Find Academic Supervisors

Liia ButlerView profile

Teaching Professor

• Computer Science Education
• Software Engineering Education
• Debugging Education
• +3 more

Liia Butler is a Teaching Professor at the University of Minnesota specializing in Computer Science Education. Previously, she completed her PhD in Computer Science at the University of Illinois Urbana-Champaign under Professor Geoffrey Herman's advisement, focusing on debugging education and collaborative learning in programming contexts. Her research bridges software engineering practices with pedagogical innovation to improve computer science instruction. Educational background: PhD in Computer Science (completed), University of Illinois Urbana-Champaign MS in Computer Science, University of Illinois Urbana-Champaign (co-advised by Tao Xie and Geoffrey Challen) BS in Computer Science with distinction, University of Kansas (transitioned from Film and German double-major) Her research centers on transforming programming education through explicit debugging instruction, collaborative learning structures, and motivation-focused assessment design. Butler investigates how to convert intimidating coding challenges into productive learning experiences, particularly for students without prior computing exposure. Her work examines structured role assignment in group work, autograding systems that incentivize quality submissions, and data-driven approaches to understanding student problem-solving patterns in introductory programming. Analysis of her publication record reveals consistent focus on three interconnected themes: (1) developing observation protocols for cooperative learning activities, (2) designing assessment mechanisms that motivate quality coding practices, and (3) applying software engineering techniques to educational contexts. Her research employs mixed methods including classroom observations, student solution analysis, and tool development, primarily targeting introductory programming courses where debugging skills are critically underemphasized. Scientific Awards: No scientific awards mentioned in source materials Butler has mentored 6 undergraduate students and accumulated 16 semesters of teaching experience across 7 courses. Her instructional roles range from undergraduate TA for programming fundamentals to Head TA positions for advanced compilers courses and teaching assistant training programs. She emphasizes creating inclusive learning environments where students discover programming's creative potential, drawing from her own transformative experience switching to computer science without prior background.

• Virtual Reality
• Computer Vision
• Human-Computer Interaction
• +4 more

Joe K. Kearney is a Professor in the Department of Computer Science at the University of Iowa and the University of Minnesota. His career spans over three decades, focusing on virtual reality, computer vision, and human-computer interaction research. Key affiliations: University of Iowa (Iowa City, IA, USA), University of Minnesota (Minneapolis, MN, USA) Research domains: Virtual environments, perception-action coupling, motion capture systems, pedestrian behavior simulation Research trends show sustained contributions to immersive visualization , autonomous navigation , and human factors in virtual reality . His 2014-2025 work explores AR-based pedestrian safety systems, while earlier studies (1986-2006) established foundational frameworks for virtual environment simulation and optical flow analysis. Long-term collaborations with Jodie M. Plumert (1986-2021), James F. Cremer (1986-2009), and Pooya Rahimian (2015-2017) demonstrate consistent team research in VR cognition and autonomous systems.

Ayşe Tosun KühnView profile

Associate Professor

• Software Engineering
• Software Quality
• Defect Prediction
• +9 more

Ayşe Tosun Kühn is an Associate Professor in the Department of Computer Engineering at Istanbul Technical University (ITU), where she also serves in administrative roles such as Deputy Dean and Management Board Member of the ITU Artificial Intelligence and Data Science Application and Research Center. She earned her Ph.D. in Computer Engineering from Boğaziçi University and has held academic positions at Sabancı University and the University of Oulu. Her research lies at the intersection of software engineering, empirical methods, and data science, with a focus on software quality, defect prediction, technical debt, vulnerability analysis, and test-driven development. She leads numerous funded research projects, including those supported by TÜBİTAK and industry collaborations, applying machine learning and reinforcement learning to software engineering challenges. Her recent publications reflect a strong trend in applying advanced machine learning techniques—particularly deep learning and reinforcement learning—to problems in software analytics, developer behavior modeling, and delivery optimization. She has made significant contributions to empirical studies on test-driven development, defect prediction models, and vulnerability detection in code. Her work is frequently published in high-impact journals such as IEEE Transactions on Software Engineering, Empirical Software Engineering, and Journal of Systems and Software. She has served as a guest editor and editorial board member for the Turkish Journal of Electrical Engineering and Computer Sciences , and has contributed book chapters on data science in software engineering. Her research has been cited over 1,700 times, with an h-index of 23. Scientific Awards: None explicitly mentioned. She advises several graduate students and has collaborated extensively with researchers in Turkey and internationally. She has also contributed to industry applications through projects on software measurement, defect prediction, and AI-based analytics. She is actively involved in organizing and contributing to major software engineering conferences and workshops. She is a key member of ITU’s AI and Data Science initiatives, contributing to both academic research and practical implementations in software engineering.

