جستجوی استاد راهنمای دانشگاهی

Dr. Araz Jabbari serves as an Associate Professor in the Department of Organizational Information Systems at Laval University's Faculty of Business Administration. His research examines how individuals and organizations engage with digital technologies and navigate digital transformation, with particular focus on conceptual modeling practices in increasingly complex digital environments. Dr. Jabbari maintains an active research agenda that bridges theoretical frameworks with practical applications, contributing significantly to information systems scholarship through publications in top-tier journals and conferences. Dr. Jabbari's academic foundation includes: Ph.D. in Information Systems from Queensland University of Technology MBA in IT Management from Multimedia University B.Sc. in Mathematics from University of Urmia Dr. Jabbari's research centers on conceptual modeling in the digital era, investigating how traditional modeling approaches must evolve to address contemporary challenges. His work explores how individuals understand and use multiple conceptual modeling scripts, ontological overlap in combined models, and the transition from representation to mediation in digital environments. Recent research increasingly addresses AI-specific challenges, including information quality frameworks for AI systems and the faithfulness of machine learning training data. His scholarship examines digital transformation from both technical and organizational perspectives, with growing emphasis on how data, intelligence, and transparency reshape coordination practices. Dr. Jabbari's publication trajectory demonstrates progression from foundational conceptual modeling research to cutting-edge investigations at the intersection of information systems, organizational theory, and artificial intelligence. His work shows increasing engagement with interdisciplinary topics, particularly how digital systems fundamentally reshape organizational practice. The research evolution reflects the field's broader shift from viewing information systems as representations to understanding their mediating role in digital ecosystems. Dr. Jabbari's scholarly impact is evident through: Publications in premier journals including MIS Quarterly, Journal of the Association for Information Systems, and Decision Support Systems Presentations at leading conferences such as HICSS and AMCIS Development of influential frameworks like 'Modeling 4.0' that reshape conceptual modeling discourse 297 citations across 29 publications indicating research influence As an educator, Dr. Jabbari teaches system analysis and design, business analysis, and digitization courses that likely integrate his research expertise. His student supervision approach probably emphasizes both theoretical rigor and practical application, preparing students to address real-world digital transformation challenges. His collaborative research style, evident in numerous international co-authorships, suggests opportunities for students to engage with a global research network. The Department of Organizational Information Systems at Laval University provides a rich academic environment where Dr. Jabbari contributes to shaping how future information systems professionals understand and design digital solutions for complex organizational challenges.

• Information Systems
• Conceptual Modeling
• Digital Transformation
• +۴ مورد دیگر

Elvira Patricia Pino Blanco is a Professor in the Department of Computer Science at the Barcelona East School of Engineering, Polytechnic University of Catalonia (UPC). She is a member of the ALBCOM research group (Algorithms, Bioinformatics, Complexity and Formal Methods) and has an extensive publication record spanning over two decades. Her research interests focus on formal methods in computer science, particularly in graph theory, logic programming, and database systems. She has made significant contributions to navigational logics for graphical structures, graph databases, and model synchronization using triple graph grammars. Her work bridges theoretical foundations with practical applications in software engineering and data management. Her publication trends show a consistent focus on graph-based approaches to computational problems, with recent work emphasizing logical approaches to graph databases and navigational query languages. She has published in high-impact venues including Journal of Logical and Algebraic Methods in Programming, Theoretical Computer Science, and various international conferences. Professor Pino Blanco has been involved in numerous competitive R&D projects related to algorithmics, bioinformatics, and formal methods. Her work demonstrates interdisciplinary connections between theoretical computer science and practical applications in data management and software engineering. She is affiliated with the ALBCOM research group which focuses on algorithmics, bioinformatics, complexity theory, and formal methods. This group represents a vibrant research community working at the intersection of theoretical computer science and practical applications.

• Computer Science
• Formal Methods
• Logic Programming
• +۵ مورد دیگر

Надежда Василева Славова is a Senior Lecturer at the Technical University - Gabrovo, Bulgaria, working in the Department of Language and Specialized Training. With over 15 years of academic experience, she focuses on language education, particularly English for specific purposes including Technical English, Business English, and language training for engineering students. Her work bridges language teaching methodologies with modern educational technologies. Dr. Slavova's research interests span specialized language education for technical and business contexts, with particular emphasis on developing effective teaching methodologies for adult learners. She explores the intersection of language learning with cognitive processes, translation theory, and educational technology applications. Her work addresses practical challenges in language acquisition for professional settings. Her publication record shows a strong focus on practical language teaching applications. Recent works emphasize digital platforms like Moodle for language instruction, visualization techniques in translation, and effectiveness of different teaching approaches. She has researched the use of proverbs in language learning and challenges of foreign language acquisition, particularly for adult learners in technical fields. Dr. Slavova has been actively involved in numerous research projects, including international collaborations through ERASMUS+ programs. Her project work focuses on active learning communities, upskilling technicians and engineers, and developing modern educational technologies for language instruction across multiple European countries.

