جست‌وجوی استاد و پژوهشگر

José Proençaمشاهده پروفایل

استادیار

• Formal Methods
• Concurrency
• Coordination Models
• +۵ مورد دیگر

José Proença is an Assistant Professor at the Faculty of Sciences of the University of Porto (FCUP) and a Researcher at CISTER Research Centre, collaborating with INESC TEC. He specializes in formal methods for component-based systems, concurrency, and cyber-physical systems. His research focuses on coordination models, embedded systems, and software product lines, with contributions to frameworks like Reo and LooCI. Education: PhD in Concurrent & Distributed Computing (Leiden University, 2011), BSc+MSc in Mathematics & Computer Science (University of Minho, 2005) Research interests include formal verification, runtime verification for real-time systems, and hybrid systems programming. He coordinates projects like Ibex (FCT-funded) and has been involved in ECSEL projects like VALU3S. Supervised numerous MSc and PhD students, including work on CPS monitors, hybrid simulations, and variability analysis. Teaching includes Concurrent Programming, Algorithms, and Software Verification at the MSc level. Active in program committees for conferences like COORDINATION and SAFECOMP, and steering committee roles. Tools developed include Lince and RebeCaos for system simulation and formal analysis.

Arvindمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Computing
• Memory Systems
• +۳ مورد دیگر

Arvind is the Johnson Professor of Computer Science and Engineering at MIT and a member of CSAIL (Computer Science and Artificial Intelligence Laboratory). He holds a B.Tech. from IIT Kanpur (1969), M.S. and Ph.D. from the University of Minnesota (1972-1973). His research focuses on computer architecture, parallel computing, memory models, and hardware synthesis. He pioneered dataflow architectures and developed the pH programming language. Notable projects include the Monsoon dataflow machine and Sandburst, a semiconductor company for 10G-bit Ethernet routers. Arvind has received prestigious awards like the IEEE Harry H. Goode Memorial Award (2012) and ACM Fellow (2007). He co-founded Bluespec Inc. and managed collaborations like Nokia-CSAIL (2006-2010). His work spans academia and industry, emphasizing scalable systems and secure computing. Research interests include synthesis/verification of digital systems, graph algorithms, and weak memory models. Current projects explore next-gen Graph AI systems and financial security applications.

• Computer Architecture
• Computer Systems
• Compilers
• +۸ مورد دیگر

José Cano Reyes is a Senior Lecturer (Associate Professor) at the University of Glasgow's School of Computing Science, leading the Glasgow Intelligent Computing Lab (gicLAB) and serving as deputy Head of the GLAsgow Systems Section (GLASS). His academic career includes postdoctoral roles at the University of Edinburgh (2014-2018) and Universitat Politècnica de Catalunya (2012-2013), with a PhD and engineering degree from Universitat Politècnica de Valencia (2004-2012). He has held visiting and guest lecturer positions at Edinburgh and Glasgow across computer architecture, compilers, and embedded systems topics. Research focuses on hardware-software co-design for edge AI, including DNN acceleration (FPGA/GPU), encrypted AI systems, and secure mission-critical SoCs. Key projects include EU's dAIEDGE, EPSRC IDEAL, and UKRI AppControl. He leads over 15 research staff and students in areas like quantization, sparsity exploitation, and robust AI deployment. Notable contributions span 100+ peer-reviewed publications across top venues (ISCA, IJCNN, IEEE TPDS) and 3 authored books on ad hoc networks and embedded systems. Academic service includes organizing 20+ conferences (ISPASS, Euro-Par, ASPLOS) and serving on editorial boards for ACM TACO and IEEE TPDS. His educational efforts include teaching Computer Architecture (Year 4), Computer Systems (Year 1), and supervising over 20 PhD/MSc students since 2017.

Anton Burtsevمشاهده پروفایل

دانشیار

• Operating Systems
• Computer Security
• Formal Verification
• +۳ مورد دیگر

Anton Burtsev is an Associate Professor at the Kahlert School of Computing, University of Utah. His research focuses on redefining operating system architectures to address modern challenges like security attacks, data center workloads, and heterogeneous hardware. He leads the Mars Research Group, developing systems like the formally verified Atmosphere microkernel in Rust/Verus, and the high-performance DRAMHiT hash table. Key projects include Rust for Linux kernel integration, verified drivers (Veld), and isolation mechanisms like RedLeaf OS. Research interests include kernel isolation, formal verification, language safety (Rust), and overcoming the memory wall. Current work emphasizes clean-slate OS designs and retrofitted security solutions for existing kernels. Collaborative projects include Horizon (secure scientific cloud computing) and RedLeaf OS verification efforts. Advising undergraduate to PhD students interested in OS research. Notable grants include NSF CAREER (NgOS) and collaborative NSF grants on verified systems. Active in the MARS reading group and open-source contributions via repositories.

