects on distributed real-time systems, WCET analysis, and multicore resource protocols. Notable advisees include Hausmann Jannis, Florian Güthlein, Thomas Reichinger, and Felix Bräunling. Labs and Teams: He contributes to interdisciplinary projects like the I4 Copter quadrocopter system and collaborates on frameworks such as RTSC and AORTA. His work often involves cross-disciplinary efforts in real-time control and embedded systems.
Keith D. Cooper is the L. John and Ann H. Doerr Professor in Computational Engineering and Professor of Computer Science at Rice University. He holds a courtesy appointment in the Department of Electrical and Computer Engineering. His research focuses on program analysis, optimization, and compiler construction. He has authored influential textbooks like Engineering a Compiler and has produced 18 Ph.D. students. Cooper has served in key administrative roles, including Chair of Computational and Applied Mathematics (2019–2020), Associate Dean for Research in the Brown School of Engineering (2012–2018), and Co-Director of the Ken Kennedy Institute for Information Technology (2015–2019). Education: Ph.D. (1983), M.A. (1982), and B.S. (1978) in Mathematical Sciences and Electrical Engineering from Rice University. Research Interests: Program analysis and optimization, compiler design, parallel computing, adaptive compilation, and memory hierarchy optimization. His work includes foundational contributions to interprocedural analysis, register allocation (Chaitin-Briggs algorithm), and compiler frameworks like ParaScope. Awards: ACM Fellow, George R. Brown Award for Superior Teaching (2019), and the L. John and Ann H. Doerr Chair (2019). Grants & Leadership: Played a pivotal role in Rice’s Data Science Initiative and the design of Duncan Hall. Advised over 25 students and contributed to numerous grants in compiler research and high-performance computing. Labs & Teams: Key contributor to the Rice Compiler Group and the Ken Kennedy Institute, advancing research in compilers, parallel computing, and computational science.
Rebecca Schreib serves as an Assistant Teaching Professor and Director of Undergraduate Studies in Rice University's Department of Computer Science. She holds a Ph.D., M.S., and B.S. in Computer Science from Rice University (2019, 2015, 2014 respectively). Her research focuses on computer science education, virtualization, and embedded runtime systems. Her educational background includes a doctoral emphasis on designing personalized interactive learning tools for large introductory courses. Key research contributions include MemStep (2024), collaborative computational thinking courses (2020), and automated assessment systems (2016–2017). Her work spans both educational technology and embedded systems, with a focus on bridging theory-practice gaps in programming education while advancing runtime system reliability for constrained environments. She has developed tools that enhance student engagement and automated systems for testing and memory management. While no scientific awards are listed, her publications reflect sustained innovation in educational technology and embedded computing since 2012. Her advising and grant activities are not explicitly documented here. She contributes to Rice's undergraduate program infrastructure through her directorship role.
Yuke Wang is an incoming Assistant Professor at Rice University's Department of Computer Science starting Fall 2025. He earned his Ph.D. in Computer Science from the University of California, Santa Barbara (2024) and B.E. in Software Engineering from the University of Electronic Science and Technology of China (2018). His research focuses on optimizing deep learning systems through compiler and hardware co-design, with expertise in GPU acceleration, parallel computing, and distributed training. Education: Ph.D., UC Santa Barbara (2024); B.E., UESTC (2018). Professional experience includes postdoctoral research at Amazon AWS AI and internships at NVIDIA, Microsoft Research, and Alibaba DAMO Academy. Research interests include accelerating graph neural networks (GNNs), recommendation systems, and large language models (LLMs). He has developed frameworks like GNNAdvisor, MGG, and ZEN to enhance efficiency and scalability in deep learning workloads. His work has been recognized with awards such as the NVIDIA Graduate Fellowship and ACM PACT Student Research Competition. Awards include NVIDIA Graduate Fellowship (2022-2023), UCSB Dissertation Fellowship (2023), and multiple best paper nominations. He actively serves on program committees for top conferences like OSDI, ASPLOS, and ICS. Current hiring: Seeking graduate/undergraduate students for projects in deep learning systems, compiler optimization, and GPU acceleration. Collaborates closely with industry partners including NVIDIA and Amazon.
