Find Academic Supervisors

Cristina LopesView profile

Professor

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +5 more

Cristina Lopes is a Professor of Informatics at the Donald Bren School of Information and Computer Sciences , University of California, Irvine. She holds administrative roles including Director of the Master of Software Engineering Program and former Director of the Institute for Software Research . Her research focuses on software engineering, programming languages, and distributed systems, with contributions to open-source projects like OpenSimulator and AspectJ. She has authored the influential book Exercises in Programming Style . Education: PhD from Northeastern University, MS/BS from Instituto Superior Técnico (Portugal). Awards include IEEE Fellow (2019), ECOOP Test of Time Award (2017), and ACM Distinguished Scientist (2011). She co-founded a virtual reality company for urban redevelopment and leads NSF-funded projects, including the prestigious CAREER Award. Research Interests: Large-scale software systems, aspect-oriented programming, code clone detection, and applying AI to programming challenges. Her work bridges theory and practice, with applications in urban simulation and healthcare systems. Awards and Grants: Over 15 awards including national and international distinctions. Grants focus on scalable software tools and environmental sustainability in computing. Labs/Teams: Leads the Software Engineering Research Group and collaborates with industry partners on open-source infrastructure and AI-driven development tools.

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +3 more

Crista Lopes is a Professor in the Department of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences. She serves as Director of the Master of Software Engineering Program and previously led the Institute for Software Research. Her research focuses on software engineering, programming languages, and distributed virtual environments. Dr. Lopes holds editorial roles as Editor-in-Chief of The Art, Science, and Engineering of Programming and on the Advisory Board of PACMPL . She has received notable awards including IEEE Fellow (2019), ECOOP Test of Time Award (2017), and ACM Distinguished Scientist (2011). Her teaching spans courses like INF 212 Programming Languages II and INF 225 Information Retrieval . Recent research includes AI-assisted programming tools, code analysis frameworks like Sourcerer , and studies on climate-conscious conference practices. She actively mentors students in UCI’s Software Engineering doctoral program.

Peter DawyndtView profile

Professor

• Computational Biology
• Bioinformatics
• Computer Science
• +7 more

Peter Dawyndt is a Professor in the Department of Applied Mathematics, Computer Science and Statistics at Ghent University's Faculty of Sciences, where he heads the Computational Biology Lab. His research bridges computer science and life sciences through interdisciplinary work on computational applications for (meta)genomics, (meta)proteomics, and educational data mining. The lab actively develops the Unipept platform for metaproteomics biodiversity analysis and the Dodona platform for programming education, demonstrating dual expertise in biological data science and educational technology. His research interests encompass computational biology, bioinformatics, and educational data mining with specific focus on metagenomics, metaproteomics, metatranscriptomics, and data visualization for life sciences applications, alongside learning analytics and educational technology for computer science education. The Unipept platform enables taxonomic analysis of metaproteome samples through tryptic peptide biomarkers, while the Dodona ecosystem includes tools like Dolos for plagiarism detection and Blink for Scratch debugging, all supporting active learning in coding education. Analysis of his 2023-2025 publications reveals two equally prominent research thrusts: advancement of bioinformatics tools (e.g., Unipept's expansion to non-tryptic peptides and metabolic pathway visualization) and innovation in educational technology (e.g., LLM applications for CS1 education and automated code review systems). This dual trajectory highlights his commitment to both fundamental biological discovery and transformative educational practices in computing. No scientific awards were documented in the provided source materials. While specific student advising details and grant information were not explicitly stated, his leadership of the Computational Biology Lab and extensive publication record suggest active mentorship of graduate students and researchers in developing computational tools for biological and educational applications. The Computational Biology Lab operates as an integrated team developing the Unipept and Dodona platform ecosystems. Current projects include enhancing metaproteomics analysis capabilities through missed cleavage support and expanding educational tools for plagiarism detection and virtual co-teaching, reflecting the lab's commitment to open-source software development at the computer science-life sciences education interface.

