جست‌وجوی استاد و پژوهشگر

Bo Wangمشاهده پروفایل

استادیار

• Compiler Testing and Tuning
• Mutation Analysis
• Automated Program Repair
• +۳ مورد دیگر

Bo Wang is an Assistant Professor in the School of Computer Science and Technology at Beijing Jiaotong University (BJTU), where he serves as a Master's Supervisor. He received his PhD in Computer Science from Peking University in 2021, with prior educational background from University of Science and Technology of China (Master) and Central South University (Bachelor). His academic journey includes significant international experience, having been a visiting Ph.D. student at the National University of Singapore in 2019 under the supervision of Prof. Abhik Roychoudhury, and a visiting scholar at Singapore Management University in 2024. These experiences have contributed to his global perspective on software engineering research. Dr. Wang's research spans four primary areas of software engineering: Compiler Testing and Tuning - Focusing on identifying bugs in C++ compilers through innovative fuzzing techniques and type-driven mutation Mutation Analysis - Developing efficient approaches to mutation testing that reduce computational overhead while maintaining effectiveness Automated Program Repair - Creating systems that automatically fix software bugs, with emphasis on efficiency and validation techniques AI for Software Engineering - Exploring how large language models can enhance various software engineering tasks including fault localization and test generation His publication record demonstrates a consistent focus on practical software engineering problems with significant technical depth. Recent work shows an increasing integration of AI/ML techniques with traditional software engineering approaches, particularly in evaluating how large language models can contribute to automated program repair and fault localization. His research often targets efficiency improvements, seeking to make advanced software engineering techniques more practical for real-world application. Dr. Wang has been recognized with prestigious awards including the ACM SIGSOFT Distinguished Paper Award for his ISSTA 2017 work on mutation analysis and the IEEE TCSE Distinguished Paper Award for his ICSME 2025 paper on automated program repair. As an active member of the software engineering community, Dr. Wang serves on program committees for major conferences including ASE, FSE, and ICSE. He has advised multiple Master's students at Beijing Jiaotong University, guiding research in software testing, program analysis, and automated repair techniques. His work has been supported by academic grants that enable his research group to pursue innovative approaches to challenging software engineering problems. Dr. Wang maintains an active research group focused on software testing and analysis, with projects spanning compiler testing, mutation analysis, automated program repair, and AI applications in software engineering. His lab employs both traditional program analysis techniques and cutting-edge AI approaches to address longstanding challenges in software reliability and maintenance.

Yanyan Jiangمشاهده پروفایل

دانشیار

• Software Engineering
• Software Testing
• Software Verification
• +۲ مورد دیگر

Dr. Yanyan Jiang is an Associate Professor at Nanjing University, China, specializing in software systems with a focus on validation, verification, and synthesis. His research spans software testing, analysis, and program synthesis, with significant contributions to the field of software engineering. Dr. Jiang's research interests include: Software Testing - particularly code coverage validation and Android application testing Software Verification - with focus on compiler validation and system correctness Program Synthesis - especially for dynamic software updates and state transformation Operating Systems - including educational approaches and system design principles His recent work shows a strong trend toward practical applications of software engineering research, with focus on Android systems, compiler validation, and self-adaptive software. His publications demonstrate expertise in both theoretical approaches to software validation and practical tools for real-world systems, particularly in the areas of code coverage validation, dynamic software updating, and compiler verification. Dr. Jiang has received numerous prestigious awards: SOSP'23 Best Paper Award ACM SIGSOFT Distinguished Paper Awards (ICSE'21 and ASE'18) ACM Europe Council Best Paper Award Microsoft Research Asia Fellowship Award CCF Outstanding Doctoral Dissertation Award Dr. Jiang actively contributes to the software engineering community through program committee memberships at major conferences including ASE, ICSE, and ESEC/FSE. He also serves on the Steering Committee for regional Computing Olympiad contests and as a Technical Committee member for the Asia-Pacific Informatics Olympiad (APIO) 2022-2024, demonstrating his commitment to both research excellence and educational outreach in computer science.