• Language Education
• Technical English
• Business English
• +۵ مورد دیگر

Jihyeok Park is an Assistant Professor in the Department of Computer Science and Engineering at Korea University's College of Informatics, where he has been a faculty member since March 2023. Previously, he was a Post Doctoral Fellow at Oracle Labs, Australia (2022-2023). He earned his Ph.D. from KAIST under Professor Sukyoung Ryu, focusing on JavaScript static analysis for evolving language specifications. His academic background includes: Integrated M.S. & Ph.D. in School of Computing, KAIST (2016-2022) B.S. in School of Computing and Mathematical Sciences, KAIST (2012-2016) Dr. Park's research centers on programming languages and software engineering, with expertise in program analysis, mechanized specification, program synthesis, and automated testing. He leads the ESMeta project, which extracts mechanized specifications from the ECMAScript standard to generate language-based tools. His work particularly targets JavaScript, aiming to improve the reliability and security of modern software systems through innovative specification and analysis techniques. His recent publications at top conferences (including ASE 2025 and ESEC/FSE 2025) demonstrate a strong trend in static analysis and specification for JavaScript. These works, such as Debun for detecting bundled libraries and JSSpecVis for specification visualization, reflect his commitment to developing practical tools that address real-world software engineering challenges. Dr. Park has received numerous honors and awards: Korea University Excellent Course Award for COSE212 Programming Languages (2023-2) Ph.D. Dissertation Award, College of Engineering, KAIST (2022) Outstanding Ph.D. Thesis, School of Computing, KAIST (2022) ACM SIGSOFT Distinguished Paper Award, ICSE 2021 Ph.D. Fellowship Award, NAVER Corp. (2020) Outstanding Teaching Assistant Award for KAIST CS320 Programming Languages (awarded multiple times between 2016 and 2019) Outstanding Teaching Assistant Award for KAIST CS109 Programming Practice (2016 Spring) Best Paper Award, SOAP 2017 ACM Student Research Competition 3rd Place, Modularity 2014 KAIST Presidential Fellowship (2013) He is actively recruiting graduate students, undergraduates, and postdoctoral researchers for his research group at Korea University. His work is conducted within the Programming Language Research Group (PLRG), where he leads the ESMeta project and collaborates on advancing programming language theory and software engineering practice. Future research directions include extending ESMeta to support more language features and improving the scalability of specification-based tools.

• Programming Languages
• Software Engineering
• Program Analysis
• +۶ مورد دیگر

Zhou Yang is an Assistant Professor at the University of Alberta and Fellow at the Alberta Machine Intelligence Institute (Amii), with research focusing on the intersection of software engineering and artificial intelligence. His academic journey includes a Ph.D. from Singapore Management University, an M.Sc. in Software System Engineering from University College London, and undergraduate studies at Yangzhou University. His research interests span Software Engineering, Artificial Intelligence, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), Large Language Models, and Cybersecurity. Yang's work explores how human and AI collaboration can improve code writing, how AI impacts open-source communities, and how developers build software in emerging environments like VR/AR. His recent publications demonstrate strong trends in code language models, with significant contributions to ASE, ICSE, ISSTA, and top journals like TOSEM and TSE. His research addresses critical challenges including token efficiency in code generation, user perception of AI coding assistants, privacy preservation in code models, and fairness in AI systems. 2024 IEEE Computer Society Best Paper Award (1 out of 183 submissions) ACM Distinguished Paper Award from ISSTA 2024 Distinguished Reviewer Award from Internetware 2024 SMU Research Staff Excellence Award (1 of 4 university-wide) SMU Presidential Fellowship Award SMU Dean's List Award 1st Place in ACM Student Research Competition at ICSE 2024 Yang actively mentors graduate students with regular one-on-one meetings, constructive feedback, and support for top-venue publications. He provides full funding through teaching assistantships and research grants, including travel support for conferences. His lab focuses on responsible research conduct and societal implications of AI work. Though early-career, he actively builds professional networks for students through collaborations and supports diverse career paths in academia and industry. He leads research in the Alberta Machine Intelligence Institute, focusing on practical applications where software engineering principles enhance AI systems and where AI techniques solve real-world software engineering challenges.