Michalis FamelisView profile

Assistant Professor

• Software analysis
• Software design
• Empirical software engineering
• +3 more

Michalis Famelis is an Assistant Professor at the Department of Computer Science and Operations Research , affiliated with the Faculty of Arts and Sciences at Université de Montréal . He leads research in the GEODES Software Engineering Research Group , focusing on formal yet practical methods for software development. His work integrates formal verification, model-driven engineering, and empirical methods to address challenges in software design and uncertainty management. Educated at the University of Toronto (PhD 2016, MSc 2010) and the National Technical University of Athens (DiplEng 2008), he completed a postdoctoral fellowship at the University of British Columbia . He teaches courses such as IFT1025 Programming 2 and IFT6755 Software Analysis . His research projects include a Wellcome Trust-funded platform for climate-sensitive disease modeling and CRSNG grants for formal software design support. He has supervised 6 master’s students, focusing on topics like design uncertainty, API usage verification, and software product lines. Notable collaborations involve Climate-Sensitive Infectious Disease Modelling and Formal Support for Software Design . His work emphasizes improving developer workflows through tool development and empirical studies.

Torstein J. F. StrømmeView profile

Associate Professor

• Computer Science Education
• Informatics Didactics
• Algorithmic Thinking
• +7 more

Torstein J. F. Strømme is an Associate Professor in the Department of Informatics at the University of Bergen, Norway. His academic work is centered within the Didactics research group, focusing on computer science education and pedagogical methods. Position: Associate Professor Department: Department of Informatics University: University of Bergen Email: torstein.stromme@uib.no Office: HIB - Thormøhlens gate 55, Room 3101 / Høyteknologisenteret, Office 404P2 Location: Bergen, Norway He earned his PhD (2015–2020) and MSc (2013–2015) in Computer Science from the University of Bergen, and a BSc in Electrical and Computer Engineering from Carnegie Mellon University (2009–2013). Prior to his current role, he worked as a Senior Software Engineer at Vizrt (2020–2021) and as an Assistant Professor at UiB (2018–2019). His research is dedicated to computer science education and algorithmic thinking , with a strong emphasis on teaching practices, student motivation, and curriculum development. He is deeply involved in informatics didactics , exploring how programming is taught and learned, particularly at the introductory level. His interests extend to making theoretical computer science accessible to K-12 students and integrating computing into interdisciplinary domains like medicine and law. Although no specific publications are listed in the provided text, his teaching portfolio and thesis topics suggest a focus on algorithms, computational efficiency, and educational software tools. He has contributed to educational resources such as a simple Python graphics library for beginners and is active in competitive programming communities (NIO, NCPC). He is open to supervising master's theses on topics related to CS education, algorithmic thinking, and interdisciplinary applications of computing. Torstein also offers minor consulting services, leveraging his expertise as an expert witness in source code plagiarism cases and in data science application development.

• Compiler Design
• Programming Languages
• Software Engineering

Jack W. Davidson is a Professor at the University of Virginia renowned for transformative leadership in ACM's publications ecosystem. He served as Co-Chair of the ACM Publications Board (2010-2021) and founding chair of the ACM Digital Library Board (2021-present), driving digital library revitalization, open-access transitions, and inclusive publishing policies including the groundbreaking author name change policy. His core research expertise lies in compiler design and implementation, recognized by his 2008 ACM Fellowship. This work underpins critical advancements in programming language theory and software engineering infrastructure, enabling efficient code translation and optimization across computing systems. Major honors include: ACM Fellow (2008) for contributions to compiler design and implementation Outstanding Contribution to ACM Award (2023) for publications program leadership Professor Davidson pioneered standards for research artifact evaluation and replication studies while expanding ACM's portfolio with interdisciplinary journals like the ACM/IMS Journal of Data Science. His advocacy addressed complex publication ethics issues including plagiarism, compromised reviewing, and bullying. Information regarding student advising and grant funding was not specified in available sources.

Massimiliano Di PentaView profile

Professor

• Software Evolution
• Software Analytics
• DevOps
• +5 more

Massimiliano Di Penta is a Full Professor at the University of Sannio, Italy, working within the Department of Engineering. He has established himself as a prominent researcher in software engineering with extensive contributions to software evolution, software analytics, DevOps, and software engineering with/for AI. His academic leadership is evident through his roles as program co-chair of major conferences including ICSE 2023 and ESEC/FSE 2021, and his editorial positions as associate editor-in-chief of IEEE Transactions on Software Engineering and co-editor-in-chief of the Journal of Software: Evolution and Processes. His research interests span multiple critical areas in modern software engineering: Software evolution and maintenance Software analytics and mining software repositories DevOps practices and tooling Integration of AI in software engineering processes Technical debt management Software testing and quality assurance Analysis of his recent publications (2024-2025) reveals a strong focus on the intersection of AI and software engineering, particularly examining how large language models impact development practices, the challenges in software supply chain security through Software Bills of Materials (SBOM), and the application of AI techniques to traditional software engineering problems. His work demonstrates a consistent emphasis on empirical validation and practical applicability to real-world development scenarios. Notable scientific recognition includes: Four ACM SIGSOFT Distinguished Paper awards Multiple distinguished reviewer awards Extensive service on program committees for over 100 conferences Professor Di Penta has advised numerous students and has been instrumental in shaping research directions through his editorial work and conference leadership. His lab and research team at the University of Sannio focus on empirical studies of software development practices with particular attention to modern challenges in AI-assisted development and software supply chain security. His future work appears to be increasingly focused on the implications of generative AI for software engineering practices and the evolving landscape of software supply chain management.