• Formal Verification
• Parallel and Distributed Systems
• GPU Programming
• +۴ مورد دیگر

GANESH GOPALAKRISHNAN is a Professor of Computer Science at the University of Utah's School of Computing. His work focuses on formal verification of parallel/distributed systems, GPU programming, and numerical error analysis. He has contributed to tools like ISP for MPI verification, ARCHER for OpenMP race detection, and FLiT for floating-point consistency testing. His research spans theoretical foundations (e.g., concurrency models) and practical applications (e.g., GPU error analysis). Recent work includes advancing formal methods for mixed-precision computing and resilience in exascale systems. Notable projects include rigorous error estimation for floating-point operations and compiler-assisted verification techniques. Research Interests: Formal Verification of Parallel Systems | GPU & HPC Correctness | Floating-Point Numerical Analysis | Concurrency Bugs | Tools for Distributed Systems. Current work emphasizes hybrid approaches combining formal methods with dynamic analysis to address emerging challenges in heterogeneous computing architectures. Articles Trends: Recent publications (2020–2025) emphasize GPU verification (data races, error analysis), mixed-precision computing (matrix operations, tensor cores), and resilience in HPC systems. Tools like FPDetect and BinFPE highlight practical contributions to error detection in production runs. Workshops (DOE/NSF) indicate leadership in defining correctness strategies for exascale computing. Labs/Teams: Leads research groups focused on formal methods for parallel computing and numerical system reliability. Collaborations include Argonne National Lab, NVIDIA, and LLNL on verification tools and HPC correctness frameworks.

Benjamin Lee Greenmanمشاهده پروفایل

استادیار

• Programming Languages
• Gradual/Migratory Type Systems
• Language Interoperability
• +۴ مورد دیگر

Benjamin Lee Greenman is an Assistant Professor at the Kahlert School of Computing , part of the John and Maria Price College of Engineering at the University of Utah. His research focuses on programming languages, gradual/migratory type systems, formal methods, and human factors in software development. He holds a Ph.D. from Northeastern University (2020), a CIFellows postdoc at Brown University (2020–2022), and degrees from Cornell University (B.S. in ILR, M.Eng. in CS). Key projects include: Forge: A tool for teaching formal methods with lightweight model finding. FlowFPX: Tools for debugging floating-point exceptions in scientific computing. LTL Tutor: An adaptive learning system addressing temporal logic misconceptions. Gradual Typing Benchmarks: Evaluating performance and guarantees of type systems. His work emphasizes rigorous methods for language design, including empirical studies, performance evaluation, and human-centered approaches. Recent contributions include exploring misconceptions in LTL education and advancing type system interoperability between typed and untyped code. Teaching roles include courses on compilers, software verification, and programming languages. He advocates for practical tools like Rhombus (Python-like syntax with Lisp macros) and Static Python ’s sound gradual typing system.

• Compilers
• Software Testing
• Formal Verification
• +۳ مورد دیگر

John Regehr is a Professor in the School of Computing at the University of Utah. His research focuses on compilers, formal verification, software testing, and embedded systems. He has contributed to tools like Alive2, YARPGen, and ARMor, which address compiler correctness, fuzz testing, and secure isolation. His work emphasizes uncovering compiler bugs, optimizing low-level code, and ensuring system reliability. Key collaborations include Eric Eide, Yang Chen, and Nuno P. Lopes. His articles span compiler verification, fuzzing techniques, and embedded system safety, reflecting a strong commitment to both academic rigor and practical impact. Research interests include compiler optimization validation, undefined behavior analysis, and program synthesis. His work on peephole optimizations and formal methods has influenced LLVM and industry practices. He also explores scheduling algorithms for real-time systems and memory safety in constrained environments like TinyOS. Notable contributions include foundational papers on compiler bug detection (e.g., 'Finding and understanding bugs in C compilers') and tools like Minotaur for SIMD optimization. His lab's work often bridges theory and practice, with applications in security, performance, and embedded software reliability.

• High-Performance Interconnection Networks
• Computer Architecture
• Network Simulation
• +۷ مورد دیگر

Francisco J. Andújar Muñoz is an Associate Professor at the University of Valladolid in the Department of Computer Science since January 2024. His career spans multiple institutions including Universidad de Castilla-La Mancha (2008-2015) and Universitat Politècnica de València (2017-2018), with academic roles ranging from Research Assistant to Juan de la Cierva Formación Researcher. PhD in Advanced Computer Science Technologies (2011-2015) MsC in Advanced Computer Science Technologies (2010-2011) Computer Science Engineering (2008-2010) Computer Science Technical Engineering (2004-2008) His research focuses on high-performance interconnection networks , with significant contributions to quality-of-service mechanisms, energy-efficient network topologies, and heterogeneous programming optimization. He maintains the open-source VEF Traces framework for network workload modeling. Recent publications (2023-2025) demonstrate expertise in FPGA high-level synthesis portability, SYCL-based GPU optimization, and machine learning applications for Twitch streaming analysis. His work combines theoretical network design with practical implementations in the Journal of Supercomputing and IEEE Transactions on Computers .

