جستجوی استاد راهنمای دانشگاهی

Jifeng Xuanمشاهده پروفایل

استاد

• Software Testing and Debugging
• Software Data Analysis
• Search Based Software Engineering
• +۲ مورد دیگر

Dr. Jifeng Xuan is a Professor and Deputy Dean at the School of Computer Science, Wuhan University, China. He founded the CSTAR (Centre of Software Testing, Analysis and Reliability) and holds editorial roles at Empirical Software Engineering and PLOS One . Previously, he was a postdoctoral researcher at INRIA Lille-Nord Europe (France) and earned his PhD from Dalian University of Technology. Research Interests: His work focuses on software testing, debugging, automated program repair, software data analysis, and search-based software engineering. He integrates AI/ML techniques for tasks like log analysis, fuzz testing, and vulnerability detection, with applications in robotics, microservices, and Android development. Publication Trends: Recent articles (2022–2025) emphasize AI-driven software engineering, including LLM-based repair, reinforcement learning for testing, and deep learning surveys. Security (vulnerability logs) and empirical studies on industrial challenges (e.g., C program repair) are recurring themes. Awards & Honors: ACM SIGSOFT Distinguished Paper Award (2025) IEEE TCSE Distinguished Paper Award (2025) CCF NASAC Youth Software Innovation Award (2024) Outstanding Doctoral Dissertation Award, China Computer Federation (2014) Luojia Young Scholar (2015) Student Advising & Labs: Actively recruits PhD and master students for CSTAR Lab. Research areas include automated debugging, testing tools (e.g., Mergebot, FastLog), and AI-generated code assessment. No specific grants listed.

Brian Fitzgeraldمشاهده پروفایل

استاد

• Software Engineering
• Information Systems
• Open Source Software Development
• +۶ مورد دیگر

Brian Fitzgerald holds the Frederick A Krehbiel II Chair in Innovation in Business and Technology at the University of Limerick and serves as Director of Lero - the Irish Software Research Centre. He is a globally recognized leader in software engineering and information systems research with significant contributions to open source, agile methodologies, and global software development. His research interests focus on software development methodologies, particularly in open source, inner source, crowdsourcing, agile, lean, BizDevOps, and continuous software engineering. Fitzgerald's work bridges theoretical foundations with practical applications in global software engineering contexts. The trends in his recent publications demonstrate a consistent focus on empirical studies of software development practices, with increasing attention to large language models, community dynamics in open source, and scaling agile methodologies in enterprise environments. His research spans both theoretical frameworks and practical applications across multiple software development domains. AIS Fellow award recipient LEO Award for outstanding lifetime contribution to the IS discipline (2024) President of the Association for Information Systems (2020) Fitzgerald has secured over €115 million in peer-reviewed research funding, including a notable €6 million project with Huawei. He serves as General Chair for major conferences including the 49th International Conference on Software Engineering (ICSE) in Dublin 2027 and previously chaired the 37th International Conference on Information Systems (ICIS) in 2016. His leadership extends to directing Lero, Ireland's national software research center that coordinates researchers across nine third-level institutions. As Director of Lero, Fitzgerald oversees a major research center focused on critical software domains including driverless cars, automation, artificial intelligence, and cybersecurity. His work connects academic research with industry applications through collaborations with major technology companies and government initiatives.

