جست‌وجوی استاد و پژوهشگر

• Formal analysis
• Software testing
• Programming languages
• +۶ مورد دیگر

Alastair Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he has been a faculty member since 2011. He leads the FastPL research group (formerly Multicore Programming Group), focusing on formal analysis, software testing, and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson earned his BSc (First Class Honors) in Computing Science and Mathematics from the University of Glasgow in 2003, followed by a PhD in Computing Science from the same institution in 2007 under Alice Miller. His academic journey includes positions as an EPSRC Postdoctoral Research Fellow at Oxford, Visiting Researcher at Microsoft Research Redmond, and Research Engineer at Codeplay Software Ltd. His research spans automated reasoning, compiler verification, and GPU programming with significant contributions to software reliability. He pioneered metamorphic testing for graphics drivers through GraphicsFuzz (acquired by Google in 2018) and developed innovative compiler fuzzing techniques. His work addresses critical challenges in memory models, concurrency, and verification of complex systems. Recent publications show increasing focus on applying these techniques to modern challenges including AI-generated code and verification-aware programming languages like Dafny. Donaldson's scientific contributions have been recognized with the 2017 BCS Roger Needham Award, an EPSRC Early Career Fellowship, and multiple best paper awards including EuroSys 2024 (Best Paper), ICST 2024 (Best Industry Paper), and ISSTA 2023 (Distinguished Paper). His 2012 GPUVerify paper received the ACM SIGPLAN Most Influential OOPSLA Paper Award in 2022. As an advisor, Donaldson has mentored numerous PhD students and postdocs, many now in prominent academic and industry positions. His research is supported by Amazon Research Awards (2022-2023) for Dafny ecosystem testing and compiler validation. He previously served as Senior Software Engineer and Visiting Researcher at Google following the GraphicsFuzz acquisition. The FastPL group maintains strong industry connections with Google, Microsoft, and Amazon, ensuring practical relevance of their theoretical work. Donaldson currently serves as Editor-in-Chief of ACM TOPLAS (2025-present) and on program committees for major conferences including PLDI, ICSE, and ASPLOS.

Ke Wuمشاهده پروفایل

استادیار

• Theoretical Cryptography
• Game Theory
• Decentralized Protocols
• +۲ مورد دیگر

Ke Wu is an Assistant Professor at the University of Michigan within the Theory of Computation Lab of the EECS Department. He focuses on theoretical cryptography and game theory, designing incentive-compatible decentralized protocols, with applications in blockchain security and error correction codes. He actively seeks PhD students for the CSE graduate program. University: University of Michigan Department: Electrical Engineering and Computer Science (EECS) Academic Rank: Assistant Professor Research Interests: Ke Wu explores the intersection of cryptography and game theory, emphasizing provably secure decentralized systems. His work includes mechanisms for distributed consensus, fair coin toss protocols, and applications of error correction in cryptographic primitives. He has contributed to transaction fee design, anonymous routing, and synchronization string construction. Recent Publications: His research spans topics such as game-theoretically fair leader election, platform-assisted auctions, and error correction in blockchain contexts. Key venues include CRYPTO, ITCS, and FOCS. Scientific Awards: Stellar Academic Research Grant (2024) CMU CyLab Presidential Fellowship (2022–2023) JP Morgan Chase AI Research PhD Fellowship (2023) Education: Ph.D. from Carnegie Mellon University (advised by Elaine Shi), Master’s from Johns Hopkins University (advised by Xin Li), and B.S. from Fudan University in Information and Computing Science.

Dominik Endresمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Sensorimotor Integration
• Machine Learning
• +۷ مورد دیگر

Dominik Endres is a Professor at the Department of Psychology , Philipps-Universität Marburg , leading the Theoretical Cognitive Science working group. His research spans Cognitive Neuroscience , Sensorimotor Integration , and Machine Learning , with a focus on modeling how the brain represents knowledge and controls movement. His team investigates Movement Primitives in virtual reality, Bayesian Inference in attention control, and Formal Concept Analysis in decoding neural data. Recent work includes reaction time decomposition , VR immersion studies , and assistive technology development for neurological disorders. Publications highlight sensorimotor hierarchies , relational coding , and dynamic human motion modeling . Collaborations include the International Research Training Group 1901 , SFB/TRR 289 , and GRK 2271 . His team includes researchers like Neda Meibodi (PhD student) and Benjamin Knopp (Scientific Staff), with projects involving VR experiments and cognitive modeling .

