جستجوی استاد راهنمای دانشگاهی

Eray Tüzünمشاهده پروفایل

دانشیار

• Software Product Line Engineering
• Empirical Software Engineering
• Gamification
• +۵ مورد دیگر

Eray Tüzün is an Associate Professor of Computer Engineering at Bilkent University in Turkey, where he leads the Bilkent University Software Engineering and Data Analytics Research Group (BILSEN). With over 20 years of experience in software design and development spanning both academia and industry, he bridges theoretical research with practical software engineering applications. His educational background includes bachelor's and master's degrees in Computer Science and a PhD in Information Systems. Before joining Bilkent University, he accumulated substantial industry experience including 9 years at HAVELSAN (serving as Productization Lead, Academy Manager, Product Owner, and Software Engineer), plus roles at Microsoft as a Software Design Engineer in the Online Services group, Senior Software Engineer at Howard Hughes Medical Institute, and Research Engineer at CWRU Genomics Center. His professional certifications include Certified Product Manager, MCSD: Application Lifecycle Management, Professional Scrum Master (PSM), and Professional Scrum Product Owner (PSPO). Tüzün's research focuses on several interconnected areas including Software Product Line Engineering , Empirical Software Engineering , Gamification , Software Engineering Education , DevOps & Agile Software Development , and Bioinformatics . His empirical approach involves mining software repositories to analyze development practices, identify patterns, and propose improvements. Recent work increasingly examines the intersection of AI and software engineering, particularly how large language models can enhance code review and comment quality. His research output shows clear trends toward analyzing code quality metrics, identifying 'smells' in development processes, and applying data analytics to software engineering practices. Key themes include bus factor estimation for measuring knowledge concentration in software projects, empirical studies of code review processes, continuous integration practices, and issue tracking systems in open source projects. Tüzün is a senior member of IEEE and an active member of ACM SIGSOFT and IEEE Computer Society. He represents Bilkent University in the International Software Engineering Research Network (ISERN), connecting his research with the global software engineering community. His service to the field includes program committee roles at major conferences such as ASE, ICSE, ESEC/FSE, and ESEM, with leadership positions including PC Co-Chair for ICSSP 2020 and Industry Track Co-Chair for EASE 2023. As head of the BILSEN research group, he mentors graduate students and collaborates on projects that bridge theoretical research with practical applications. His research has been consistently published in top-tier software engineering venues over the past decade, demonstrating both continuity in core research areas and adaptation to emerging trends like AI-assisted software development.

Antonio Ruiz-Cortésمشاهده پروفایل

استاد

• Service Oriented Computing
• Software Engineering
• Software Architecture
• +۴ مورد دیگر

Antonio Ruiz-Cortés is Professor of Software and Service Engineering at the University of Seville and an elected member of the Academy of Europe. He currently heads the Applied Software Engineering Group at the University of Seville and has served as President of the Spanish Society on Software Engineering (SISTEDES) since September 2018. His research spans multiple critical areas of modern software engineering: Service-Oriented Computing Software Architecture Business Process Management Testing methodologies Software Product Lines Automatic Model Analysis Professor Ruiz-Cortés has established himself as a leading researcher in REST API testing and verification, with multiple influential publications in top software engineering conferences. His work bridges traditional software engineering with emerging domains like quantum computing, demonstrating remarkable adaptability. He has developed practical tools including RESTest and AGORA that address real-world testing challenges faced by industry practitioners. His scientific contributions have been recognized with the Most Influential Paper award at SPLC 2017. He serves as associate editor for Springer Computing and has organized major conferences including JCIS 2008, SPLC 2017, SISTEDES 2018 and BPM 2020, demonstrating significant leadership in the academic community. Professor Ruiz-Cortés maintains active research funding supporting his work in service-oriented computing and software testing, though specific grant details aren't provided in the available information. His presidency of SISTEDES reflects his commitment to advancing software engineering research in Spain.

Sven Apelمشاهده پروفایل

استاد

• Software product lines and configurable systems
• AI-based program generation and optimization
• Socio-technical software analysis
• +۳ مورد دیگر