Yijun Yuمشاهده پروفایل

استاد

• Requirements Engineering
• Automated Software Engineering
• Software Maintenance and Evolution
• +۳ مورد دیگر

Yijun Yu is a Professor of Software Engineering at The Open University, UK, where he leads research on automated techniques to enhance software engineering productivity and software quality. He serves as Associate Editor for the Software Quality Journal and Chair of the BCS Specialist Group on Requirements Engineering, while actively contributing to program committees of premier conferences including ICSE, FSE, RE, ICSME, and SEAMS. His research spans Requirements Engineering, Automated Software Engineering, and Software Maintenance and Evolution, with emphasis on developing methods for software adaptation, security enhancement, and resilience engineering. Key contributions include techniques for requirements-driven adaptation, Rust-based safety mechanisms, and socio-technical resilience frameworks that bridge theoretical advances with practical industry applications. Analysis of his 2018-2024 publications reveals a strong trajectory in programming language safety (particularly Rust transpilation), neural code representation learning, and adaptive security systems. His work consistently addresses real-world challenges in memory safety, vulnerability prediction, and autonomous system behavior through innovative static analysis, machine learning, and formal methods approaches. His scientific achievements include: 10 Year Most Influential Paper award (CASCON’16) 6 Best Paper awards (SEAMS’18, iRENIC’16, TrustCom’14, EICS’13, VMPDP’01) 3 Distinguished Paper awards (RE’11, BCS’08, ASE’07) Best Tool Demo Paper Award (RE’13) Best Student Paper Award (PDCS’02) As Principal Investigator, Professor Yu has managed knowledge transfer projects with industry leaders: NATS (air traffic management) Huawei (telecommunications) IBM (enterprise software) CA Technologies (IT management) RealTelekom (network solutions) These collaborations focus on translating academic research into practical solutions for requirements engineering, adaptation techniques, and security challenges in industrial software systems.

Arie van Deursenمشاهده پروفایل

استاد

• software testing
• software architecture
• human aspects of software engineering
• +۳ مورد دیگر

Arie van Deursen is a Professor in software engineering at Delft University of Technology where he heads the Department of Software Technology. He serves as chair of the ICSE steering committee and is an elected member of the Netherlands Academy of Engineering (NAE). His work extends beyond academia as he serves on the Advisory Council of IT Assessment (AcICT) for the Dutch government and the advisory council of ING Bank Netherlands. Van Deursen's research spans software testing, software architecture, human aspects of software engineering, foundation models, and software engineering applications in financial and public sectors. His work increasingly focuses on the intersection of AI and software engineering, particularly examining how large language models impact development practices, code quality, and developer productivity. He also investigates sustainable computing practices, particularly energy efficiency in machine learning systems. His recent publications reveal a strong trend toward examining the practical applications and limitations of foundation models in software development, with particular attention to code quality, reliability, and ethical considerations. The research spans multiple subfields including code completion systems, large language model evaluation, concept drift monitoring, and sustainable AI practices. His scientific recognition includes: Elected member of the Netherlands Academy of Engineering (NAE) Van Deursen actively mentors students and early-career researchers, having previously mentored PhD students like Ali Mesbah (now professor at UBC). He has secured significant research funding through strategic collaborations with industry partners including ING, DSM, and Booking.com, which led to the establishment of industry-funded labs. His department has grown substantially, with faculty increasing from 54 to 72 members between 2015-2020. He leads research initiatives within TU Delft's computer science organization, which operates across five main themes: decision support, data management and analytics, software systems engineering, networked and distributed systems, and security and privacy. His department has established strategic collaborations with major organizations including Erasmus Medical Center and Leiden University Medical Center.