• Text Mining
• Natural Language Processing
• Machine Learning
• +4 more

Roles & Affiliations: Efstathios Stamatatos is a Professor in the Department of Information and Communication Systems Engineering at the University of the Aegean, Greece. He has held academic roles since 2004, including adjunct professorships and postdoctoral research positions. His primary affiliation is the University of the Aegean, where he directs the Artificial Intelligence Lab and organizes international evaluation campaigns (PAN/CLEF). Education: Earned his Diploma (1994) and PhD (2000) in Electrical and Computer Engineering from the University of Patras. He conducted postdoctoral research at the Austrian Research Institute for Artificial Intelligence (2001-2002) and held visiting roles at institutions like the Polytechnic University of Madrid and Lehigh University. Research Interests: Focuses on text mining, natural language processing, machine learning, and authorship analysis. Key areas include plagiarism detection, author profiling, cross-domain attribution, and forensic linguistics. His work bridges computational methods with applications in digital forensics and humanities. Publications & Contributions: Over 100 peer-reviewed articles in journals like Journal of the Association for Information Science and Technology and conference proceedings (ECIR, ACL, CICLing). His research emphasizes reproducibility and has led to open-source codebases for authorship analysis tools. Awards & Activities: Editorial board member of Language Resources and Evaluation and Information Processing and Management . Organizes PAN competitions on authorship forensics and serves on program committees for top conferences (ACL, SIGIR, ECIR). Active in promoting ethical AI through initiatives like text detoxification and generative AI analysis.

Jie ZhaoView profile

Assistant Professor

• Computer Vision
• Artificial Intelligence
• Big Data Analytics
• +4 more

Jie Zhao is an Assistant Professor of Computer Science & Software Engineering at the School of Engineering, Pennsylvania State University. His research bridges artificial intelligence, big data analytics, and energy systems, with a focus on computer vision, machine learning, and sustainable energy solutions. Research Interests include: Computer Vision and AI applications Wind power ramp forecasting and renewable energy analytics Machine learning for perovskite solar cells and edge-AI platforms Community solar credit-sharing frameworks Code plagiarism detection and educational data mining Recent Publications highlight interdisciplinary work in wind energy prediction, object detection algorithms, and developer satisfaction studies, reflecting a blend of computer science and energy systems research. Awards & Grants : 2024: IEE Seed Grant for interdisciplinary energy projects Collaborative Projects include integrating conductive atomic force microscopy (c-AFM) with machine learning to analyze perovskite solar cell instability, and co-organizing workshops on enterprise modeling and FAIR data management.

• Software Engineering
• Data Engineering and Data Science
• Artificial Intelligence
• +4 more

Assoc Prof Caslon Chua is an Associate Professor and Department Chair of Computing Technologies at the School of Science, Computing and Emerging Technologies, Swinburne University. He specializes in software engineering, data science, artificial intelligence, and human-centered computing. His research focuses on federated learning, cybersecurity, medical imaging, education technology, and sustainable energy systems. Prof Chua has led numerous grants, including projects on CTF-based cybersecurity platforms, smart energy systems, and AI-driven healthcare solutions. He actively supervises doctoral and master’s students in areas like AI ethics, medical diagnostics, and smart energy. His grants span collaborations with organizations like the Australian Council of Deans of ICT, Victorian Chamber of Commerce, and Commonwealth Scientific and Industrial Research Organisation (CSIRO). Recent grants include developing cybersecurity platforms for education and improving evacuation modeling in the Philippines. Prof Chua’s work emphasizes ethical AI integration in education and healthcare, addressing challenges like data imbalance and model drift in federated learning systems. He has published over 80 papers in top journals and conferences, focusing on edge-assisted learning systems, colorectal polyp detection, and AI-driven insurance predictions. His teaching activities include courses on AI ethics, cybersecurity, and data analytics. Prof Chua’s contributions bridge academia and industry, addressing real-world challenges in computing and emerging technologies.