• Software Engineering
• Model Checking
• System Modeling
• +۵ مورد دیگر

Seung Yeob Shin serves as a Research Scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where he contributes to the Software Verification and Validation (V&V) Lab under Prof. Lionel Briand. His active participation in major software engineering conferences includes serving on ASE 2025's Research Papers Program Committee and authoring multiple journal-first publications presented at premier venues like ICSE and ESEC/FSE. Shin earned his PhD in 2016 from the Laboratory for Advanced Software Engineering Research (LASER) at the University of Massachusetts Amherst's College of Information and Computer Sciences. His research expertise centers on applying formal methods to complex software systems, with particular emphasis on model-based verification techniques. His current research program bridges theoretical modeling and practical system validation across critical domains. Key focus areas include developing simulation frameworks for software-defined networks, creating model-checking approaches for cyber-physical control loops, and establishing probabilistic methods for real-time system verification. This work consistently targets reliability challenges in safety-critical infrastructure through rigorous engineering methodologies. Recent publications demonstrate a cohesive trajectory in applying formal verification to emerging system paradigms. The 2024 journal-first papers reveal increasing sophistication in handling non-deterministic behaviors across networking, embedded systems, and requirements engineering domains, with notable emphasis on failure induction and probabilistic safety guarantees. No scientific awards were documented in the available materials. While conference contributions indicate significant scholarly engagement, no information regarding student advising or research grants appears in the provided documentation. As a core member of the V&V Lab at SnT, Shin contributes to Luxembourg's national cybersecurity research infrastructure. The lab specializes in developing mathematical frameworks for system validation, with current projects addressing verification challenges in autonomous systems, critical infrastructure, and secure communications protocols through model-driven approaches.

Tegawendé F. Bissyandéمشاهده پروفایل

استاد

• Program repair
• Software Security
• Code Search
• +۶ مورد دیگر

Prof. Tegawendé F. Bissyandé is a Chief Scientist in the Professor category at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. He holds the prestigious position of ERC Fellow and serves as Principal Investigator of the NATURAL project focused on Artificial Intelligence for Program Repair. His research spans software engineering, cybersecurity, and artificial intelligence, with particular emphasis on applying machine learning techniques to software development and security challenges. Dr. Bissyandé's research interests include: Software Debugging (especially bug localization and program repair) Software Security (especially malware detection and analysis) Code Search (both free-form and semantic code-to-code) Machine Learning and Natural Language Processing for software engineering Cyber-security applications in mobile and cloud environments His recent work demonstrates a strong focus on leveraging Large Language Models (LLMs) for various software engineering tasks. Analysis of his 15 most recent publications reveals several key trends: extensive application of LLMs to program repair and code generation; innovative approaches to Android security and malware detection; development of novel techniques for code search and understanding; and exploration of the intersection between natural language processing and software engineering. His research increasingly bridges theoretical software engineering with practical applications in mobile security and developer productivity tools, with a significant portion of his work focusing on Android ecosystem security and program repair technologies. Dr. Bissyandé has received numerous prestigious awards throughout his career: APSEC Best ERA Paper Award (2018) for 'LSRepair: Live Search of Fix Ingredients for Automated Program Repair' IPSJ SIG SE Excellent Research Award (2018) for 'FaCOY: a Code-to-Code Search Engine' FOSS Impact Paper Award (2018) for 'Characterizing Deprecated Android APIs' SANER Best ERA Paper Award (2016) for 'Parameter Values of Android APIs: A Preliminary Study on 100,000 Apps' ASE Best Paper Award (2012) for 'Diagnosys: automatic generation of a debugging interface to the Linux kernel' As an active member of the software engineering research community, Dr. Bissyandé serves on program committees for major conferences including ICSE, ASE, and ISSTA, and has been an Area Chair for ICSE 2024. His industry partnerships include significant collaborations with BGL BNP Paribas (since January 2019), Luxembourg Stock Exchange (since January 2018), and Paul Wurth (January 2015 to 2018), demonstrating the practical impact of his research. He leads the SerVAL lab at SnT, which focuses on software validation and analysis, with particular expertise in mobile security and program repair technologies, and actively mentors PhD candidates through FNR research grants.