Assoc Prof Anupam Chattopadhyay is an Associate Professor in the College of Computing & Data Science at Nanyang Technological University (NTU), Singapore. He also holds a courtesy appointment in the School of Physical & Mathematical Sciences. His research focuses on computer architecture, security, design automation, and quantum computing. Anupam received his PhD from RWTH Aachen University in 2008, followed by roles at CoWare R&D and RWTH Aachen as a Junior Professor before joining NTU in 2014. Education: B.E., Jadavpur University, India MSc, ALaRI, Switzerland PhD, RWTH Aachen University, Germany Research Interests: Anupam’s work spans quantum computing, hardware security, AI security, post-quantum cryptography, and emerging technologies. His contributions include novel high-level synthesis techniques for cryptography, reliability estimation flows for embedded processors, and exploration of coarse-grained reconfigurable architectures. His research has been featured in major outlets like The Economist and Asian Scientist. Awards: Borcher's plaque (2008) for outstanding doctoral dissertation Nomination for Best IP Award (ACM/IEEE DATE 2016) Nomination for Best Paper Award (International Conference on VLSI Design 2018) Advising & Grants: Anupam leads a team of over 20 researchers, overseeing projects funded by various grants. He has advised numerous doctoral students and collaborates with institutions like Temasek Labs and the Indian Statistical Institute. Labs & Teams: His research group focuses on advanced topics in secure computing, quantum-resistant systems, and hardware-software co-design, leveraging cutting-edge tools and platforms for next-generation technologies.
Harry Xu is a Professor in the Computer Science Department at the Samueli School of Engineering , University of California, Los Angeles . His research spans computer systems, programming languages, compilers, and AI infrastructure. He co-founded BreezeML for GenAI risk management and has held visiting roles at Microsoft Research and IBM Watson Research Center. Current research focuses on user-defined clouds and AI application infrastructures Founded BreezeML and contributed to Niijima (SOSP'19) and Yak GC (OSDI'16) Developed VQPy, integrated into Cisco's DeepVision Scientific Awards 2018 Dahl-Nygaard Junior Prize ACM Distinguished Scientist Advising and Collaborations Current students: Shan Yu, Zhenting Zhu, Shu Anzai, Yicheng Liu Alumni: Shi Liu (Databricks), Jiyuan Wang (AWS), Haoran Ma (ByteDance AI Infra), Yifan Qiao (UC Berkeley), Christian Navasca (BreezeML), Pengzhan Zhao (BreezeML co-founder)
Andrei Popescu is a Senior Lecturer (Associate Professor level) in the Department of Computer Science at the University of Sheffield, where he conducts research in formal methods, proof assistants, and information flow security. He previously held academic positions at Middlesex University and TU Munich. University: University of Sheffield Department: Department of Computer Science Previous Affiliations: Middlesex University, TU Munich His research focuses on the logical foundations and practical applications of proof assistants, particularly Isabelle/HOL. He has made foundational contributions to inductive and coinductive datatypes, syntax with bindings, higher-order logic, and the formal verification of secure systems. His work bridges theoretical logic with real-world systems such as conference management (CoCon) and social media platforms (CoSMeDis). The recent publications highlight a strong trend in formalizing deep logical results (e.g., Gödel’s incompleteness theorems), advancing datatype theory, verifying complex security properties, and applying formal methods to practical systems. His work consistently appears in top-tier venues such as POPL, CAV, ITP, and CSF. Distinguished Paper Award at POPL 2025 Distinguished Paper Award at POPL 2024 Distinguished Paper Award at POPL 2023 RS 3 Best Paper Award for 2012–2013 He has advised PhD students including Lorenzo Gheri and has been actively involved in organizing major academic events such as the Midlands Graduate School, CPP, ITP, and TABLEAUX conferences. He has served on numerous program committees including POPL, ITP, CSF, and CAV, and has led research projects funded by VeTSS and industrial partners. He is a key contributor to the Isabelle proof assistant ecosystem, particularly in the development of the (co)datatype package and foundational consistency results. His work combines deep theoretical insight with practical implementation, making significant impacts in both academia and applied security.