Furkan Kıraçمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Furkan Kıraç is an Assistant Professor in the Computer Science Department at Özyeğin University, specializing in Computer Vision and Machine Learning . He previously served as a Part-Time Instructor at the same university (2012-2013) and as a Research Assistant at Boğaziçi University (2009-2013). Education: PhD in Computer Engineering, Boğaziçi University (2013) MS in Systems and Control Engineering, Boğaziçi University (2002) BS in Mechanical Engineering, Boğaziçi University (2000) His research focuses on real-time hand pose estimation , deep learning , and computer vision applications in industrial automation. Recent publications highlight his work on pedestrian tracking, spatio-temporal mapping, and image processing pipelines for test oracle automation. Notable achievements include founding two computer vision companies ( Proksima and Fortibase ) and receiving awards at SIU conferences (2004, 2005, 2012). He has contributed to projects funded by TÜBİTAK and the Scientific and Technical Research Council of Turkey. Scientific Awards: 3rd place in best demo award (SIU 2012) Best application paper award (SIU 2012) 3rd degree in Turkish National Science Competition (1994, 1995) Gold/Silver/Bronze medals in National Computer Science Olympiads

José Carlos Cabaleiro Domínguezمشاهده پروفایل

استاد

• High performance computing
• Parallel systems architecture
• Parallel algorithms
• +۶ مورد دیگر

Dr. José Carlos Cabaleiro Domínguez is a Full Professor in the Department of Electronics and Computing at the University of Santiago de Compostela's Faculty of Computing, Spain. He has been a member of CiTIUS (Centro singular de investigación en tecnoloxías da información e comunicación) since 2010 and was promoted to Full Professor in 2022 after serving as an Associate Professor since 1994. His academic journey began with a BS and PhD in Physics from the University of Santiago de Compostela in 1989 and 1994 respectively, with initial teaching experience at the University of A Coruña from 1990-1994. His research focuses on high performance computing, particularly in parallel systems architecture, development of parallel algorithms for irregular problems with sparse matrices, performance prediction and improvement of parallel applications, memory hierarchy optimization, and applications for grid and cloud computing. He has developed significant expertise in 3D point cloud processing from remote sensors like LiDAR, with applications in urban infrastructure analysis, powerline detection, and route planning. Analysis of his recent publications reveals a strong emphasis on optimizing resource allocation for big data frameworks, developing deep learning applications for point cloud classification, and creating efficient algorithms for powerline detection in LiDAR surveys. His work bridges theoretical computer science with practical applications in geospatial analysis and infrastructure monitoring. His research has been published in top-tier journals including IEEE Transactions, ISPRS Journal of Photogrammetry and Remote Sensing, and Future Generation Computer Systems, reflecting his significant contributions to the field of high performance computing and its applications. Dr. Cabaleiro actively collaborates with researchers across multiple institutions, as evidenced by his extensive publication record with co-authors from various universities and research centers. His work demonstrates a consistent trajectory of advancing parallel computing techniques while applying them to increasingly complex real-world problems involving large-scale geospatial data.

Ziyang Liمشاهده پروفایل

استادیار

• Neurosymbolic Programming
• Machine Learning
• Programming Languages
• +۵ مورد دیگر

Ziyang Li is an Assistant Professor of Computer Science at Johns Hopkins University and a member of the Data Science and AI Institute. He holds a Ph.D. in Computer Science from the University of Pennsylvania (2025) and dual bachelor's degrees in Computer Science and Mathematics from UCSD (2019). Research Areas: Neurosymbolic Programming, AI4Code His research bridges programming languages and machine learning, focusing on neurosymbolic methods that combine symbolic reasoning with learning-based techniques. Applications span software security, computer vision, natural language processing, bioinformatics, and clinical decision-making. He developed Scallop , a neurosymbolic programming language, and Lobster , a GPU-accelerated framework for neurosymbolic applications, with impacts in cybersecurity and biomedical domains. Recent publications highlight neurosymbolic approaches for RNA structure prediction, Long COVID modeling, and safety-critical systems. His work emphasizes data-efficient learning, weak supervision, and hybrid AI for scalable reasoning. Scientific Awards : AWS Fellowship (2023) KPCB Fellows, Engineering (2018) NIH L3C Honorable Mention Award Li has mentored students including Jason Liu, Felix Zhu, and Eric Zhao, and served as Teaching Assistant for courses at UPenn and UCSD. He co-organized the TACPS Workshop and reviewed for NeurIPS, ICLR, and ICML.