Professor Sven Apel holds the Chair of Software Engineering at Saarland University's Saarland Informatics Campus in Germany. He is also the Director of the Saarbrücken Graduate School of Computer Science. His work focuses on software engineering with an emphasis on automation, human factors, and interdisciplinary approaches. Prof. Apel received his Ph.D. in Computer Science in 2007 from the University of Magdeburg. His academic journey includes: Ph.D. in Computer Science, University of Magdeburg (2007) Emmy-Noether Fellowship of the German Research Foundation Heisenberg Professorship of the German Research Foundation Prof. Apel's research centers on empowering software engineering practice to enter an era of intensive automation. His key research areas include software variability and configuration, AI-based program generation and optimization, socio-technical software analysis, and empirical and neurophysiological methods. He pays special attention to the human factor and interdisciplinary research questions, applying his findings to real-world software systems from both open-source projects and industry collaborations with partners like Siemens AG, Bosch Engineering, and Airbus Helicopters. Analysis of Prof. Apel's recent publications reveals a strong focus on configurable software systems, neurophysiological approaches to understanding programming, and the application of AI techniques to software engineering problems. His work often bridges the gap between theoretical foundations and practical applications, with many studies involving industrial collaborations. There's a noticeable trend toward interdisciplinary research combining software engineering with neuroscience, organizational studies, and machine learning. Prof. Apel has received numerous prestigious awards and honors: ERC Advanced Grant "Brains On Code" (2022) ACM Distinguished Member for "Outstanding Scientific Contributions to Computing" (2018) Multiple Most Influential Paper Awards (SPLC'18, ICPC'22, GPCE'23) Multiple Best Paper Awards (SPLC'11, Modularity'15, AOM'18) Heisenberg Professorship and Emmy-Noether Fellowship from the German Research Foundation Prof. Apel has advised numerous Ph.D., Master's, and Bachelor's students throughout his career. His research has been generously funded by multiple grants including an ERC Advanced Grant (2,500,000 Euro, 2022-2027), several DFG projects (CPEC, Congruence, Pervolution), and previous grants like SafeSPL, FeatureFoundation, and Pythia. His work has practical impact through collaborations with industry partners including Siemens AG, Bosch Engineering, and Airbus Helicopters. Prof. Apel leads research in the Chair of Software Engineering at Saarland University, where his team explores the intersection of software engineering, neuroscience, and artificial intelligence. His "Brains On Code" ERC project specifically investigates how programmers' brains process code using neuroimaging techniques. The research group maintains strong connections with both academic and industry partners, facilitating the transfer of research findings into practical applications.

Shiva Nejatiمشاهده پروفایل

استاد

• Software Testing and Verification
• Cyber Physical Systems
• Applications of AI to Software Engineering
• +۴ مورد دیگر

Shiva Nejati is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, where he leads research in software engineering with a focus on verification and analysis of cyber-physical systems. Previously, he served as a senior scientist (2012-2019) at the SnT Center, University of Luxembourg, and as a scientist (2009-2012) at the Simula Research Laboratory. He earned his M.Sc. and Ph.D. from the University of Toronto in 2003 and 2008, respectively. His research interests span Software Testing and Verification, Cyber Physical Systems, Applications of AI to Software Engineering, and Search-based Software Engineering. Nejati's work draws on techniques from formal software modeling, meta-heuristics optimization, machine learning, system engineering, and empirical methods. He has extensively worked on testing and fault localization of cyber physical systems, particularly applied to autonomous vehicles and IoT systems, while also exploring requirements traceability, automated configuration of product line systems, and simulation modeling of CPS. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional software verification techniques, particularly for complex cyber-physical systems. His work bridges search-based testing with formal verification methods to address the challenges of testing compute-intensive models in domains like autonomous vehicles and satellite systems. The research shows increasing focus on applying machine learning to solve longstanding problems in software testing and requirements engineering. Nejati serves in significant leadership roles across major software engineering conferences, including PC Chair for ASE 2026, General Chair for CASCON 2026, and various program committee and organizing committee roles for ICSE, ISSTA, MODELS, and other top-tier conferences. He is also an Associate Editor for EMSE Journal and ASE Journal, and previously served on the IEEE Transactions on Software Engineering editorial board. He teaches advanced courses including 'AI-enabled Software Verification and Testing' and 'Software Construction' at the University of Ottawa, while leading the Sedna lab which focuses on verification, analysis, and testing of complex systems. His research is conducted in close collaboration with industry partners across telecommunication, maritime, energy, automotive, and aerospace sectors.