Wei ChenView profile

Assistant Professor

• Empirical Financial Accounting
• Financial Reporting
• Disclosure Practices
• +5 more

Dr. Wei Chen is an Assistant Professor of Accounting at the University of Connecticut . He holds a Ph.D. in Accounting from the University of Iowa and an MBA from Dartmouth’s Tuck School of Business. His research focuses on empirical financial accounting, with an emphasis on financial reporting standards, disclosure practices, and methodological innovations. Dr. Chen’s work bridges accounting theory with real-world applications in digital platforms and emerging markets. Education: Ph.D. in Accounting, University of Iowa MBA, Tuck School of Business at Dartmouth College Research Interests: Financial reporting mechanics and transparency Platform economics and digital marketplaces Impact of regulatory policies on business models Cryptocurrency and blockchain ecosystems Open-source software innovation dynamics Key Research Themes from Publications: Examines how exchange listings influence venture development in token-funded projects Investigates signaling mechanisms in health consultation platforms Assesses implications of recreational cannabis legalization on illicit drug markets Explores organizational structures under generative AI adoption Studies Airbnb’s role in regulatory challenges and market competition Professional Engagement: Active in academia-industry dialogues around platform governance and AI ethics. No listed awards to date. Collaborates with global institutions on digital economy research.

• Software Engineering
• Cybersecurity
• Test Case Prioritization
• +4 more

Dr. Alina Torbunova is a Researcher in the Department of Information Technology at Åbo Akademi University's Faculty of Natural Sciences and Engineering. Her work focuses on software engineering, cybersecurity education, and testing methodologies. Research Assistant, Faculty of Natural Sciences and Engineering Department of Information Technology Åbo Akademi University Research Interests: Integration of security concepts in programming education Test case prioritization algorithms (dynamic and static) Secure coding practices in industrial settings Development of security frameworks for software engineering Publication Trends: Recent work emphasizes security education in programming curricula (2025), systematic approaches to teaching security concepts (2024), and dynamic test case prioritization techniques (2024). Projects: FAST: Finnish Software Engineering Doctoral Research Network (Coordinator) Research Cybersecurity Training Cooperation Network (Project Associate)

David W. BinkleyView profile

Professor

• Software Engineering and Testing
• Program Slicing and Clustering
• Information Retrieval in Software Engineering
• +6 more

David W. Binkley is a Professor in the Department of Computer Science at Loyola University Maryland. His research focuses on Software Engineering and Testing Program Slicing and Clustering Information Retrieval Techniques in Software Engineering Safety-Critical Systems Code Clone Detection Recent work includes dynamic slicing of WebAssembly binaries and adaptive change recommendation systems using association rules. He has contributed extensively to empirical studies on dependence clusters, testability transformations, and observational slicing techniques. Key collaborations include institutions like Simula Research Laboratory (Norway) and NIST (National Institute of Standards and Technology). His publications span top-tier venues such as IEEE Transactions on Software Engineering, ACM TOPLAS, and ICSE.

Angelika PeerView profile

Professor

• Robotics
• Control Systems
• Human-Robot Interaction
• +15 more

Angelika Peer is a Full Professor in the Faculty of Engineering at the Free University of Bozen-Bolzano, Italy, a position she has held since November 2017. Previously, she served as a Full Professor at the Bristol Robotics Laboratory, University of the West of England, UK (2014–2017), and as a senior researcher and lecturer at the Technical University of Munich, Germany, where she was also a TUM-IAS Junior Fellow. Her academic base is firmly within engineering, particularly in intelligent and human-centered systems. Diploma in Electrical Engineering and Information Technology, Technical University of Munich, 2004 Doctor of Engineering, Technical University of Munich, 2008 Her research interests are centered on intelligent systems that bridge humans and machines. Key areas include robotics, control systems, human-robot interaction (HRI), emotion recognition through physiological signals, shared control, and intelligent manufacturing. She investigates how dynamic models and machine learning can improve safety, adaptability, and efficiency in human-machine collaboration. Her work spans both theoretical control design and practical applications in Industry 5.0, sustainable production, and assistive technologies. Her recent publications (2023–2025) reflect a strong trend toward data-driven and model-based intelligent systems. Topics include energy-based safety control in HRI, neural-network-based trajectory adaptation in powder compaction, emotion intensity estimation using NARX models and appraisal theory, and task prediction in digitalized shop floors using support vector regression. These works demonstrate expertise in integrating dynamic modeling, machine learning, and real-time control with applications in manufacturing and human-centered computing. Angelika Peer has advised PhD students including Ehtisham Ul Hasan and Isabel Francisca Sota Machado Barradas. She is involved in research initiatives such as the Human-centered Intelligent Systems (HCIS) macro area at her university, promoting interdisciplinary work at the intersection of computer science, engineering, and human factors. Her research is supported by collaborations and publications in high-impact journals and conferences, with a strong emphasis on open access and peer-reviewed dissemination.