Jonathan Bellمشاهده پروفایل

دانشیار

• Software Testing
• Software Engineering
• Program Analysis
• +۶ مورد دیگر

Jonathan Bell is an Associate Professor in Software Engineering and Software Systems at Northeastern University's Khoury College of Computer Sciences. Previously, he was faculty at George Mason University where he received a university-wide Teacher of Distinction award. Bell directs research that makes it easier for developers to create reliable and secure software by improving software testing and program analysis. His research spans several key areas in software engineering: flaky tests, fuzzing, software supply chain analysis, and continuous integration. Bell's work on accelerating software testing earned an ACM SIGSOFT Distinguished Paper Award (ICSE '14), and his contributions to the object-oriented programming community were recognized with the 2020 Dahl-Nygaard Junior Researcher Prize. His program analysis research has resulted in widely adopted runtime systems including the Phosphor taint tracking system and CROCHET checkpoint/rollback tool. His recent publications reveal a consistent focus on practical software engineering problems with empirical validation. His work increasingly addresses the challenges of modern software supply chains and dependency management, building on his earlier foundational work in testing and program analysis. The trend shows progression from specific testing problems to broader software ecosystem challenges. ACM SIGSOFT Distinguished Paper Award (ICSE '14 - Unit Test Virtualization with VMVM) Dahl-Nygaard Junior Researcher Prize (2020) NSF CAREER award recipient Teacher of Distinction award from George Mason University Bell actively serves the software engineering community through program committee work for major conferences (ICSE, ASE, FSE, ISSTA), co-organizing mentoring workshops, and contributing to open source projects. He co-founded the Clowdr open source project during the pandemic to support virtual academic conferences and subsequently co-founded a startup around it. His research has been funded by the NSA and NSF, and he serves on the Computing Research Association's Education Board.

Andreea Costeaمشاهده پروفایل

استادیار

• Programming Languages
• Software Verification
• Automated Program Repair
• +۴ مورد دیگر

Andreea Costea is an Assistant Professor in the Programming Languages Group within the Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS) at Delft University of Technology. She joined TU Delft in October 2024 after completing her PhD at the School of Computing, National University of Singapore (NUS), where she worked in the Programming Languages and Software Engineering lab collaborating with the Automated Program Repair team, Trustworthy and Secure Software group, and VERSE lab. Her primary research focuses on programming languages design and implementation, with particular emphasis on software verification for critical code, program synthesis, and automated program repair. She maintains strong connections with industry while pursuing formal methods research, especially in the context of Rust programming language safety and interoperability. Dr. Costea's publication record demonstrates consistent contributions to software engineering and programming languages research, with recent work focusing on automated program repair techniques, Rust language safety mechanisms, and communication protocol verification. Her research shows a clear trajectory from theoretical foundations in session types and separation logic toward practical applications in memory safety and program repair. She actively serves the research community as Program Committee member for major conferences including ASE, ICSE, ICFP, and APLAS. Her service includes chairing publicity committees for SPLASH and artifact evaluation for ESOP. Regular Journal Reviewer: CACM, TOSEM, TSE Panel discussions: PLMW @ POPL'22, PLDI'21, PLMW @ PLDI'21, POPL'21 Extensive reviewing for top-tier conferences including POPL, OOPSLA, CAV, VMCAI Dr. Costea supervises multiple Master's students working on Rust-related safety projects and is actively recruiting PhD students to work on software interoperability, particularly focusing on how to restore Rust's safety guarantees when integrating with legacy C code and ensuring correct interaction between components written in different languages.

Sam Malekمشاهده پروفایل

استاد

• Software Engineering
• Software Analysis and Testing
• Mobile Computing
• +۳ مورد دیگر