Austin Mordahlمشاهده پروفایل

استادیار

• Static Analysis
• Taint Analysis
• Automated Testing
• +۴ مورد دیگر

Austin Mordahl is an Assistant Professor in the Department of Computer Science at the University of Illinois Chicago. His research focuses on improving the usability and reliability of software quality assurance tools, particularly static analyses and fuzz testing. Dr. Mordahl actively seeks students interested in cutting-edge research in software engineering at UIC. Dr. Mordahl's research interests span multiple areas of software engineering with a particular emphasis on: Static Analysis and Taint Analysis for software security Automated Testing techniques including fuzz testing Improving the usability and reliability of software quality assurance tools Configurable static analysis tools and their behavior Applying machine learning to triage and configure static analysis tools Lifting static analysis to work on software product lines Improving evaluations of fuzz testing tools His recent publications demonstrate a strong focus on addressing challenges in configurable static analysis tools, with particular attention to nondeterministic behavior, configuration spaces, and automatic testing and debugging approaches. Mordahl's work bridges theoretical foundations with practical applications, aiming to make software quality assurance tools more accessible and effective for developers. Dr. Mordahl has received several prestigious awards for his work: NSF Graduate Research Fellowship Awardee (2020) Eugene McDermott Graduate Research Fellowship Awardee (2020) ICSE 2019 Student Research Competition Winner Dr. Mordahl is actively involved in mentoring and seeks students interested in software engineering research. He has served on numerous program committees for top software engineering conferences including ICSE, ASE, ISSTA, and PLDI. His service to the academic community extends to artifact evaluation committees, demonstrating his commitment to research reproducibility and rigor.

Stefan Wagnerمشاهده پروفایل

استاد

• Software Quality
• AI-Supported Software Engineering
• Empirical Studies
• +۳ مورد دیگر

Stefan Wagner is a full professor of software engineering at the Technical University of Munich (TUM), where he leads the Chair of Software Engineering within the Informatics Heilbronn 3 department. He earned his PhD in computer science from TUM and has established himself as a leading researcher in software engineering with a unique interdisciplinary background combining computer science and psychology. Dr. Wagner's research spans multiple areas of software engineering including software quality, human factors, AI-based software engineering, automotive software, and empirical studies. His work often bridges theoretical foundations with practical applications, particularly in the automotive domain and AI-assisted development. He has published over 130 peer-reviewed scientific articles and authored the book 'Software Product Quality Control.' His recent publications demonstrate a growing focus on AI integration in software engineering, with particular attention to large language models, empirical validation of AI-assisted development practices, and the human aspects of these emerging technologies. There's also a strong thread of research on automotive software systems, technical debt, and software quality measurement. 2022 Class of IEEE Computer Society Distinguished Contributors Senior member of IEEE and ACM Best Full Paper Award, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement 2020 Best Paper Award, EAI International Conference on Cognitive Computing and Cyber Physical Systems 2020 Keynote at the International Conference on Software Quality 2020 Google Research Award 2009 Dr. Wagner actively mentors students and early-career researchers, with several frequent co-authors on his publications likely representing his advisees. His research has been supported by various funding sources enabling his work on automotive software, AI in software engineering, and empirical studies. He serves on the editorial boards of IEEE Software, Empirical Software Engineering, and the Journal of Systems and Software, contributing significantly to the academic community. His research group appears to focus on several key areas including AI-assisted software development, automotive software systems, and empirical software engineering methods. The group maintains active collaborations with industry partners, particularly in the automotive sector, and engages in interdisciplinary research bridging computer science with psychology and human factors.

Yutian Tangمشاهده پروفایل

استادیار

• AI+SE
• Large-language Model+SE
• Program Analysis
• +۵ مورد دیگر

Dr. Yutian Tang serves as an Assistant Professor (UK Lecturer) and Principal Investigator at the School of Computing Science, University of Glasgow, where he supervises PhD students and leads research in AI-driven software engineering. His academic journey includes a PhD from The Hong Kong Polytechnic University's Department of Computing. His research spans AI+SE integration , particularly focusing on Large Language Models for program analysis, software testing, and Android security. Key areas include: LLM-assisted vulnerability detection and repair Empirical studies of real-world software systems Privacy protection mechanisms Configuration compatibility in mobile applications Smart contract security optimization His publication portfolio shows a clear trajectory toward AI-augmented software engineering , with recent work demonstrating how LLMs can enhance taint analysis, binary code similarity detection, and test generation. This evolution reflects the field's broader shift toward AI integration while maintaining rigorous empirical validation. Award highlights include: Best Industry Paper Award at ISSRE'18 Elevation to IEEE Senior Member (2024) Three Android OS defects confirmed by Google Security Team As an active researcher and community contributor, Tang serves on 40+ program committees including PLDI, ICSE, and FSE. His work receives funding from National Natural Science Foundation of China, Shanghai Science Commission, OpenAI, and Google. Current projects focus on automated bug localization and LLM-based testing frameworks, with recent grants from OpenAI Cybersecurity and Google Cloud programs. He leads research groups investigating Android security and AI-assisted program analysis, collaborating with institutions like Lund University.

