جستجوی استاد راهنمای دانشگاهی

Cezara Drăgoiمشاهده پروفایل

پژوهشگر

• Static Analysis
• Formal Verification
• Distributed Systems
• +۳ مورد دیگر

Cezara Drăgoi serves as a Researcher (Chargé de Recherche) at INRIA with dual affiliation at École Normale Supérieure's Department of Computer Science and CNRS. She maintains active roles in major programming language conferences including PLDI, POPL, and SPLASH where she contributes to program committees and steering groups, demonstrating her standing in the formal methods community. Her research program focuses on automated formal verification through abstraction techniques, specifically targeting data structures across the spectrum from sequential implementations to distributed systems. Drăgoi develops logic-based frameworks that enable Hoare-style reasoning about content and consistency properties, with particular expertise in identifying suitable fragments of first-order and separation logic for static analysis. Her work bridges theoretical foundations with practical verification challenges in both single-threaded and concurrent environments. Publication trends reveal a clear evolution from foundational work on shape analysis for sequential data structures toward increasingly complex distributed systems verification. This progression culminated in her development of PSync - a domain-specific language for fault-tolerant distributed algorithms with integrated verification capabilities - demonstrating her ability to create practical abstractions that make verification tractable for real-world systems. Steering Committee Member, Static Analysis Symposium (SAS 2025) Program Committee Co-Chair, VMCAI 2023 Multiple program committee roles at PLDI (2017, 2020), POPL (2016-2023), ECOOP (2019), and SPLASH (2020-2024) Session chair for SAS 2021 and VMCAI 2019 Drăgoi actively mentors emerging researchers through internship and PhD opportunities in specialized areas including Byzantine consensus verification (SABC project) and refinement techniques for fault-tolerant asynchronous code (RFTA project). She has developed two influential verification tools: CELIA (a Frama-C plugin for C program verification handling both data and structural properties) and PSync (a language with verification engine for distributed algorithms). Her teaching includes graduate-level courses on abstract interpretation at Université Paris Diderot. She leads verification research within the INRIA/ENS collaboration, focusing on making static analysis tractable for complex distributed systems through innovative synchronous programming abstractions. Current work targets verification challenges in consensus algorithms and communication-closed protocols, with emphasis on bridging theoretical soundness with practical applicability.

Bradford L. Chamberlainمشاهده پروفایل

استاد مدعو

• Parallel Computing
• Programming Languages
• High-Performance Computing
• +۳ مورد دیگر

Bradford L. Chamberlain is a Distinguished Technologist at Hewlett Packard Enterprise and an Affiliate Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington. With over two decades of experience in high-performance computing, he has made significant contributions to parallel programming languages, particularly as the technical lead of the Chapel programming language project since 2006. His educational background includes: Ph.D. in Computer Science & Engineering from the University of Washington (2001) M.S. in Computer Science & Engineering from the University of Washington (1995) B.S. in Computer Science from Stanford University (1992) Chamberlain's research focuses on improving programmer productivity for high-performance computing through innovative language design, compiler techniques, and runtime systems. His work centers around the Chapel programming language, which aims to provide a multiresolution programming model that allows developers to express parallelism at varying levels of abstraction while maintaining performance across diverse architectures from laptops to supercomputers. His research spans parallel language design, compiler optimization, data distribution strategies, locality management, and performance portability. Chapel builds on his earlier work with the ZPL language, where he developed region-based approaches for sparse parallel computing. His publication record over the past fifteen years demonstrates a consistent focus on practical approaches to parallel programming, with recent work emphasizing data locality, heterogeneous architectures, and performance portability. His articles show an evolution from foundational language design concepts to increasingly sophisticated implementations addressing real-world HPC challenges, particularly in the areas of domain mapping, iterator abstractions, and memory management for large-scale systems. As a Distinguished Technologist at HPE, Chamberlain has played a key role in growing the Chapel project from a modest effort to one involving nearly 20 full-time developers. His leadership has positioned Chapel as one of the most promising languages for addressing the challenge of productive parallel programming at scale. He has secured funding, established collaborations with academia and industry, and performed extensive outreach through talks, tutorials, and research visits. At the University of Washington, Chamberlain serves as a liaison between academia and industry, participating in student committees, teaching graduate courses like Parallel Computation, and fostering communication between the department and HPE/Cray. His teaching experience spans from undergraduate data structures to graduate seminars on parallel programming environments. He has also volunteered as a tutor for underrepresented students in computer science.