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۵ مورد دیگر

Aaron Turon is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), where he focuses on foundational aspects of programming languages, concurrency, and formal verification. His work bridges theoretical insights with practical applications, particularly in systems such as Rust and frameworks for reasoning about weak memory models. His research interests include concurrent programming, type systems, formal methods, and scalable distributed systems. He has contributed to seminal projects like the Iris framework for concurrent reasoning and the development of LVars for quasi-deterministic parallelism. Turon's publications emphasize practical formal verification techniques, such as separation logic and logical relations, to ensure correctness in complex systems. His work on Rust highlights the translation of theoretical concepts into industrial-strength tools. He collaborates with academic and industrial partners to advance programming language design, concurrency control, and software engineering practices.

Godmar Backمشاهده پروفایل

دانشیار

• Computer Systems
• Operating Systems
• Programming Languages
• +۵ مورد دیگر

Godmar Back is an Associate Professor in the Department of Computer Science at Virginia Tech's College of Engineering. He holds a Ph.D. in Computer Science from the University of Utah (2002) and specializes in systems research, programming languages, and performance analysis. His work focuses on foundational aspects of operating systems, distributed systems, and cloud computing, with notable contributions to memory management, concurrency, and cybersecurity education. His research explores how hardware and software interact to optimize system performance, including studies on SPEC benchmarking, garbage collection, and undefined behavior in programming languages. He has developed frameworks like CloudBrowser 2.0 for cloud-based applications and the VT-ASOS system for many-core platforms. Back is also active in pedagogy, integrating DevOps practices into undergraduate research and incorporating cybersecurity modules into core curricula through spiral theory-based methods. Key projects include the Pintos instructional operating system kernel, the VirtuOS virtualized OS, and ReplayCache for predictive computations. His work frequently bridges theoretical systems research with practical applications, emphasizing reproducibility and real-world impact. His educational initiatives aim to broaden participation in systems research through high-impact practices and collaborative development environments.

• Formal Verification
• Parallel Programming
• Programming Languages
• +۳ مورد دیگر

Frédéric LOULERGUE is a Full Professor at the University of Orléans, affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) laboratory and part of the LMV research team (Languages, Models, and Verification). His work focuses on formal methods for programming languages, parallel computing, and cybersecurity. He leads research in verified parallel frameworks, distributed systems reconfiguration, and TPM software stack validation. Contact him at frederic.loulergue@univ-orleans.fr or visit his homepage at https://www.univ-orleans.fr/lifo/Members/loulergu/ . Research interests include formal verification of parallel algorithms, deductive program analysis with tools like Frama-C and Coq, and the development of formally verified distributed systems. Recent work emphasizes combining deductive verification with shape analysis, runtime monitoring for security properties, and formalizing decentralized reconfiguration languages in Maude. His publications span topics from verified parallel functional programming (SyDPaCC framework) to cybersecurity in Trusted Platform Modules (TPM). He collaborates on frameworks like WhyBSML for scalable parallel computing and Concerto-D for distributed reconfiguration. No scientific awards are listed, but his contributions are highlighted through extensive peer-reviewed publications and conference activities. Labs/Teams: Member of LIFO's LMV team, contributing to the formal methods research group. Involved in cross-disciplinary projects on cloud computing security and high-performance parallel programming.

• Neuroscience
• Motor Control
• Biomechanics
• +۳ مورد دیگر

Prof. Dr. Andreas Daffertshofer is a Full Professor at Vrije Universiteit Amsterdam (VU Amsterdam), holding concurrent roles in the Neurocontrol department under the Faculty of Behavioural and Movement Sciences, as well as in IBBA, AMS - Ageing & Vitality, and AMS - Rehabilitation & Development. His research focuses on neural mechanisms underlying motor control, gait dynamics, and neuromuscular coordination, with interdisciplinary applications in clinical neurology and developmental disorders. Research interests include cortical contributions to locomotion, phase synchronization in neural networks, and the application of machine learning to neuromuscular assessment. Notable work addresses gait stability, muscle synergies, and the neurophysiological basis of movement disorders such as Parkinson’s disease and cerebral palsy. He has supervised 23 PhD theses, contributing to training the next generation of movement science researchers. His publications span over 230 peer-reviewed articles, exploring topics like EEG source localization, neural mass modeling, and the impact of caffeine on neurological function. Ongoing projects investigate aging-related changes in sensorimotor learning and the role of visual feedback in postural control among neurological patients. Collaborative work includes interdisciplinary projects with the Amsterdam Movement Sciences (AMS) research center and the International Brain and Behaviour Alliance (IBBA), emphasizing translational research to improve clinical outcomes in rehabilitation.