Liliana Pasqualeمشاهده پروفایل

دانشیار

• Requirements Engineering
• Self-Adaptive Systems
• Security
• +۵ مورد دیگر

Liliana Pasquale is an Associate Professor at University College Dublin's School of Computer Science and a funded investigator at Lero - the Irish Software Research Centre. She also serves as the Director of the UCD MSc in Cybersecurity program, demonstrating her leadership in both academic and research domains. Her educational background isn't explicitly detailed in the provided text, but her extensive publication record and academic positions indicate strong academic foundations in computer science and software engineering. Pasquale's research focuses on requirements engineering, self-adaptive systems, security, and digital forensics, with particular emphasis on using runtime models to engineer complex cyber-physical systems that satisfy security requirements while remaining forensic-ready and compliant with data protection regulations. Her work bridges theoretical software engineering with practical security applications across various domains including smart homes, industrial control systems, and transportation networks. Analyzing her recent publications reveals a consistent focus on adaptive security mechanisms, forensic readiness for cyber-physical systems, and GDPR compliance through software engineering approaches. Her research shows a progression from foundational work in adaptive security to more specialized applications in specific domains like industrial control systems and ransomware detection. Lero Research Award (2024) Best Paper Award at SEAMS 2014 for 'User-centric Adaptation of Multi-tenant Services: Preference-based Analysis for Service Reconfiguration' Best Student Paper Award at ICWS 2009 Pasquale actively advises PhD students on topics spanning secure software engineering, forensic-ready systems, and adaptive security. Her current supervision includes research on securing AI-based coding assistants, engineering adaptive authentication, ransomware detection, sustainable adaptive security, and cyber information sharing. She has successfully guided multiple PhD students to completion, with graduates now working as R&D engineers, post-doctoral researchers, and assistant professors. Beyond direct student supervision, she serves on numerous program committees for major software engineering conferences including ICSE, ASE, and SEAMS, demonstrating her significant contribution to the academic community. She is part of the SPARE research group at University College Dublin, which focuses on security and privacy aspects of adaptive and reliable software engineering. Her work often involves collaboration with researchers across Europe and internationally, particularly with Prof. Bashar Nuseibeh and other members of the Lero research center.

Aldeida Aletiمشاهده پروفایل

دانشیار

• Search-Based Software Engineering
• Software Testing
• Program Repair
• +۲ مورد دیگر

Aldeida Aleti serves as Associate Professor and Associate Dean of Engagement and Impact at Monash University's Faculty of Information Technology. Her academic profile combines leadership responsibilities with cutting-edge research in software engineering methodologies. Her primary research interests include: Search-Based Software Engineering (SBSE) Software Testing and Quality Assurance Program Repair and Maintenance Software Architecture and Design Optimization Techniques for Engineering Problems Dr. Aleti's research program investigates why certain software engineering problems are difficult to optimize and develops practical approaches for applying search-based techniques to new domains. Her work bridges theoretical optimization methods with real-world software engineering challenges, focusing on making SBSE more accessible and effective. Her publication record shows a consistent trajectory of impactful research, with recent work exploring intersections between large language models and software engineering tasks, autonomous vehicle testing, fairness in AI systems, and program repair. These publications demonstrate increasing sophistication in addressing complex software engineering challenges through optimization techniques. Dr. Aleti's scientific recognition includes: Australian Research Council's Discovery Early Career Researcher Award (DECRA) Over $2.5 million in competitive research funding Editorial board membership for Journal of Systems and Software and Empirical Software Engineering Active service on program committees for major conferences including ASE, ICSE, and ISSTA As Associate Dean of Engagement and Impact, she drives initiatives connecting academic research with industry applications and societal benefits. Her leadership extends to mentoring emerging researchers through the New Faculty Symposium and Doctoral Symposium committees at major conferences.

Qi Xinمشاهده پروفایل

دانشیار

• Software Engineering
• Automated Program Repair
• Software Debugging
• +۴ مورد دیگر

Qi Xin is an Associate Professor at the School of Computer Science, Wuhan University. He is a member of the Centre of Software Testing, Analysis and Reliability (CSTAR) and serves on program committees for major software engineering conferences including ASE, ISSTA, and ICSE. Dr. Xin received his Ph.D. from Brown University under the supervision of Dr. Steven Reiss and was previously a Postdoctoral Researcher at Georgia Institute of Technology working with Dr. Alex Orso. His research focuses on software engineering, particularly on developing automated and semi-automated approaches to improve software development processes and enhance software quality, security, and reliability. His recent work centers on automated program repair, software debugging, and program debloating. Dr. Xin has published extensively in top-tier software engineering venues, with research that frequently addresses practical challenges in real-world software systems. Dr. Xin's publication record shows a consistent focus on improving software reliability through automated techniques. His work spans from foundational program analysis to practical tool development, with several publications focusing on Android applications and addressing challenges specific to mobile software development. His recent work has begun exploring the application of large language models to software engineering problems, as evidenced by his 2025 paper on conversational LLM-based repair. ACM SIGSOFT Distinguished Paper Award for fault localization research Guest editor for Automated Software Engineering (AUSE) Special Issue Reviewer for ACM TOSEM, IEEE TSE, and EMSE journals Dr. Xin actively mentors students and serves the academic community through conference organization and journal reviewing. He teaches courses including Compiler Design and Software Testing and Practice at Wuhan University, bridging his research expertise with classroom instruction to train the next generation of software engineers.