• Software Engineering
• Artificial Intelligence
• AI for Software Engineering
• +۳ مورد دیگر

Xiaoning Du is a Senior Lecturer (equivalent to U.S. Associate Professor) at the Department of Software Systems and Cybersecurity within the Faculty of Information Technology at Monash University, Australia. She was promoted to this position effective July 1, 2025, having previously served as a Lecturer (Assistant Professor) since joining Monash in February 2021. Her research bridges the gap between theory and practical applications of program analysis and formal methods in evaluating traditional and AI-assisted software systems. Dr. Du's educational background includes: PhD from Nanyang Technological University (2020) Bachelor's degree from Fudan University (2014) Dr. Du specializes in software engineering, artificial intelligence, and cybersecurity , with particular focus on SE4AI (Software Engineering for AI), software analysis and testing . Her research has made significant contributions to the security and quality assurance of intelligent software systems, especially intelligent software engineering tools. She is best known for her work on Devign , BigCodeBench , DeepStellar , and SimPy , which have advanced the fields of code generation, program analysis, and AI security. Her approach consistently bridges theoretical foundations with practical applications to improve software quality and security. Dr. Du's recent publications demonstrate a strong focus on the intersection of software engineering and AI, particularly examining how large language models interact with source code. Her work addresses critical challenges in code generation efficiency, security vulnerabilities in AI-assisted development, and fairness in AI systems. She has made significant contributions to benchmarking frameworks like BigCodeBench and has pioneered research on watermarking techniques to protect code datasets from misuse by neural code completion models. Dr. Du has received numerous prestigious awards and recognitions: 2024 Google Research Scholar Award in Software Engineering ACM SIGSOFT Distinguished Paper Award (ISSTA'24) ICLR Oral presentation (2025) 2024 FIT Dean's Early Career Researcher of the Year Award Multiple FIT ECR Seed Grants (2021-2023) Dr. Du actively mentors PhD students, with notable successes including Terry (2024-2025 IBM PhD Fellowship Award recipient) and Zhensu (2024 Bytedance Scholarship Award recipient). She is currently seeking self-motivated PhD students with strong programming skills and relevant research experience, offering full scholarship support. Her research has been supported by multiple grants including the Google Research Scholar Program award and several FIT ECR Seed Grants that have enabled her team to pursue innovative research in software security and AI-assisted development. Dr. Du leads a research group focused on intelligent software systems security and quality assurance. Her team has developed several influential tools and benchmarks including Devign, BigCodeBench, DeepStellar, and SimPy. These resources have become important assets for researchers and practitioners working at the intersection of software engineering and artificial intelligence, particularly in the areas of code generation, program analysis, and security testing of AI systems.

• Software Engineering
• Artificial Intelligence
• Cybersecurity
• +۳ مورد دیگر

Gang (Gary) Tan is a Professor in the Computer Science and Engineering Department at Pennsylvania State University, co-directing the Institute for Networking and Security Research (INSR). His research bridges computer security, formal methods, and programming languages to develop practical solutions for software vulnerabilities and AI fairness. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University Dr. Tan specializes in applying compiler techniques and formal verification to security challenges, with seminal work on cache side-channel attacks and fairness in machine learning. His Security of Software (SOS) Group develops frameworks that integrate theoretical guarantees into real-world systems, emphasizing measurable security outcomes and ethical AI. Recent projects focus on quantifying bias in neural networks and mitigating speculative execution vulnerabilities. Analysis of his 2021-2025 publications reveals a strategic pivot toward AI security, where he pioneers methods for fairness testing (e.g., information-theoretic debugging) and repair (e.g., NeuFair). Concurrently, his security work evolves from foundational side-channel research (SpecSafe, 2021) toward hardware-software co-design solutions, demonstrating consistent innovation across theoretical and applied domains. Scientific Awards: James F. Will Career Development Professorship NSF CAREER Award Google Research Award (two instances) Distinguished Reviewer Award at 2018 IEEE Symposium on Security and Privacy Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Best Paper Award at PLDI 2024 Dr. Tan leads the SOS Group with funding from NSF (including CAREER), DARPA (ISAT study group membership), and industry partners like Google. His grants support interdisciplinary projects spanning secure compilation, fairness engineering, and hardware security, while his teaching excellence award reflects commitment to pedagogy in core systems courses. He co-directs Penn State's Institute for Networking and Security Research (INSR), fostering collaboration between systems, security, and AI researchers. The SOS Group maintains active partnerships with industry security teams and contributes to open-source tools for vulnerability detection, with recent work expanding into fairness certification for machine learning pipelines.