Dimitrios Papageorgiouمشاهده پروفایل

استادیار

• Robotic Control Systems
• Physical Human-Robot Interaction
• Robot Learning
• +۳ مورد دیگر

Dimitrios Papageorgiou is an Assistant Professor specializing in control and automation systems with robotic applications at the Hellenic Mediterranean University. His research develops advanced control frameworks for human-robot collaboration, motion learning, and adaptive manipulation. Key innovations include variable admittance controllers for heavy payload manipulation, constraint-aware motion learning algorithms, and active perception systems for robotic skill transfer. Recent work advances bimanual agricultural manipulation and quadruped locomotion control on challenging terrains. His publication trends demonstrate consistent focus on physical human-robot interaction paradigms, particularly kinesthetic teaching methods and safety-aware collaborative systems. Research integrates hardware development with control theory for industrial and service robotics applications.

• Computer Graphics
• Geometry Processing
• 3D Reconstruction
• +۳ مورد دیگر

Dr. Jing Ren is affiliated with the Department of Computer Science at ETH Zürich, holding a role within the Professorship for Computer Science. Their research focuses on computational geometry, 3D reconstruction, and computer graphics, with notable contributions to shape analysis, non-rigid matching, and fabric modeling. Dr. Ren’s work bridges theoretical advancements with practical applications in textile design, architectural modeling, and medical imaging. They collaborate extensively on projects involving functional maps, optimization algorithms, and geometric morphometrics. Key research interests include: Non-rigid shape correspondence and matching Computational modeling of woven fabrics and textiles 3D face and building reconstruction techniques Efficient spectral and discrete optimization methods Recent publications (2022–2024) emphasize innovations in fabric parameterization, Gaussian noise distribution, and rethinking 3D face reconstruction benchmarks. Their work often employs machine learning and functional map frameworks to solve geometric problems across disciplines. Laboratory and team affiliations are not explicitly detailed in the provided materials, but their research aligns with ETH Zürich’s broader initiatives in computer science and engineering. No grants or advising activities are specified in the current data.

• Distributed Systems
• Concurrency
• Programming Languages
• +۱ مورد دیگر

Elisa Gonzalez Boix is a Professor at the Software Languages Lab, where she leads the Distribution and Concurrency (DisCo) research group. Her work focuses on advancing distributed computing and concurrent programming paradigms within software language design and implementation. Research Interests: Distributed Systems : Scalability, fault tolerance, and network resilience in decentralized architectures Concurrency : Parallel execution models, synchronization primitives, and non-determinism management Programming Languages : Language semantics for distribution/concurrency abstractions Software Engineering : Tooling and methodologies for complex system development As head of the DisCo group, she drives research at the intersection of language theory and practical system engineering, addressing challenges in modern distributed applications through innovative runtime and compiler techniques.

• Algorithms
• Big data analytics
• Blockchain
• +۱۲ مورد دیگر

Dr. Wojciech Golab is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on distributed systems, concurrency control, and persistent memory algorithms. He has received recognition for his work on shared memory algorithms from ACM Computing Reviews. His academic career includes teaching courses like ECE 252, ECE 356, and ECE 454 in the past five years. Education: PhD in Computer Science, University of Toronto (2010) M.Math in Computer Science, University of Waterloo (2004) BSc in Computer Science, University of Toronto (2002) Dr. Golab's research interests span algorithms, blockchain, distributed systems, fault tolerance, and scalable storage solutions. His work emphasizes practical applications of theoretical computer science, such as optimizing transaction processing and ensuring consistency in distributed environments. His recent publications explore topics like detectable synchronization objects for persistent memory, blockchain sharding protocols, and efficient mutual exclusion algorithms under system failures. These contributions highlight advancements in both theoretical foundations and real-world distributed system design. Awards: ACM Computing Reviews 'Notable Computing Items' recognition (2012) Dr. Golab has collaborated with industry partners like Hewlett-Packard Labs, Google, and Cisco to advance research in distributed computing and cloud systems. He currently oversees graduate studies in his department and welcomes applications from prospective students.

Ashwin Daniمشاهده پروفایل

دانشیار

• Robotics
• Autonomous Navigation
• Estimation and Control Theory
• +۵ مورد دیگر