Sam Malek is a Professor in the Department of Informatics at the University of California, Irvine's School of Information and Computer Sciences, where he directs the Software Engineering and Analysis Laboratory. Previously serving as Director of the Institute for Software Research (2018-2022), his academic leadership spans software engineering research and institutional management. His research centers on software engineering with specialized expertise in software analysis and testing , mobile computing , security , software architecture , and accessible computing . Malek's work consistently focuses on developing practical techniques and tools for constructing, analyzing, and maintaining large-scale software systems, with recent emphasis on accessibility challenges in mobile and web environments. His publication trends reveal a strategic shift toward accessible computing since 2020, where he pioneered frameworks like Ma11y for web accessibility testing and Groundhog for mobile app crawling. Earlier work established foundations in energy testing (2020), GUI input generation (2021), and architectural analysis, demonstrating methodological evolution from core software engineering to human-centered accessibility solutions. ACM SIGSOFT test-of-time award (2020) National Science Foundation CAREER award (2013) GMU Emerging Researcher/Scholar/Creator award (2013) GMU Computer Science Department Outstanding Faculty Research Award (2011) Malek serves on editorial boards for ACM Transactions on Software Engineering and Methodology and ACM Transactions on Autonomous and Adaptive Systems , while frequently acting as a software expert witness in intellectual property litigation. His research group actively recruits PhD students through UCI's Software Engineering PhD program, with current projects focusing on AI-driven accessibility solutions and mobile testing frameworks. The Software Engineering and Analysis Laboratory under his direction maintains strong industry connections through sponsored research and tool development, particularly in accessibility testing and mobile application quality assurance.

Haipeng Caiمشاهده پروفایل

دانشیار

• Software Engineering
• Program Analysis
• Software Security
• +۵ مورد دیگر

Haipeng Cai serves as an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. His academic work spans software engineering, program analysis, and software security with particular emphasis on adaptive analysis techniques for mobile and distributed systems. His research interests center on adaptive/data-driven static and dynamic analysis for security applications targeting mobile apps, distributed systems, and multilingual software. Current work focuses on enhancing vulnerability detection, cross-language bug analysis, and automated security tooling through machine learning approaches. His lab produces tools like VinJ for vulnerability data generation and PolyFax for multilingual software characterization. Recent publications reveal strong trends in multilingual system security and AI-enhanced analysis , with 15+ papers since 2022 addressing cross-language vulnerabilities, Android security, and learning-based vulnerability detection. His work bridges theoretical program analysis with practical security applications in real-world software ecosystems. As an active academic contributor, he serves on program committees for major conferences including ASE, ICSE, and FSE, and will deliver a keynote at PROMISE 2025. His leadership includes journal-first paper chair roles and session chair positions at top software engineering venues. Dr. Cai maintains an active research presence through his personal website , GitHub repository ( github.com/chapering ), and academic social media profiles, with consistent contributions to the software engineering research community since 2018.

Huong Haمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Software Engineering
• Automated Machine Learning
• +۵ مورد دیگر

Dr. Huong Ha is a tenured Senior Lecturer in Computer Science and Program Manager of the Bachelor of Computer Science at the School of Computing Technologies, RMIT University, Australia. Previously, she worked at the Applied Artificial Intelligence Institute (A2I2), Deakin University, Australia. She received her PhD from the University of Newcastle, Australia in May 2017. Her educational background includes: PhD in Computer Science from the University of Newcastle, Australia (2017) Dr. Ha's research focuses on the intersection of Machine Learning and Software Engineering, specializing in Automated Machine Learning (particularly Bayesian Optimization), Trustworthy Machine Learning, and Data-driven Software Engineering. Her work addresses critical challenges in intelligent incident management of software systems and quality prediction and optimization for software systems. She has made significant contributions to root cause analysis for microservice systems using causal inference and Bayesian optimization techniques. Her publication record shows a strong trend in applying advanced machine learning techniques to software engineering problems, particularly in microservices architecture. Her recent work demonstrates expertise in developing benchmarking frameworks (RCAEval) and optimization methods (MOCA-HESP) that bridge theoretical advancements with practical applications in software systems. Dr. Ha has received numerous awards and recognitions: Top High-volume Course at RMIT (Semester 1, 2025) Outstanding Reviewer of KDD 2025 Research Track Special Commendation for 2024 RMIT STEM College Learning and Teaching Award ACM SIGSOFT Best Artifact Award at FSE 2024 Top Reviewer of NeurIPS 2022-2023 As Program Manager of the Bachelor of Computer Science, Dr. Ha plays a key role in curriculum development and academic leadership. She actively supervises PhD students including Thuan (Solving Mathematical Problems with LLMs) and Thanh (Fraud Detection for Blockchain Networks), and has secured multiple research grants including the OpenAI Researcher Access Grant (10,000 USD) and several RMIT RACE Merit Allocation Scheme grants. Her academic service includes serving on program committees for major conferences in both machine learning (NeurIPS, ICML) and software engineering (ASE, ICSE).

