جست‌وجوی استاد و پژوهشگر

Shiyi Weiمشاهده پروفایل

دانشیار

• Software Engineering
• Security
• Programming Languages
• +۳ مورد دیگر

Shiyi Wei is an Associate Professor in the Department of Computer Science at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a Ph.D. in Computer Science from Virginia Tech (2015) and a B.E. in Software Engineering from Shanghai Jiao Tong University (2009). His postdoctoral research was conducted at the University of Maryland, College Park's PLUM Lab. His research focuses on enhancing software security and reliability through automated analysis, testing, and static/dynamic tool development. Key areas include configurable systems analysis, machine learning-driven static analysis, and fuzz testing benchmarking. Wei has received prestigious awards, including the NSF CAREER Award (2021) and a USENIX Security Distinguished Paper Award (2022). He teaches courses such as Compiler Construction (CS 6353), Compiler Design (CS 4386), and Software Maintenance and Evolution (CS/SE 6356). Current research projects involve improving fuzz testing methodologies, AI-driven vulnerability修复, and evaluating static analysis tools. His group has developed frameworks like ECSTATIC for configurable tool testing and FIXREVERTER for realistic bug injection. Wei has advised numerous students, including Austin Mordahl (Assistant Professor at UIC) and Zenong Zhang (Software Engineer at Google). His work is supported by NSF grants and AWS research credits. Notable recent contributions include studies on nondeterministic static analysis tools and feature-based fuzz testing benchmarking.

Zhoulai Fuمشاهده پروفایل

دانشیار

• Programming Language Theory and Implementation
• Program Analysis
• Testing and Verification
• +۵ مورد دیگر

Zhoulai Fu is a tenured Associate Professor at the State University of New York (SUNY), Korea, specializing in programming languages and software security. He also holds joint appointments as a Research Associate Professor at Stony Brook University and is affiliated with the Electrical and Computer Engineering Department at Virginia Tech. His educational background includes: Ph.D., 2009-2013, INRIA – Université de Rennes 1, France M.Eng., 2008-2009, Télécom ParisTech, France M.S, B.S, and French engineer degrees (Ingénieur), 2005-2008, École Polytechnique, France Professor Fu's research focuses on the intersection of Programming Languages, Software Security, and Large Language Models, with special emphasis on improving software reliability through formal methods, numerical error analysis, and scalable verification techniques . His work spans abstract interpretation, automated testing, and verification tools development. He has made significant contributions to floating-point analysis and program verification, with publications at top-tier conferences including PLDI, POPL, OOPSLA, ICSE, and CAV. His publication record shows a consistent trajectory in programming language theory with increasing practical applications. Early work focused on foundational aspects of abstract interpretation and floating-point analysis, while recent papers address security concerns through programming language techniques and incorporate modern approaches like incorrectness logic. Key themes across his publications include formal verification of low-level code, numerical error analysis, and developing scalable analysis tools for real-world software systems. His notable achievements include: Principal Investigator for DARPA E-BOSS Program funding Sole Principal Investigator for National Research Foundation of Korea funding Program Committee membership for POPL 2026, FSE 2024, and PLDI 2023 Professor Fu actively mentors students and has taught courses including Foundations of Computer Science, Programming Abstractions, and Research in Computer Science. His research is supported by significant grants from DARPA and NRF, enabling him to lead the Data & Intelligent Computing Lab at SUNY Korea. He is currently seeking postdocs, PhD, and graduate students to join his research team. He leads the Data & Intelligent Computing Lab, which focuses on advancing programming language techniques for software reliability and security. The lab collaborates with institutions including Virginia Tech, Stony Brook University, and international partners across Europe, working on projects that bridge theoretical computer science with practical software engineering challenges.

Abid M. Malikمشاهده پروفایل

دانشیار

• High-performance computing
• Parallel programming models
• Compiler optimizations
• +۴ مورد دیگر

Abid M. Malik is an Associate Professor in the Department of Computer Science at Stony Brook University, joining in September 2023. His research focuses on high-performance computing, parallel programming models, and compiler optimizations targeting LLVM and MLIR frameworks. Prior roles include positions at Brookhaven National Laboratory, the University of Houston, Rice University, INRIA (France), and IBM's Center for Advanced Studies in Toronto. Education: PhD from the University of Waterloo, Canada. Research interests span compiler technology, parallel programming languages, and constraint programming. He has over 15 years of academic and industry experience, combining theoretical and applied work in computing systems. Teaching responsibilities include courses such as CSE 220, CSE 307, CSE/ISE 337, CSE 416, and CSE 304. No specific scientific awards or grants are listed in the provided text.

Christopher Dutchynمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Aspect-Oriented Programming
• +۶ مورد دیگر

Christopher Dutchyn is an Associate Professor in the Department of Computer Science at the University of Saskatchewan . He holds a Ph.D. and M.Sc. in Computer Science from the University of British Columbia and University of Alberta respectively, and a B.Sc. (honours) in Mathematics. His research spans programming language design and implementation , type theory , category theory , game semantics , and aspect-oriented programming . He has contributed to semantics for dynamic join points, continuation-based models, and multi-dispatch optimization in JVM. His recent publications focus on Aspect-Oriented Programming Programming Language Semantics Compiler Design Modularity in Software Category Theory Applications Multi-Dispatch Systems with citations in ACM, Elsevier, Springer, and Usenix. Scientific awards include Best Student Paper at COOTS 2001 for his work on multi-dispatch performance optimization. Dutchyn has developed open-source tools like AspectScheme and SLaTeX mode for Emacs , and maintains collaborations in programming language theory and software engineering principles.