Wensheng Douمشاهده پروفایل

پژوهشگر

• software analysis and testing
• distributed systems
• database systems
• +۱ مورد دیگر

Wensheng Dou is a Researcher at the Institute of Software, Chinese Academy of Sciences . His work bridges software engineering, distributed systems, and database technologies, with a strong emphasis on improving system reliability through advanced testing methodologies. Research Focus: Dou's interests span: Software Testing & Analysis : Differential testing, fault injection, and bug detection in databases and distributed systems. Systems Reliability : Cloud systems, graph databases (Gremlin/RDF), and transaction processing. Emerging Platforms : IoT, mobile apps (WeChat), and LLM-assisted bug fixing. Publication Trends: His recent work (2022–2025) demonstrates a consistent focus on: Automated testing tools for databases (e.g., FaultFuzz ) and distributed systems. Bug characterization in real-world systems (cloud, IoT, mini-apps). Innovations in differential testing and coverage-guided fault injection.

Fiorella Zampettiمشاهده پروفایل

پژوهشگر

• Experimental Software Engineering
• Continuous Integration and Delivery
• Static Analysis Tools
• +۴ مورد دیگر

Fiorella Zampetti is a researcher at the University of Sannio, Italy, specializing in empirical software engineering with a focus on continuous integration and delivery, static analysis tools, mining software repositories, and software maintenance and evolution. Her work bridges theoretical research with practical applications in real-world software development environments. Her research interests span multiple critical areas of modern software engineering, with particular emphasis on Experimental methodologies for evaluating software engineering practices Technical debt identification and management, especially in emerging domains like deep learning systems Continuous integration and delivery pipelines, including common anti-patterns and solutions Mining software repositories to extract valuable insights about development processes Software quality assessment through static analysis and empirical studies Analysis of her recent publications reveals an evolving research trajectory that has increasingly incorporated artificial intelligence and large language models into traditional software engineering concerns. Her 2023-2025 work shows a significant focus on how AI-generated code impacts software development practices, licensing concerns, and educational contexts. She has also maintained a strong thread of research on technical debt, particularly examining self-admitted technical debt across different software domains. Dr. Zampetti has been actively involved in the software engineering research community as a program committee member for major conferences including ASE, ICSE, ESEC/FSE, and ICSME. Her service on these committees demonstrates recognition by her peers as a subject matter expert in her research domains. Her research has practical implications for software development teams looking to improve their CI/CD practices, manage technical debt effectively, and understand the emerging challenges posed by AI-assisted development tools. She has conducted numerous empirical studies that provide evidence-based insights into software engineering practices across both open-source and industrial contexts.

Guowei Yangمشاهده پروفایل

دانشیار

• Software Engineering
• Machine Learning Systems
• Programming Languages
• +۵ مورد دیگر

Guowei Yang is a Senior Lecturer (equivalent to U.S. Associate Professor) at the School of Electrical Engineering and Computer Science, Faculty of Engineering, Architecture and Information Technology, University of Queensland. His research bridges software engineering, machine learning, and programming languages, focusing on enhancing software and ML system reliability/security. Dr. Yang leads projects in symbolic execution, fuzzing techniques, Android app testing, and LLM-based tool development. Research Interests: Core interests include software testing automation, Android ecosystem analysis, ML system robustness, and symbolic execution optimization. His work emphasizes practical tools for API compatibility detection, security patch generation, and fuzzing efficiency. Recent projects leverage large language models for document-guided testing and dynamic vulnerability detection. Professional Service: Dr. Yang actively contributes to top-tier conferences as a program committee member (ICSE, FSE, ASE, ISSTA) and organizer (DSN 2024 Local Chair, TAIC PART Co-Chair). He mentors through Google Summer of Code and NSF Research Experiences for Undergraduates programs, and reviews for journals including IEEE TSE and ACM TOSEM.