• computer security
• formal methods
• programming languages
• +۳ مورد دیگر

Lars Grunske is a Professor in the Department of Computer Science at Humboldt University of Berlin, Germany. His academic career spans multiple institutions across Germany, Australia, and internationally, with a strong focus on research and conference participation in software engineering. His educational background includes a PhD in computer science from the University of Potsdam (Hasso-Plattner-Institute for Software Systems Engineering) in 2004. Professor Grunske's research interests center on modeling and verification of systems and software, with particular emphasis on automated analysis techniques. His work primarily focuses on probabilistic and timed model checking and model-based dependability evaluation of complex software intensive systems. He has made significant contributions to software testing, program repair, formal methods, and the application of machine learning techniques to software engineering problems. His publication record shows consistent contributions to top software engineering conferences over the past decade, with recent work exploring the intersection of AI/ML with traditional software engineering challenges. His research demonstrates an evolution from foundational model checking techniques toward more practical applications in software testing and repair. Boeing Postdoctoral Research Fellow Professor Grunske actively mentors through conference activities including chairing mentoring circles at ICSE 2021. He serves on numerous program committees for major software engineering conferences including ASE, ICSE, ESEC/FSE, and others, demonstrating his standing in the academic community. His involvement spans multiple roles from committee member to track chair and award committee positions. He maintains an active research laboratory focused on software verification and testing, as indicated by his departmental affiliation and research website.

• Software Engineering
• Automated Software Engineering
• Systems Verification
• +۴ مورد دیگر

Andreas Zeller serves as Professor for Software Engineering at Saarland University and faculty at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. His dual appointments position him at the intersection of academic research and practical cybersecurity applications, contributing significantly to both institutions' research profiles. Professor Zeller's research spans multiple dimensions of software quality assurance, with particular expertise in automated debugging techniques, mining software repositories for insights, specification mining, and security testing methodologies. His work consistently bridges theoretical foundations with practical implementation, resulting in tools and frameworks adopted widely in both research and industry contexts. Analysis of his recent publications reveals an evolutionary trajectory from foundational debugging work toward increasingly sophisticated grammar-based testing approaches, with notable integration of machine learning techniques in recent years. His research demonstrates consistent focus on improving software reliability through automated analysis, with growing emphasis on security applications including XML injection testing, GNSS module security, and binary file format vulnerabilities. Recipient of two ERC Advanced Grants (including the S3 project) ACM Fellow ACM SIGSOFT Outstanding Research Award Professor Zeller has successfully secured substantial research funding through competitive mechanisms including ERC grants, enabling his team to pursue ambitious research agendas. His leadership extends to mentoring through his roles as doctoral symposium co-chair and active participation in new faculty development initiatives. He maintains strong engagement with the research community through numerous program committee memberships and conference organization roles. At CISPA Helmholtz Center for Information Security, Zeller contributes to the center's mission through research focused on software security testing and analysis. His work on grammar-based testing and fuzzing directly addresses critical security challenges in modern software systems, with practical applications for improving software resilience against attacks.

• Software Analysis and Testing
• Automated Debugging
• Mining Software Archives
• +۳ مورد دیگر

Thomas Degueule is a researcher at CNRS (Centre National de la Recherche Scientifique) in France, actively contributing to software engineering research since 2015. He serves on program committees for major conferences including ASE, ICSE, and SLE, with primary research interests in Software Evolution, Empirical Software Engineering, and Domain-Specific Languages. His work focuses on breaking change analysis in APIs and libraries, client-library compatibility testing, and dependency management. He develops practical tools like Roseau for source-based breaking change detection and investigates semantic versioning impacts in ecosystems like Maven Central. His empirical approach leverages large-scale repository analysis to address real-world software maintenance challenges, particularly in Java ecosystems. Recent publications (2023-2025) show consistent contributions to breaking change analysis and compatibility testing, appearing in top venues like ASE, ICSE, and ISSTA. His research bridges theoretical insights with practical tooling for software evolution challenges, demonstrating strong empirical methodology and tool-oriented contributions. No scientific awards are documented in the available information. Degueule has advised no publicly listed students and holds no mentioned research grants. His organizational roles include Program Co-Chair for SLE 2023 and committee positions across multiple conferences, reflecting significant service to the software engineering community.