Marco Vassenaمشاهده پروفایل

استادیار

• Security
• Programming Languages
• Cyber Security
• +۳ مورد دیگر

Marco Vassena is an Assistant Professor at the Department of Information and Computing Sciences, Utrecht University, within the Faculty of Science. He focuses on developing principled methods for building secure systems, bridging Security and Programming Languages research communities. His work applies type systems, compilers, program analysis, and verification to ensure reliable security guarantees in software systems. PhD in Computer Science from Chalmers University of Technology Visiting Assistant Professor at Stanford Postdoctoral Researcher at CISPA Helmholtz Center for Information Security Member of the CISPA-Stanford Center for Cybersecurity His research spans language-based security (constant-time programming, memory safety, information flow control), software defenses against Spectre and side-channel attacks, and WebAssembly sandboxing. He leads projects like MSWasm and Blade, targeting microarchitectural attack mitigation through formal verification and compiler design. Scientific recognition includes the Veni Grant (2023). Current projects explore speculative execution security, dynamic information flow control, and secure WebAssembly implementations.

• Machine Learning
• Relational Databases
• Quantum Computing
• +۳ مورد دیگر

R. Hai is a researcher active in the fields of Machine Learning , Relational Databases , and Quantum Computing . Their work bridges the integration of large language models (LLMs) with database systems, focusing on optimizing query processing and data management through linear algebraic methods. Hai's research emphasizes seamless data-ML workflows and innovative applications of relational databases in emerging domains. Key Research Themes : LLM compilation to SQL, quantum circuit simulation via RDBMS, and convergence of data integration with ML. Collaborations : Active in international academic networks, with contributions to conferences like SIGMOD and IEEE journals. Scientific Awards: Veni grant AES2022 (2023) Publications demonstrate expertise in overcoming data barriers, enhancing database performance for ML tasks, and simulating quantum computations using relational database management systems.

• Computer Science
• Cybersecurity
• Internet of Things
• +۵ مورد دیگر

Gang Tan is an Associate Professor at the Pennsylvania State University's College of Engineering, Department of Computer Science and Engineering. He also holds the James F. Will Career Development Professorship and is affiliated with the Institute for Computational and Data Sciences (ICDS). His research focuses on binary reverse engineering , cybersecurity , Internet of Things (IoT) security , machine learning fairness , and information flow security . He has led numerous NSF-funded projects, including work on precise binary analysis, IoT policy enforcement, and automated fairness repair in AI systems. Recent work trends include memory safety validation , pseudocode extraction , and control-flow integrity mechanisms. His 127+ research outputs reflect deep engagement with static program analysis , cache side-channel detection , and secure kernel-driver interfaces . Scientific Awards: James F. Will Career Development Professorship Gang Tan has secured multiple grants from the National Science Foundation (NSF) and U.S. Navy for projects like Sliver (information flow verification) and Semantics-Directed Binary Reverse Engineering . His work involves advising teams on IoT safety, and he has 19 active or completed grants since 2008.

Anitha Gollamudiمشاهده پروفایل

استادیار

• Language-based Security
• Trusted Execution Environments
• Formal Methods
• +۴ مورد دیگر

Anitha Gollamudi is an Assistant Professor in the Department of Computer Science at the Miner School of Computer and Information Sciences, University of Massachusetts Lowell. She teaches core courses including Systems Security (COMP 5300), Compiler Construction (COMP 4060/5340), and Organization of Programming Languages (COMP 3010). Her research focuses on language-based security through hardware-assisted mechanisms, cryptography, and formal methods. Current projects include: Automatic compartmentalization of Trusted Execution Environment (TEE) programs Formal foundations of Fully Homomorphic Encryption (FHE) compilers Privacy-preserving machine learning with encrypted learning Analysis of her 8 recent publications (2016-2025) reveals dominant themes in TEE security and secure compilation. Key contributions address memory safety in WebAssembly, authorization logic for computation principals, and formal verification of cryptographic systems. Her work consistently bridges theoretical foundations with practical implementations for real-world security challenges. No scientific awards were mentioned in the available information. Professor Gollamudi actively mentors students across levels, currently advising PhD candidates Wesley B. Nuzzo and Samuel Dodson alongside undergraduate Benjamin Houle. Her former students include Nam Bui, James Chen, Yuka Akiyama (honors thesis), and Andrew Eggleston. She emphasizes collaborative research and encourages prospective students to contact her with research interests and academic background. She leads a research group focused on applying programming language techniques to security problems, with ongoing projects targeting enclave placement optimization, FHE correctness verification, and encrypted machine learning frameworks.