Martin Schoeberlمشاهده پروفایل

استاد

• Real-Time Systems
• Embedded Systems
• Multicore Processing
• +۳ مورد دیگر

Professor Martin Schoeberl is affiliated with the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on real-time systems, worst-case execution time analysis, and embedded systems engineering. He is actively involved in projects such as Rigoletto, aiming to develop high-performance automotive processors using RISC-V architecture. Research Interests: Schoeberl's work spans time-predictable processors, network-on-chip architectures, and hardware-software co-design for cyber-physical systems. He explores methodologies to ensure deterministic behavior in multicore environments and develops tools for WCET analysis. His contributions include advancements in compiler optimizations for neural networks and temporal semantics in embedded systems. Advising & Grants: Schoeberl supervises PhD students such as E. Khodadad (on rigorous design of time-predictable systems) and A. Cerioli (on compiler optimizations for neural networks). He leads or participates in funded projects including Rigoletto (2025-2028) and Multi-Core Architecture for L1 Deterministic Processing (2022-2025). These projects aim to enhance real-time capabilities in embedded systems and automotive computing platforms. Labs & Teams: As part of the Embedded Systems Engineering group at DTU, Schoeberl collaborates on hardware generators using Chisel and designs reactor-oriented architectures for cyber-physical systems. His work integrates reconfigurable logic and synchronous models to create efficient, time-predictable solutions.

• Programming Languages
• Concurrency
• Embedded Systems
• +۴ مورد دیگر

Dr. Emil Sekerinski is a Professor in the Department of Computing and Software at McMaster University. He holds the position of Undergraduate Advisor for Computer Science (Jan 1, 2025 – June 30, 2025). His expertise spans programming logic (verification, refinement), concurrency (components, implementation), embedded systems (modelling, analysis), and programming languages (run-time, compilation). He is actively involved in research clusters focused on Digital & Smart Systems. His research interests emphasize formal methods in computer science, concurrency theory, parallel algorithms, and embedded systems design. He has contributed to advancing methodologies for software quality assurance and system reliability through formal specifications and automated verification techniques. Recent work includes efficient synchronization mechanisms for object-oriented programming languages and formal development of delay-tolerant multicast protocols for wireless sensors. Dr. Sekerinski has organized and participated in major conferences such as FMTea'24 (Co-Chair) and ICTAC'24 (Program Committee). His teaching includes advanced courses like CAS 781 Advanced Topics: Advanced Compiler Design and Optimization and SFWR ENG 3BB4 Concurrent System Design . He maintains an active presence in academic outreach through LinkedIn, Instagram, and other platforms. His work bridges theoretical foundations with practical applications, including environmental sensor data analysis and holistic embedded system development. Despite no explicit mention of awards, his contributions to formal methods education and research are widely recognized in his field.

John Williamsمشاهده پروفایل

دانشیار

• Reconfigurable Computing
• Real-Time Embedded Systems
• 3D Computer Vision
• +۳ مورد دیگر

Associate Professor John Williams holds dual roles as Deputy Director of Cyber Security and faculty member at the School of Electrical Engineering and Computer Science, University of Queensland. His academic journey includes a PhD (2001) and undergraduate degrees (1995) in Electronic Engineering and Information Technology from Queensland University of Technology (QUT). Research Focus: Reconfigurable computing architectures Real-time embedded systems 3D computer vision and imaging Cyber security solutions Key Contributions: Edited the 2004 IEEE International Conference on Field Programmable Technology proceedings Developed the Egret platform for reconfigurable systems-on-chip Published 5 journal articles and over 20 conference papers Professional Affiliations: Member of IEEE for over 20 years, contributing to standards and interdisciplinary cyber security initiatives at UQ.

Roy Hermannsمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Quantum Compilation
• Quantum Processor Architecture
• +۳ مورد دیگر

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.

• Dependent Types
• Programming Languages
• Functional Programming
• +۵ مورد دیگر

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.

• Partial Differential Equations
• Harmonic Analysis
• Fractional Calculus
• +۴ مورد دیگر

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.

• Teaching Chinese as a Second Language
• Language Teaching Materials Development
• Online Language Education
• +۲ مورد دیگر

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.

Volkmar Siehمشاهده پروفایل

پژوهشگر

• Distributed Systems
• Real-Time Systems
• Fault Tolerance
• +۴ مورد دیگر

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 Klausمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Distributed Systems
• Operating Systems
• +۳ مورد دیگر

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. Cooperمشاهده پروفایل

استاد

• Compiler Construction
• Program Analysis and Optimization
• Parallel Computing
• +۵ مورد دیگر

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.

• Computer Science Education
• Virtualization
• Embedded Runtime Systems
• +۳ مورد دیگر

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.