Demetris P. Gerogiannisمشاهده پروفایل

پژوهشگر

• Computer Vision
• Image Processing
• Image Segmentation and Registration
• +۷ مورد دیگر

Demetris P. Gerogiannis is a researcher in the Department of Computer Science & Engineering at the University of Ioannina, Greece. His academic work focuses on Computer Vision and Image Processing, with specific expertise in image registration, pointset registration, and feature extraction. He has maintained a consistent publication record from 2007 through 2020, primarily collaborating with Christophoros Nikou and A. Likas. Gerogiannis' research interests span multiple areas within Computer Vision including Image Segmentation and Registration, Pointset Registration, Feature Extraction, Object Detection and Recognition, Pattern Recognition, Automatic Image Annotation, and Machine Learning applications. His work demonstrates a consistent focus on developing robust algorithms for geometric problems in vision, with particular attention to handling noise and outliers in visual data. He has made significant contributions to point set registration, shape representation, and vanishing point detection. His publication history reveals a strong trend toward developing mathematically rigorous approaches to Computer Vision problems, particularly utilizing statistical models like Student's t-distributions for robust registration. His work bridges theoretical computer vision with practical applications, including consumer-facing technologies like QR code systems. The 15 most recent publications show progression from foundational work in image registration to more applied research in texture analysis, word spotting, and biomedical applications. Gerogiannis is also an active entrepreneur, currently coordinating QReca!, a startup focused on consumer engagement through QR codes and NFC technology. He has previously worked on a Video On Demand startup and is developing a spin-off to commercialize his Computer Vision research through an API framework. He maintains a commitment to open academic knowledge by providing Matlab code for non-commercial use related to his publications. He has volunteered for the Athens 2004 Olympic Games and maintains a passion for Mathematics, particularly Number Theory and Euclidean Geometry. His academic profile suggests a researcher who bridges theoretical computer vision with practical applications and entrepreneurial ventures.

Bernhard Scholzمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Static Analysis
• +۴ مورد دیگر

Bernhard Scholz is a Professor at the University of Sydney's School of Computer Science. His research focuses on programming languages, compilers, static analysis, and blockchain technologies, with significant contributions to Datalog optimization and smart contract security. He teaches COMP3109 Programming Languages and Paradigms and leads research in declarative programming frameworks. Scholz's primary research interests include: Development of Soufflé, a Datalog-based program analysis framework Ethereum smart contract security through tools like Ethainter and MadMax Parallel data structures for efficient Datalog evaluation Compiler optimizations for embedded systems and cloud environments His recent publications demonstrate a consistent focus on improving the efficiency and security of declarative programming systems, particularly through innovations in Datalog execution and smart contract analysis. This work bridges theoretical computer science with practical applications in blockchain and distributed systems. Scholz has secured research funding including an ARC Discovery Project on adaptive key-value stores and a Fantom Operations grant for smart contract toolchain development. He collaborates with international researchers on parallel computing and blockchain verification projects.

Mira Meziniمشاهده پروفایل

استاد

• Software development paradigms and tools
• Programming systems for reliable distributed software
• Automated software analysis
• +۳ مورد دیگر

Mira Mezini is a Professor of Computer Science at the Technical University of Darmstadt, Germany, leading the Software Technology Lab. She serves on steering committees, program committees, and editorial boards of top-tier conferences and journals. Her affiliations include the National Research Center for Applied Cybersecurity ATHENE and co-directorship of hessian.AI, the Hessian Center for Artificial Intelligence. Her research focuses on programming systems for reliable distributed software and AI, automated software analysis, and foundational code models. She has developed large-scale module concepts for adaptability, extensible programming languages, and intelligent software development environments that leverage web-based resources to generate programming rules and patterns. Specializes in software engineering Expert in programming language design Contribution to cybersecurity and AI Her recent work emphasizes static analysis, distributed systems, and programming language design, with trends in API misuse detection, decentralized applications, and secure local-first programming. The focus spans from foundational type systems to practical tools enhancing software quality and developer productivity. Scientific Awards Two-time IBM Eclipse Innovation Award recipient (2005, 2006) Google Research Award (2017) Horst Görtz IT Security Award (2014) ERC Advanced Grant (2012) ACM Fellow Dahl-Nygaard Prize (2025) She has held leadership roles including Dean of Computer Science at TU Darmstadt (2013-2014) and Vice President positions (2014-2019). Her service extends to international juries, funding panels, and editorial boards. Labs & Teams Leads the Software Technology Lab at TU Darmstadt, driving research in programming paradigms and tools. Co-directs hessian.AI and contributes to the Excellence Cluster 'Reasonable Artificial Intelligence.'