Jan Brederekeمشاهده پروفایل

استاد

• Embedded Systems
• Neural Networks
• FPGAs for Space
• +۷ مورد دیگر

Jan Bredereke is a Professor at Bremen University of Applied Sciences (HSB) in the Faculty of Electrical Engineering and Computer Science, where he specializes in Embedded Systems. He leads the Laboratory for Computer Technology and Digital Circuits, focusing on cutting-edge research in hardware and software integration for specialized computing applications. His research spans two major phases: current work on neural networks for space applications and time/space partitioning for avionics, and earlier foundational work on formal requirements specification, mode confusions in user interfaces, and feature interactions in telecommunications systems. Bredereke's research demonstrates a consistent thread of addressing complex system interactions and reliability concerns across different technological domains. His publication record shows significant contributions to both academic literature and practical applications, with recent work focusing on implementing neural networks on resource-constrained platforms for space applications. His earlier work established important frameworks for managing feature interactions in telecommunications systems, which remains relevant to modern software engineering challenges. Bredereke has maintained an active research profile for over two decades, with publications spanning journals, conference proceedings, and books. His work bridges theoretical formal methods with practical engineering concerns, particularly in safety-critical and resource-constrained environments.

• Software Anomaly Detection
• Railway Safety
• Intrusion Detection
• +۴ مورد دیگر

Tommaso Zoppi is a Fixed-term researcher (RTD-A) at the University of Florence, Department of Mathematics and Computer Science 'Ulisse Dini', specializing in computer science with a focus on anomaly detection and cybersecurity for critical systems. He is affiliated with the RCL Group and maintains an active research and teaching schedule within the Computer Science program. Current Position: Fixed-term researcher under Law 240/10 (RTD-A) Department: Mathematics and Computer Science 'Ulisse Dini' Research Group: RCL Group Contact: Room 156, Viale Morgagni 65, Florence, Italy Dr. Zoppi earned his Bachelor's degree in Computer Science from the University of Florence in October 2012, followed by his Master's degree in July 2014. He completed his PhD in Mathematics, Computer Science, Statistics (Computer Science curriculum) from November 2014 to November 2017 under the supervision of Prof. Andrea Bondavalli. His research interests span across multiple critical domains including safety in railway systems, anomaly detection in dynamic and complex cyber-physical systems, intrusion detection based on machine learning approaches, and crisis management support systems. His work bridges theoretical machine learning concepts with practical applications in safety-critical environments where system failures could have severe consequences. Recent publications demonstrate his focus on making machine learning classifiers more reliable and safe for deployment in critical infrastructure. Zoppi's publication record shows a clear trajectory of increasing impact, with numerous papers in IEEE, ACM, and other reputable venues. His recent work (2023-2025) focuses on practical implementations of anomaly detection in real-world systems like power grids, railway infrastructure, and ROS2-based cyber-physical systems. A notable trend is his exploration of how to make machine learning classifiers aware of their own limitations, particularly in safety-critical contexts where knowing when a classifier is uncertain could prevent catastrophic failures. As an educator, Zoppi has served as a tutor for undergraduate Computer Science students since March 2015, helping first-year students organize their studies and facilitating student-professor relationships. He has taught multiple courses including 'Quantitative Analysis of Systems,' 'Computer Architectures,' and 'Data Collection and Machine Learning for Critical Cyber-Physical Systems' across various academic years from 2018-2023. His research is conducted primarily through the RCL Group at the University of Florence, where he collaborates with Andrea Ceccarelli, Andrea Bondavalli, and other researchers on projects related to dependable computing and critical systems. His work often involves practical implementations and testing in real-world scenarios, particularly in railway safety and power grid security applications.