Michele BUGLIESIView profile

Professor

• Computer Security
• Web Security
• Formal Methods
• +4 more

Michele Bugliesi is a Full Professor of Computer Science at Ca' Foscari University of Venice, where he is affiliated with the Department of Environmental Sciences, Computer Science and Statistics. His research spans theoretical computer science with a strong emphasis on practical security applications in web technologies and distributed systems. Professor Bugliesi's primary research interests focus on computer security, particularly web security, formal methods for security analysis, programming languages, and blockchain technologies. His work combines theoretical foundations with practical implementations, addressing critical security challenges in modern computing environments. He has made significant contributions to understanding and preventing session hijacking attacks, developing content security policies, and analyzing smart contract security. Analysis of Professor Bugliesi's recent publications (2016-2025) reveals a clear evolution in his research focus. Initially centered on web security and formal verification methods, his work has expanded to include blockchain technologies, smart contracts, and more recently, the security implications of large language models. His publications consistently appear in top-tier computer security conferences and journals, demonstrating the high quality and impact of his research. Professor Bugliesi maintains an active research group and collaborates extensively with colleagues including Stefano Calzavara, Alvise Rabitti, and Sabina Rossi. His research has practical implications for improving the security of web applications, blockchain systems, and emerging AI technologies.

• Software Engineering
• Software Quality
• Code Smells
• +7 more

José Pereira dos Reis is an Assistant Professor in the Department of Information Science and Technology at ISCTE - University Institute of Lisbon, where he contributes to both teaching and research. He is also an Associate Researcher at ISTAR-Iscte, a research center focused on Information Sciences, Technologies, and Architecture. His work bridges software engineering with data science and human-centric development practices. His educational background includes a PhD in Information Science and Technology (2022), a Master’s in Computer Engineering (2008), and dual Bachelor’s degrees in Electrical Engineering and Electronic and Telecommunications Engineering from ISEL (1991, 1994). PhD in Information Science and Technology, ISCTE-University Institute of Lisbon, 2022 Master’s in Computer Engineering, FCT-UNL, 2008 Bachelor’s in Electrical Engineering - Systems and Communications, ISEL, 1994 Bachelor’s in Electronic and Telecommunications Engineering - Digital Systems, ISEL, 1991 His research interests center on Software Engineering , with a focus on Software Quality , Code Smells , and their detection through Machine Learning and collective intelligence . He explores Scientific Workflow Management Systems as tools for enabling non-programmers in data science, advocating for visual programming and parameterized templates to improve accessibility and reuse. His work also extends into Process Mining and Software Development Analytics , analyzing team efficiency and refactoring practices. The recent publications reflect a strong trend in empirical and systematic studies on code quality, visualization, and workflow systems. He frequently collaborates with researchers like F. Brito e Abreu and G. Figueiredo Carneiro, contributing to high-impact journals such as Archives of Computational Methods in Engineering and Empirical Software Engineering . His work combines technical rigor with human-centered design principles. He has been involved in research projects including: DataScience4NP : Exploring visual programming to enable non-programmers in data science using scientific workflow systems. SUSTENTURIS : Focused on sustainability and authenticity in tourism, developing tools for certification and marketing sustainable tourism products. José Pereira dos Reis supervises Master’s students, currently guiding two dissertations on Deteção de Code Smells and IDE Plugin for Metrics Collection from Java Code . He teaches courses such as Software Engineering , Software Architecture and Design , Algorithm Design and Analysis , and Object-Oriented Programming across undergraduate and graduate programs in Computer Engineering and related fields. He is affiliated with research platforms including Scopus, ORCID, Google Scholar, and ScienceVitae, and his work is widely cited across academic databases.