Sebastian Ottمشاهده پروفایل

استاد

• Business Information Systems
• Computer Science

Sebastian Ott is a Professor in the Faculty of Computer Science at Hof University of Applied Sciences, specializing in Business Information Systems. Based at Campus Hof, Building B, Room B129, he maintains office hours every Tuesday from 13:00 to 14:00 and can be contacted via phone (+49 9281 409 - 4812) or email. His research focuses on Business Information Systems, bridging computer science and business management to develop information systems that optimize organizational processes and decision-making. This interdisciplinary field integrates software engineering, data management, and business process modeling to address real-world enterprise challenges.

Rainer Kellerمشاهده پروفایل

استاد

• Operating Systems
• Distributed Systems
• Parallel Programming
• +۴ مورد دیگر

Prof. Dr.-Ing. Rainer Keller serves as Vice Dean of the School of Computer Science and Information Technology at Esslingen University of Applied Sciences. He concurrently holds Laboratory Management roles for both the Operating Systems Laboratory and Information Technology Laboratory, coordinates the Applied Computer Science (Master) program, and serves on the Environmental Committee for his school. His academic journey includes a Doctorate in Engineering (with distinction), Research Associate and Group Leader positions at HLRS, University of Stuttgart (leading the 9-member "Applications, Models and Tools" group), PostDoc tenure at Oak Ridge National Laboratory (ORNL), and prior appointments at Stuttgart University of Applied Sciences. Keller's research centers on operating systems, distributed systems, and HPC with specialized expertise in Linux-based parallel programming tools and file I/O optimization. His work bridges theoretical system models with practical performance tuning, particularly in high-performance computing environments where syscall tracing and storage optimization are critical. Recent publications reveal consistent focus on system-level performance analysis, evolving from foundational file I/O profiling (2020) to advanced syscall tracing mechanisms (2022) and forward-looking access optimization frameworks (2025). These works demonstrate applied research in Linux ecosystems with direct relevance to HPC infrastructure. As Program Coordinator for the Applied Computer Science (Master) program and laboratory manager for two key facilities, he oversees academic development and hands-on technical training. His consultation hours (Tuesdays 1-2 PM by appointment) support student engagement in systems research. He actively contributes to national HPC infrastructure as a Member of the State User Committee (LNA) bwHPC, influencing regional high-performance computing strategies while maintaining his laboratory management responsibilities at Esslingen.

• Cybersecurity
• Blockchain Technology
• Edge Computing
• +۳ مورد دیگر

Yu Chen is a researcher affiliated with Binghamton University (College of Engineering and Applied Sciences, Department of Computer Science) and University of Southern California , with additional ties to institutions like Chinese Academy of Sciences and Tsinghua University. Their work spans cybersecurity, blockchain technology, edge computing, and IoT systems , focusing on decentralized architectures for public safety, privacy-preserving surveillance, and defense against deepfake attacks. Primary Affiliation: Binghamton University, NY, USA Previous Affiliation: University of Southern California, CA, USA Yu Chen’s research explores blockchain-enabled security frameworks for IoT networks, UAV systems, and smart cities. Recent projects include the Microverse metaverse model and ELOCESS smart grid management. They specialize in real-time data authentication using Electrical Network Frequency (ENF) signals and edge-based privacy solutions for video surveillance and personal drones. Their 15 most recent publications address digital twin security , decentralized data marketplaces, and lightweight protocols for IoT devices. Key areas include UAV network resilience , smart city surveillance , and metaverse classroom models . Yu Chen collaborates with researchers such as Erik Blasch , Ronghua Xu , and Genshe Chen . No student names or specific awards are listed in the provided data.