Thabit Thabitمشاهده پروفایل

مدرس

• Accounting
• Financial Accounting
• Auditing
• +۶ مورد دیگر

Thabit Thabit is an academic faculty member specializing in Accounting at Cihan University in Erbil, Iraq. He also holds a position at Ninevah University in the Computer and Information Engineering Department. With an M.Sc. in Accounting and currently pursuing a Ph.D. in Financial Accounting, his academic career spans multiple disciplines including accounting, finance, management, and IT applications. His primary research interests include Financial Accounting, Auditing, IFRS, Oil and Gas Accounting, and the application of fuzzy logic in accounting decision-making. His research portfolio demonstrates expertise in both theoretical accounting frameworks and practical business applications, with numerous publications addressing contemporary challenges in financial reporting, auditing practices, and educational technology. His recent publications (2021-2023) show a strong focus on pandemic-related financial challenges, knowledge sharing in educational institutions, and the intersection of information technology with traditional accounting practices. His work often employs advanced statistical methods including fuzzy logic and structural equation modeling. Thabit has demonstrated interdisciplinary research capabilities, publishing in both accounting/finance journals and engineering/technology publications, reflecting his dual expertise in accounting and information technology.

Timo Kehrerمشاهده پروفایل

استاد

• Software Engineering
• Model-Based Systems
• Cyber-Physical Systems
• +۷ مورد دیگر

Prof. Timo Kehrer is a Professor and Head of the Software Engineering Group (SEG) at the Institute of Computer Science, University of Bern. He also serves as Deputy Director of Studies, overseeing academic programs in software engineering. His research focuses on variability modeling, model-based systems engineering, simulation-based testing of autonomous systems, and empirical studies in software development practices. Key areas include software product lines, cyber-physical systems, and the application of formal methods in industrial contexts. Notable contributions include work on Community-driven variability management in open-source software, Automated testing tools like ScoutSL and TEASER , Simulation-based frameworks for self-driving cars (e.g., Sensodat datasets), and Empirical analyses of GitHub Actions workflows and merge conflict resolution. His research bridges theory and practice, addressing challenges in software sustainability, AI-driven development, and the integration of formal verification tools like TLA+. He actively participates in conferences such as VaMoS (Variability Modelling) and contributes to open-source projects in model-driven engineering. Prof. Kehrer collaborates with industry partners to advance tools for model repositories, vulnerability detection (e.g., VUDENC ), and semantic analysis of software changes. His work emphasizes reproducibility, tool support for developers, and educational initiatives to modernize software engineering curricula.

Volker Stolzمشاهده پروفایل

دانشیار

• Formal Methods
• Model Transformation
• UML
• +۷ مورد دیگر

Volker Stolz is an Associate Professor in the Department of Informatics at the University of Oslo, Faculty of Mathematics and Natural Sciences. He is affiliated with the Reliable Systems research group, where his work centers on improving software reliability through formal methods, model transformation, and UML-based modeling. Institution: University of Oslo School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Research Group: Reliable Systems Contact: stolz@ifi.uio.no | +47 22852438 | Room GA06 9461 His research spans formal verification, concurrency, model-based testing, and programming language semantics. He has made significant contributions to deadlock detection, refactoring equivalence, runtime verification in distributed systems, and data race analysis, often using formal models such as Petri nets and active object languages. The recent publications highlight a consistent focus on software correctness , modular analysis , and automated verification techniques. Trends include the use of behavioral effects, abstract execution, and field calculus for distributed monitoring. His work frequently appears in top-tier venues like Theoretical Computer Science , Lecture Notes in Computer Science , and Journal of Logical and Algebraic Methods in Programming , indicating strong theoretical and practical impact. He collaborates extensively with researchers such as Violet Ka I Pun, Rui Wang, Lars Michael Kristensen, and Martin Steffen, reflecting an active and collaborative research profile. No scientific awards are mentioned in the provided text. There is no information available about student advising or research grants. Volker Stolz is involved in research projects related to model-based testing, formal methods, and reliable software systems, particularly through the Reliable Systems group. His work often involves building theoretical foundations and practical tools for verifying and improving software behavior in distributed and concurrent environments.