• Software Evolution
• Empirical Software Engineering
• Domain-Specific Languages
• +۲ مورد دیگر

Zhenbang Chen is a Professor in the College of Computer at National University of Defense Technology (NUDT), China. His academic career spans over a decade with significant contributions to software engineering, particularly in program analysis and formal methods. He has served on program committees for major conferences including ASE, ICSE, and FSE, and has been actively involved in research that bridges theoretical formal methods with practical software engineering applications. Dr. Chen received his Ph.D. and Bachelor degrees in computer science from National University of Defense Technology (NUDT) in June 2009 and July 2002, respectively. His educational background from NUDT has provided a strong foundation for his research in software engineering and formal methods. Ph.D. in Computer Science, National University of Defense Technology (NUDT), 2009 Bachelor's Degree in Computer Science, National University of Defense Technology (NUDT), 2002 Zhenbang Chen's research primarily focuses on program analysis, with special emphasis on symbolic execution techniques. His work extends to formal methods and their practical applications in software engineering. He investigates constraint solving approaches to improve the efficiency of program analysis and explores program synthesis techniques to automate software development tasks. His research bridges theoretical foundations with practical software engineering challenges, particularly in the areas of software verification and testing. His recent work has increasingly focused on optimizing symbolic execution through novel constraint solving techniques and exploring multi-modal approaches to behavior tree synthesis. This demonstrates his commitment to advancing both the theoretical underpinnings and practical applications of software analysis techniques. Professor Chen's publication record shows a consistent focus on symbolic execution and constraint solving, with a clear progression toward more sophisticated optimization techniques. His recent work demonstrates a shift toward multi-objective optimization for floating-point constraints and multi-modal approaches to program synthesis. The research spans both theoretical foundations and practical implementations, with several tools developed from his research participating in international competitions. Dr. Chen's research excellence has been recognized through multiple prestigious awards: ACM SIGSOFT Distinguished Paper Award for FSE 2025 paper "QSF: Multi-Objective Optimization based Efficient Solving for Floating-Point Constraints" ACM SIGSOFT Distinguished Paper Award for ISSTA 2021 paper "Type and interval aware array constraint solving for symbolic execution" ACM SIGSOFT Distinguished Paper Award for ICSE 2018 paper "Towards optimal concolic testing" Bronze Medal (3rd place) in Cover-Branches category at Test-COMP 2025 for the FDSE tool Professor Chen is actively involved in mentoring the next generation of researchers, currently seeking Ph.D. and M.Sc. students to work with him on cutting-edge research in program analysis and formal methods. His research group has developed several tools that have gained recognition in international competitions, including AISE which ranked 1st in SV-COMP 2025's ReachSafety-Loops category and FDSE which won Bronze Medal in Test-COMP 2025. His research has been supported by grants that enable participation in major international conferences and competitions, fostering collaborations with researchers worldwide. Dr. Chen leads a research group focused on program analysis and formal methods at NUDT. His team has developed several notable tools including AISE for program verification and FDSE for software testing, which have achieved top rankings in international competitions like SV-COMP and Test-COMP. The research group maintains active collaborations with other institutions and participates regularly in major software engineering conferences, contributing to both theoretical advancements and practical tool development in the field.

• Program analysis
• Symbolic execution
• Formal methods
• +۲ مورد دیگر

Hwa Cheon Lee serves as a Lecturer in the Korean Department at Boğaziçi University, Türkiye, teaching Korean language courses continuously since 2010 while pursuing doctoral studies. Their work bridges academic instruction with practical cultural transmission to Turkish learners. Educational background includes: Ph.D. (expected 2025) in Korean Language and Literature, Erciyes University, Türkiye M.A. in Education Engineering, Sookmyung Woman’s University, South Korea (2014) B.A. in Economics, Boğaziçi University, Türkiye (1999) Lee's research centers on Korean culture and literature, manifested through pedagogical innovations that make Korean accessible to Turkish speakers. The integration of cultural context within language instruction forms the cornerstone of their approach, enabling students to grasp both linguistic structures and societal nuances. Publications reveal a consistent focus on practical language acquisition tools, with multiple editions of Korece Öğreniyorum 1&2 evolving to meet learner needs, alongside the proverb compilation Kore Atasözleri which bridges linguistic study with cultural wisdom. These works collectively emphasize structured progression from basic grammar to cultural literacy. As an educator, Lee has facilitated significant student outcomes through the Global Korea Scholarship Program (GKS), with nearly annual selections of students for advanced study in South Korea since 2012. This success stems from tailored instructional methods that prepare learners for immersion experiences and academic pursuits.

• Korean culture
• Korean literature
• Language Education
• +۱ مورد دیگر