Michael E. Cotterell is a Senior Lecturer of Computer Science and Undergraduate Coordinator at the University of Georgia's School of Computing. He holds a B.S. (2011) and Ph.D. (2017) in Computer Science from UGA. His roles include directing the Computer Science Undergraduate Assistant (CSUA) and UGAHacks experiential learning programs. He chairs the Undergraduate Program & Curriculum Committee and serves on UGA’s University Council. Dr. Cotterell’s teaching career began in 2012 with Software Development courses, transitioning to full-time instructor in 2015. He has won multiple teaching awards, including the Teaching Excellence in Computer Science Award (2018, 2020) and was promoted to Senior Lecturer in 2021. He has also served as a UGA Online Learning Fellow, Writing Fellow, and Teaching Academy Fellow. His research interests span computational education, active learning methodologies, and technical fields like big data analytics, ontology-based semantics, and energy informatics. His work bridges pedagogical innovation with applied computational science. Dr. Cotterell’s publications focus on improving educational practices, predictive analytics, and interdisciplinary applications of computer science. His most recent work emphasizes student sentiment analysis in active learning environments and scalable energy systems modeling. Awards include the 2016 Outstanding Faculty Teaching Award and multiple fellowships recognizing his contributions to pedagogy and online education. He oversees undergraduate program development and coordinates experiential learning initiatives, emphasizing hands-on learning through hackathons and assistantship programs.
Mae Milano is an Assistant Professor in the Department of Computer Science at Princeton University. She joined in 2024 after earning her Ph.D. from Cornell University in 2020. Her research focuses on designing programming languages to address challenges in distributed systems, with particular emphasis on concurrency safety, language interoperability, and formal verification. Education: Ph.D. in Programming Languages and Systems, Cornell University, 2020 Research Interests: Milano's work bridges programming languages and distributed systems. She develops type systems for safe concurrency (e.g., fearless concurrency ), designs languages for distributed state management (e.g., Gallifrey, Hydro), and explores compiler techniques for interoperability between systems. Her projects include: Fearless Concurrency – Safe shared-memory programming Gallifrey – Language for geographically distributed applications Hydro – Cloud-native programming models Grants & Collaborations: Milano collaborates with researchers like Alvin Cheung (University of Washington) and Joseph M. Hellerstein (UC Berkeley). Her work has been supported by projects such as the Hydro Framework and the Gallifrey language initiative. Labs & Teams: She leads the Princeton Systems Group and collaborates with the Programming Languages Group , fostering interdisciplinary research between PL and distributed systems.
Hubie Chen is a Senior Lecturer in the Department of Informatics at King's College London, part of the Faculty of Natural, Mathematical & Engineering Sciences. Prior to working in the UK, he was an Ikerbasque Research Professor in Donostia-San Sebastian, Spain. He has held invited positions at institutions such as École Polytechnique, Humboldt-Universität zu Berlin, and Universität Wien. Dr. Chen received his PhD and BS degrees in computer science and mathematics from Cornell University and Stanford University, respectively. His academic career spans multiple prestigious institutions across Europe and the United States, demonstrating his international recognition in theoretical computer science. Dr. Chen's research focuses on the theoretical foundations of computer science, with particular expertise in database theory, logic in computer science, computational complexity, and constraint satisfaction. His work bridges theoretical computer science with practical database applications, exploring the fundamental limits and possibilities of computation and data management. His recent book "Computability and Complexity" published by MIT Press provides a comprehensive introduction to automata theory, computability theory, and complexity theory, including parameterized complexity. Dr. Chen's publication record demonstrates a consistent contribution to top-tier theoretical computer science venues. His recent work shows a strong focus on constraint satisfaction problems, database query theory, and computational complexity. He has made significant contributions to understanding the theoretical foundations of database queries, constraint satisfaction, and computational complexity, with publications in prestigious venues such as Computational Complexity, ACM Transactions on Computation Theory, and proceedings of ICDT, PODS, and LICS. Dr. Chen has received recognition for his work, including the ICDT 2017 Best Paper Award. His research has been supported by the Engineering and Physical Sciences Research Council (EPSRC), with active projects on "Algebraic methods for Quantified Constraints" (2024-2026) and "Query Evaluation" (2023-2026). Within King's College London, Dr. Chen is affiliated with the Software Systems Group and contributes to the broader research ecosystem of the Department of Informatics, which includes hubs for Trusted Autonomous Systems, Finance (FinTech), Algorithms and Data Analysis, and Security.