Panagiotis Nastouمشاهده پروفایل

استادیار

• Secure Discrete Systems Modeling
• Graph Theory
• Cryptography
• +۵ مورد دیگر

Panagiotis Nastou is an Assistant Professor at the Department of Mathematics , University of the Aegean , with research interests in Secure Discrete Systems Modeling, Graph Theory, Cryptography, Design and Analysis of Algorithms , and Complexity Theory . He has been active in teaching courses such as Discrete Mathematics and Cryptography since 2007 and serves as Director of the Applied Mathematics and Mathematical Modeling Laboratory since 2019. Education : Ph.D., MSc., and BSc. in Computer Engineering and Informatics from Patras University. Membership : Center for Applied Optimization (University of Florida), GDPR TEAM, IEEE, ACM, and Hellenic Technical Chamber. His research bridges theoretical computer science and applied security, focusing on cryptographic protocols, algorithm design, and the application of discrete mathematics to real-world problems. He has contributed to the development of secure systems for critical infrastructure and privacy-preserving frameworks in smart cities. Recent publications (2021-2025) emphasize malware evasion , quantum cryptanalysis , and privacy in IoT environments , utilizing formal methods and combinatorial structures. His work also extends to deep learning for document analysis and consensus algorithms in social networks . He has supervised numerous Master's and undergraduate theses in areas like Zero-Knowledge Proofs , Neural Networks , and Cryptographic Boolean Functions . Administrative roles include representation in the ERASMUS+ program and participation in EU-funded project evaluations.

Kunle Olukotunمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Programming
• Chip Multiprocessors
• +۴ مورد دیگر

Kunle Olukotun is a Professor of Electrical Engineering and Computer Science at Stanford University's School of Engineering, where he has been faculty since 1991. He directs the Stanford Pervasive Parallelism Lab (PPL) and co-leads the Transactional Coherence and Consistency (TCC) project. His research focuses on computer architecture, parallel programming environments, and scalable parallel systems. Key areas include chip multiprocessors (CMPs), transactional memory systems, domain-specific languages (DSLs) for heterogeneous computing, and hardware-software co-design for machine learning workloads. His work bridges theoretical foundations with practical systems implementation. Notable contributions include the Stanford Hydra research project (one of the first chip multiprocessors with thread-level speculation), founding Afara Websystems (acquired by Sun Microsystems), and developing the Niagara processor architecture. His DSL frameworks like Green-Marl and Spatial enable efficient graph analysis and hardware acceleration. His publications reveal strong trends in parallel systems evolution: from foundational CMP research (2000s) to transactional memory (2004-2010), then DSLs for heterogeneous computing (2010-2015), and currently foundation model systems (2023-2025). Subfield analysis shows consistent focus on hardware-software co-design, sparse computation, and compiler techniques across decades. ACM Fellow (2006) for contributions to multiprocessors on a chip and multi-threaded processor design Best Paper Award at IEEE International Symposium on Workload Characteristics (IISWC '10) for EigenBench Olukotun actively mentors researchers through the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate parallelism across application domains. His projects have secured significant industry partnerships, including the acquisition of his startup Afara Websystems by Sun Microsystems. Current research focuses on compiler frameworks for foundation model systems and hardware acceleration for sparse machine learning workloads, supported by collaborations with major tech companies. He leads the Stanford Pervasive Parallelism Lab (PPL), which develops compiler and runtime systems for heterogeneous architectures. The lab's work spans DSLs, hardware acceleration, and parallel programming models, with strong industry ties to companies like NVIDIA and Google. Current initiatives include the Mosaic compiler framework and Stardust architecture for sparse tensor computation.