Alicia García Holgadoمشاهده پروفایل

دانشیار

• Knowledge Management
• Educational Technology
• Digital Ecosystems
• +۵ مورد دیگر

Alicia García-Holgado is an Associate Professor in the Department of Computer Science and Automation at the University of Salamanca. She is a member of the GRIAL Research Group, where she leads the "Social Responsibility and Inclusion" research line, and also affiliated with the Salamanca Biomedical Research Institute and the University Institute of Educational Sciences. Her educational background includes a Degree in Computer Sciences (2011), M.Sc. in Intelligent Systems (2013), and a PhD in Education in the Knowledge Society (2018, Cum Laude), all from the University of Salamanca. Dr. García-Holgado's research focuses on developing technological ecosystems for knowledge and learning management in diverse contexts, with particular emphasis on promoting diversity and inclusion in STEM fields. She has organized numerous international activities aimed at reducing the gender gap in STEM, including the "Women Researchers' Breakfast at the University of Salamanca," which received the Gutenberg Award for scientific dissemination in 2020. Her work bridges computer science, education, and social responsibility, with practical applications in academic, professional, and public administration contexts. Her publication record shows a strong focus on educational technology, knowledge management systems, and informal learning recognition, with over 170 international publications in scientific journals and conferences. Her research spans multiple disciplines including computer science, education, and human-computer interaction, with applications in academic, professional, and public administration contexts. Gutenberg Award for scientific dissemination 2020 by CoxmoCaixa Dr. García-Holgado has participated in over 50 research projects including MIH, VALS, WYRED (H2020), and W-STEM. She currently coordinates the Erasmus+ SPADATAS project focused on security and privacy in academic data management. She serves on the Negotiating Committee of the II Equality Plan of the University of Salamanca and is active in several professional organizations including IEEE, ACM, and AMIT. She is Associate Editor of the IEEE Revista Iberoamericana de Tecnologías del Aprendizaje and the Revista Facultad de Ingeniería. As a member of the GRIAL Research Group, she contributes to the group's work on interactive systems for learning, educational technologies, and strategic knowledge management, while leading the "Social Responsibility and Inclusion" research line that focuses on gender equity in STEM fields.

• Software Engineering
• Machine Learning
• Information Retrieval
• +۳ مورد دیگر

Ana Cristina Marcén Terraza serves as Professor and Director of the Artificial Intelligence degree at the University of San Jorge's School of Architecture and Technology. She teaches core courses across Computer Engineering, Video Game Design and Development, and Bioinformatics programs including Information Systems, Operating Systems Administration, and Human-Computer Interaction. Education: Doctorate in Computer Engineering from Polytechnic University of Valencia (Thesis: Fragment recovery in models through machine learning techniques) Research Focus: Her work centers on applying Machine Learning to solve critical challenges in Software Engineering , particularly for information retrieval systems, model-driven development frameworks, and automated software maintenance processes. This research bridges artificial intelligence with practical software development methodologies. Research Leadership: Actively leads the National Project "ALPS" (Intelligent Evolutionary Assistants for Software Product Lines) and National Project "DataME" (Model-Driven Software Production for Big Data Applications). Previously contributed to the International Project "REVaMP2" (Round-trip Engineering and Variability Management). Research Affiliation: Member of "Software Variability for Internet of Things" Research Group Publication Record: Author of multiple high-impact publications in premier journals including Information & Software Technology (IST), Journal of Systems and Software (JSS), and Software and Systems Modeling (SoSyM).

Stephen P. Johnstonمشاهده پروفایل

استاد

• Polymer Processing
• Injection Molding
• Process Control
• +۴ مورد دیگر

Stephen P. Johnston is a Professor in the Department of Plastics Engineering at the University of Massachusetts Lowell's Francis College of Engineering. He holds a B.S. in Plastics Engineering Technology from Pennsylvania State University, an M.S. in Plastics Engineering (2005), and a Ph.D. in Plastics Engineering (2007) from UMass Lowell. His industrial experience includes positions at Moldflow Corp., Bausch & Lomb, and Lord Corp. Dr. Johnston's research focuses on polymer processing and product design with specialization in: Injection molding process monitoring, control, and development Computer-aided engineering for part and mold design Process instrumentation and finite element analysis Industrial applications of polymer processing technologies His publication portfolio demonstrates consistent focus on injection molding optimization, sensor-based process control, and polymer characterization. Recent work explores capillary rheometry, microstructured surfaces, and thermally conductive polymers. Significant Awards: Teaching Excellence Awards (2014, 2011) Faculty Member of the Year (2013) Outstanding Paper Award from SPE (2011) Multiple graduate research awards (2004-2006) He leads industrially-funded research supported by over 25 companies, resulting in 40+ publications, a book chapter, and three patents. Johnston advises the Student Chapter of the Society of Plastics Engineers and teaches courses including Mold Design Engineering, Product Design, and Introduction to Engineering.