Christian Meilickeمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Knowledge Graphs
• Ontology Matching
• +۵ مورد دیگر

Christian Meilicke is a Researcher at the Data and Web Science Group (DWS) within the School of Business Informatics and Mathematics at the University of Mannheim. His work focuses on artificial intelligence, ontology matching, and knowledge graph completion, with recent contributions to rule-based methods and their applications in business process modeling. He is heavily involved in teaching, coordinating courses such as 'Modeling Business Processes' and 'Artificial Intelligence.' His research interests include the integration of open and structured knowledge, probabilistic reasoning frameworks, and improving the efficiency of knowledge base systems. He has explored topics like inductive logic programming, automated debugging of ontologies, and the use of Markov Logic Networks for root cause analysis in IT systems. In terms of trends, his recent publications emphasize combining symbolic rule-based approaches with machine learning for knowledge graph tasks, such as activity recommendation and link prediction. He also investigates explainability in embeddings and temporal forecasting in knowledge graphs. His work often bridges theoretical advancements with practical applications in business informatics and data integration. No scientific awards have been explicitly mentioned. Christian has advised no formal students listed here but has contributed to teaching and mentoring through his courses and tutorials. His research and teaching are closely tied to the DWS Group, which focuses on data-centric AI and semantic technologies.

• Mathematical Biology
• Computational Modeling
• Biophysics
• +۳ مورد دیگر

Sabine Fischer is a Professor for Supramolecular and Cellular Simulations at the University of Würzburg’s Center for Computational and Theoretical Biology (CCTB). She holds a PhD in Mathematics from the University of Nottingham (2009) and completed postdoctoral research at the University of Cambridge (2009-2011) and the University of Frankfurt (2011-2017). Her work focuses on mathematical modeling and data-driven simulations of biological processes across subcellular, multicellular, and multi-tissue scales. Key research areas include agent-based modeling of parasite collective behavior (e.g., Project 7 of SPP 2332 PoP), cell-cell interactions, and morphological modeling with Blender. Her group develops tools for image analysis and applies methods ranging from classical statistics to machine learning. Education: Diploma in Mathematics, University of Würzburg PhD in Mathematical Biology, University of Nottingham (2009) Professional Experience: Postdoc, University of Cambridge (2009-2011) Postdoc, University of Frankfurt (2011-2017) Development Engineer, h.a.l.m. Elektronik GmbH (2017-2018) Professor, University of Würzburg (since 2018) Her research integrates experimental data with computational models to study processes like mouse blastocyst differentiation, tissue-level organization, and parasitic locomotion. Current projects emphasize agent-based modeling of Trypanosoma collective behavior and the development of open-source tools like VESNA for 3D vessel analysis.

Maria Schweigelمشاهده پروفایل

استاد

• Artificial Intelligence Algorithms
• Optimization Techniques
• Software Development
• +۴ مورد دیگر

Professor Maria Schweigel Prof. Maria Schweigel is a Professor at the Department of Autonomous Systems, Schmalkalden University of Applied Sciences. Her teaching focuses on automation control, electronic control systems, robotics, and embedded systems. She leads the research group 'Eingebettete Diagnosesysteme' (Embedded Diagnostic Systems) and specializes in artificial intelligence algorithms, optimization using genetic and evolutionary methods, and biosignal analysis for anesthesia and sleep studies. Her research spans robotics, embedded systems, image processing, and software development with tools like C/C++, MATLAB/Simulink, and LabView. Key projects include real-time EEG classification for anesthesia monitoring, low-SNR biomedical signal extraction, and SVM-based classification on resource-constrained platforms. She has contributed to international conferences like ECT and IWK TU Ilmenau, focusing on interdisciplinary applications in medical technology and autonomous systems. No scientific awards were explicitly listed in the provided materials. Her advising and grants are not detailed here, but her extensive publication record (2009–2016) demonstrates active involvement in collaborative research with colleagues like Wenzel, Walther, and Baumgart-Schmitt. She co-developed tools such as the Multi-EEG-Viewer and explored wireless biomedical signal transmission for relaxation control systems.