Ashwin Dani is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Connecticut, affiliated with the School of Engineering. His research focuses on robotics, control systems, and autonomous navigation, with applications in manufacturing, biomedical engineering, and environmental monitoring. He holds a Ph.D. in Mechanical and Aerospace Engineering from the University of Florida (2011) and a B.S. in Mechanical Engineering from the University of Pune, India (2005). Prior to his faculty role, he served as a Post-doctoral Research Associate at the University of Illinois at Urbana-Champaign (2011–2013). His research interests span estimation theory, autonomous systems navigation, human-robot collaboration safety, sensor fusion, and neuro-prosthesis control. Notable contributions include advancements in vision-based control, GPS-denied navigation for UAVs, and adaptive control algorithms with safety guarantees. He leads the Robotics & Controls Lab, which develops solutions for industrial automation and assistive robotics. Dr. Dani has been awarded the Innovator’s Invention Award from the University of Florida for his work on nonlinear dynamic estimation. His research has produced patents on structure-motion estimation and over 50 peer-reviewed publications in top journals like IEEE Transactions on Automatic Control and Journal of Field Robotics. He actively explores intersections between machine learning and control theory to enhance system safety and adaptability in dynamic environments. His academic contributions include pioneering work on concurrent learning observers for depth estimation and developing probabilistic frameworks for human intent prediction in collaborative tasks. Ongoing projects focus on safe human-robot interaction protocols, deformable object manipulation, and real-time adaptive control systems for uncertain environments.

• Programming Languages
• Data Structures and Algorithms
• Concurrency
• +۳ مورد دیگر

Matti Rintala is a University Lecturer at Tampere University's Faculty of Information Technology and Communication Sciences, specifically within the Computing Sciences department. His primary responsibilities include teaching core courses such as Principles of Programming Languages and Functional Programming 1, alongside contributing to Data Structures and Algorithms 1. His expertise spans programming languages, data structures, algorithms, and concurrency. Research interests focus on C++ programming paradigms, concurrency mechanisms, and educational technology. Notable work includes leveraging modern C++ features for high-level synthesis, optimizing exception handling in concurrent systems, and analyzing student preferences in hybrid learning environments. His articles consistently address practical challenges in software engineering and distributed systems. While no formal advising or grant details are provided, his teaching and research contributions highlight a commitment to advancing both theoretical and applied aspects of computing sciences. No scientific awards are documented in the provided materials.

Xinyu Fengمشاهده پروفایل

استاد

• Programming Languages
• Formal Methods
• Program Verification
• +۴ مورد دیگر

Xinyu Feng is a Professor at the Department of Computer Science and Technology, Nanjing University, with research spanning programming languages, formal methods, and system software verification. His work focuses on developing rigorous frameworks for certifying low-level system programs, particularly those involving concurrency, preemptive threads, and hardware interrupts. Nanjing University, China Huawei (collaboration) Yale University, PhD in Computer Science (2007) Research Interests: His research integrates Separation Logic and Rely-Guarantee Reasoning to create modular verification techniques for concurrent systems. Key areas include: Formal verification of OS kernels and hypervisors Concurrency control in preemptive and interrupt-driven environments Parameterized memory models for relaxed concurrency semantics Certified compilation and proof-carrying code Optimistic concurrency algorithms and non-blocking data structures Modular verification of synchronization primitives Article Trends: His publications emphasize modular and compositional methods for concurrent program verification, with a strong focus on practical applications in system software. Recurring themes include integrating formal reasoning with real-world challenges like hardware interrupts, preemptive scheduling, and SDN programming. Scientific Awards: PLDI'19 Distinguished Paper Award Professional Leadership: Xinyu Feng has served on program committees for leading conferences (POPL, PLDI, ICFP, CAV) since 2005 and chairs sessions at events like PLDI and POPL. He actively contributes to advancing formal verification standards in the field.

Nikita Kovalمشاهده پروفایل

پژوهشگر

• Concurrent Programming
• Kotlin Coroutines
• Concurrent Data Structures
• +۶ مورد دیگر

Nikita Koval is a Researcher at JetBrains , specializing in concurrent programming, Kotlin coroutines, and testing frameworks. His work bridges academic research with industrial application, focusing on synchronization primitives, lock-free data structures, and JVM-based concurrency tools. Academic rank: Researcher Affiliation: JetBrains Research interests include: Concurrent algorithm design and optimization Formal verification of synchronization mechanisms Testing frameworks for JVM-based languages Memory-efficient lock-free data structures Scalability in coroutine communication Distributed systems debugging Publication trends show a focus on Kotlin coroutines, JVM concurrency, and testing frameworks like Lincheck. His work spans algorithm design (union-find, queues), formal verification (CQS), and practical tools for concurrency testing (Lincheck) across conferences like PPoPP, PLDI, and ECOOP. Scientific recognition: Nikita received the Best Paper Award at OPODIS 2019 for his work on concurrent union-find algorithms. His contributions to Lincheck and CQS have been adopted into Kotlin's core libraries. Workshop leadership: He offers a 4-day corporate workshop on concurrent algorithms, covering testing, debugging, and implementation of lock-free data structures, now booked for Q3/Q4 2025. The curriculum includes hands-on Java/Kotlin coding with topics like segment queues, fetch-and-add queues, flat combining, and concurrent hash tables.