Kai-Hsiung ChangView profile

Professor

• Software Testing
• Software Comprehension and Visualization
• Software Complexity Metrics
• +7 more

Kai-Hsiung Chang is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. He has been a faculty member since 1986, progressing from Assistant to Associate Professor in 1991, and to full Professor in 1998. He served as Department Chair from 2006 to 2016 and was honored with the Alumni Professorship from 2004 to 2009. Ph.D., Electrical and Computer Engineering, University of Cincinnati, 1986 M.S., Electrical and Computer Engineering, University of Cincinnati, 1982 Diploma, Electrical Engineering, Taipei Institute of Technology, 1977 Dr. Chang's research focuses on software testing, software comprehension and visualization, complexity metrics, information assurance education, computer supported cooperative work (CSCW), and artificial intelligence in software engineering. His work integrates formal methods and usage profiles to enhance software quality and safety. He has led research sponsored by the National Science Foundation (NSF) and the Department of Defense (DoD), particularly in pervasive and mobile computing and information assurance education. His recent publications reflect a strong focus on software testing methodologies, formal specification-based validation, collaborative systems, and intelligent software tools. Themes include object-oriented testing, complexity measurement, CSCW, and AI-driven test generation, indicating a long-standing commitment to improving software reliability and development processes. Alumni Professorship, Auburn University (2004–2009) ACM Certificate of Appreciation for Outstanding Service (1997) IEEE Senior Member INFOSEC Professional Certification (2005) Multiple Outstanding Teaching Awards at Auburn University (1989, 1992, 1997) Summer Faculty Fellowship at NASA Marshall Space Flight Center (1995) Dr. Chang has advised over 50 graduate students, including numerous Ph.D. and Master’s candidates, many of whom now hold academic and industry positions. He has served on NSF and DHS fellowship review panels, contributed to ABET accreditation as a commissioner and program evaluator, and participated in the IEEE-Computer Society/ACM Curriculum Committee for Software Engineering. He also served as Vice President of the International Society of Applied Intelligence. He has led significant research initiatives, including NSF-sponsored REU programs in pervasive computing, and has been deeply involved in curriculum development and professional service. His lab and research group have focused on software quality, intelligent systems, and collaborative environments, fostering interdisciplinary work in software engineering and AI.

Xavier DevroeyView profile

Assistant Professor

• Software Engineering
• Test Automation
• Search-Based Testing
• +5 more

Xavier Devroey is an Assistant Professor of Software Engineering at the Faculty of Computer Science , University of Namur , where he co-leads the SNAIL Team . His research focuses on test automation for search-based and model-based software testing , test suite augmentation , DevOps , and variability-intensive systems . PhD in Computer Science (University of Namur, 2017) Master in Computer Science (University of Namur, 2010) Recent research highlights include: Automated Android safety/security audits (A3S3, 2025) REST API benchmarking infrastructure (2025) Energy consumption analysis through test execution (2025) Fuzzing approaches for Odoo integration testing (FuzzE, 2025) Scientific recognitions: 1st place Java Test Case Generation Tool Competition (2025) VAMOS 2024 Ten-Year Most Influential Paper SSBSE 2020 Best Paper Award ICST 2024 Distinguished Reviewer AST 2023 PC Reviewer Star He actively supervises PhD and master's students while organizing international conferences like ISSTA (2025) and Belgium-Netherlands Software Evolution Workshops (2024).

Simon WorthingtonView profile

Researcher

• Open Science
• Open Source Software
• Publishing Technology
• +3 more

Simon Worthington is a leading researcher in future publishing systems, focusing on free and open source technologies, economic models, and the politics of Open Science. He serves as Editor-in-Chief at Generation Research, an editorial platform for open scholarship under the Leibniz Association Research Alliance Open Science, and works in R&D at the Open Science Lab, TIB - German National Library of Science and Technology. Board Member of FORCE11 (2019-2022) Co-founder of Mute magazine (1994) Executive Member of LIBER Citizen Science Working Group (2019-2021) Co-founder of Open Climate Knowledge (2019-ongoing) His research emphasizes creating platform-independent, interoperable publications to democratize research access. Key areas include open access publishing, semantic web applications for climate science, decentralized web technologies for academia, and innovative software citation practices. He has contributed to projects like AGATE (European academies digital integration) and Hybrid Publishing Lab. Recent publications highlight intersections between Free and Open Source Software (FOSS) and Open Scholarship, climate science open knowledge platforms, and infrastructure remixing for citizen science. His work often challenges traditional publishing norms while developing practical open systems. Simon studied media art at the Slade School (UCL, UK) and CalArts (USA), bringing interdisciplinary perspectives to his academic roles. He maintains active involvement in editorial and community-driven research initiatives across Europe.

• Cyber Security
• Computer Science
• Software Engineering
• +5 more

Dr. Bryan Malone is an Associate Professor and Director of Cyber Security, Computer Science, and Data Analytics at the College of Adult and Graduate Studies, School of Business and Technology, Colorado Technical University. He brings together academic rigor and practical experience in technology and education leadership. His educational background includes: D.C.S. in Computer Science, Colorado Technical University M.Ed. in Secondary Education, Eastern New Mexico University B.B.A. in Computer Information Systems/Business Administration, Eastern New Mexico University Post Graduate Work in Online Instructional Technology, Texas Tech University Dr. Malone's research focuses on cyber security, software engineering, and the application of technology in business and educational environments. His expertise spans network protection, applied cyber technology, and the integration of online learning tools. He emphasizes the practical implementation of theoretical models in real-world business settings. His scholarly work, including a publication in IEEE Transactions on Reliability, centers on enhancing security practices in open-source software development. The research demonstrates trends in empirical analysis of security tactics, software reliability, and defensive programming patterns. Dr. Malone has presented at national conferences on topics such as online course design, internet-based teaching tools, and student satisfaction in web-based learning environments. These contributions highlight his commitment to advancing digital education and instructional technology. He has been involved in academic and professional presentations, including: "Two Different Approaches to Online Course Offerings," League for Innovation in Community Colleges, Chicago, 1999 "Online Training Tools for the Internet," Stop Surfing-Start Teaching National Conference, Myrtle Beach, 1999 "Web-based Student Satisfaction Survey," New Mexico Higher Education Assessment Conference, 1999 As Director, he leads academic programs in cyber security and data analytics, shaping curriculum and strategic direction in emerging technology fields. His work bridges academic theory with industry application, particularly in securing digital infrastructures and developing robust software systems.

• Software Engineering
• Agile Methodologies
• Teamwork in Software Development
• +3 more

Yngve Lindsjørn is an Associate Professor in the Department of Computer Science at Oslo Metropolitan University's Faculty of Technology, Art and Design. His research focuses on agile software development, teamwork quality, project success factors, and educational technology. Research Interests: Software Engineering, Agile Methodologies, Teamwork Dynamics, Technical Debt, and Educational Technology. Key Contributions: Co-authored studies on gender composition in agile teams, teamwork effectiveness models, and capstone course design. Recent publications analyze team composition in agile education, large-scale project challenges, and gender dynamics in software teams. His work appears in journals like Empirical Software Engineering and conference proceedings for XP and CHASE . Notable collaborations include researchers from the University of Oslo, Norwegian Computing Center, and IT didactic initiatives. He contributes to disseminating agile principles in software education and has co-authored reports on teamwork assessment frameworks.

Peter PopovView profile

Researcher

• Software Reliability
• System Dependability
• Software Fault-Tolerance
• +5 more

Peter Popov is a Reader at the Centre for Software Reliability (CSR) , City St George's, University of London , where he has been employed since 1997. He specializes in software dependability , fault tolerance , and stochastic modeling of critical infrastructures. Before his current position, he was an Associate Professor at the Bulgarian Academy of Sciences (1990-1997) and a Research Fellow at City St George's. Peter's academic journey began with a PhD in Computer Science from the Kiev National University of Technologies and Design (1989), following his BEng in Computer Engineering from the National Technical University of Ukraine (KPI, 1982). He has worked as a visiting scientist at renowned institutions including the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign , LAAS-CNRS in Toulouse, and Duke University . His research interests span Software reliability assessment System dependability Software fault-tolerance Performance evaluation Interdependencies of critical infrastructures He has contributed extensively to projects such as ReSIST , IRRIIS , DISPO , and AFTER , focusing on the dependability of composite systems and critical infrastructure resilience. Key publication trends reveal expertise in Stochastic modeling of autonomous vehicle safety Software diversity for fault tolerance Interdependency analysis in critical systems Bayesian reliability assessment Performance evaluation of distributed protocols Security implications in cyber-physical systems Peter has supervised several PhD students , including those researching autonomous vehicle resilience , safety assurance with ML components , and adaptable web services . His professional activities include serving on program committees for ISSRE , SAFECOMP , and EDCC conferences, as well as editorial contributions to CEUR Workshop Proceedings . He is proficient in Bulgarian , English , and Russian , with peer-review capabilities in all three languages.