David CooperView profile

Senior Lecturer

• Software Engineering
• Educational Technology
• Collusion Detection
• +3 more

Dr. David Cooper is a Senior Lecturer in the School of Elec Eng, Comp and Math Sci (EECMS) at Curtin University, part of the Faculty of Science and Engineering. He holds a role in the Office of the Provost and is based at Curtin Perth Campus. His expertise lies in software engineering education and development of tools for academic purposes. Research Interests: Cooper focuses on software engineering pedagogy, automated assessment systems (e.g., TokenDiff for plagiarism detection), educational technology, and developer cognition. His work emphasizes practical tools like Textema for academic content generation and automated lab testing systems. Publications: His research spans software inspection techniques, cognitive aspects of collaborative coding, and educational methodologies in computing education. Key areas include Bloom's Taxonomy applications in software quality analysis and developer comprehension studies. Labs/Tools: Developed TokenDiff (source code collusion detector), Textema (LaTeX academic toolset), and automated feedback systems for coding assignments. These tools reflect his commitment to enhancing both teaching practices and software engineering processes.

Essam EliwaView profile

Senior Lecturer

• Software Engineering
• Web Science
• Information Retrieval
• +4 more

Dr. Essam Eliwa is a Senior Lecturer in the Department of Computing at Sheffield Hallam University, affiliated with the School of Computing and Digital Technologies and the Industry and Innovation Research Institute. He holds a PhD and MSc in Computer Science from the University of Nottingham. His career spans teaching, software development, and clinical trials programming. He previously served as an Assistant Professor in Egypt at Misr International University, Ain Shams University, and the Arab Academy. His research focuses on Web Science (information retrieval, automation frameworks like Web2Sh), software engineering, automated assessment systems, and augmented reality in education. Key contributions include the WSh scripting language and Evalseer, a gamified assessment tool. He has also explored deep learning for mental health diagnosis and AR applications in automotive industries. Teaching expertise includes software engineering, web/mobile programming, and software architecture. Advising and project supervision are central to his pedagogy. His work bridges academic research and practical software solutions, emphasizing innovation in education and healthcare.

Barbara CutlerView profile

Associate Professor

• Computer Graphics
• Geometry Processing
• Visualization
• +3 more

Barbara Cutler is an Associate Professor in the Computer Science Department at Rensselaer Polytechnic Institute (RPI), with an affiliation to EMPAC. She holds a Ph.D. and served as a Post-Doctoral Lecturer at MIT in Electrical Engineering and Computer Science, focusing on computer graphics and visualization within the CSAIL lab. Her research spans computer graphics, geometry processing, architectural design tools, and educational technology, particularly in autograding systems like Submitty and plagiarism detection (Lichen). She has contributed to open-source platforms, container-based grading solutions, and policies to reduce academic stress and misconduct. Education Background: Ph.D. and Postdoc at MIT (EECS). Research Interests: Combining computational techniques with real-world applications in architecture, visualization, and education. Key areas include erosion modeling, tangible user interfaces, and collaborative infrastructure restoration simulations. Her work bridges theory and practice through tools like Submitty for scalable programming assignment evaluation. Grants & Projects: Developed Submitty, a widely used autograding platform. Authored over 50 publications on autograding systems, plagiarism detection, and computer graphics. Collaborated across institutions on H/FOSS curriculum integration and late-day policy studies. Labs & Teams: Affiliated with RPI’s Computer Science Department and EMPAC. Active in the Submitty development community and interdisciplinary projects involving architecture and engineering.

Alex AikenView profile

Professor

• Programming Languages
• Compiler Construction
• Parallel Computing
• +2 more

Alex Aiken is the Alcatel-Lucent Professor of Computer Science at Stanford University and serves as the Computer Science Division Director at SLAC. He has been a faculty member at Stanford since 2003, after previously serving as a Professor in the EECS department at UC Berkeley (1993-2003) and as a Research Staff Member at IBM Almaden Research Center (1988-1993). Dr. Aiken received his Bachelors degree in Computer Science and Music from Bowling Green State University in 1983 and his Ph.D. from Cornell University in 1988. He previously served as chair of the Stanford Computer Science Department. Alex Aiken's research focuses primarily on programming languages, compilers, and parallel computing systems. He is renowned for his work on the Legion programming system for heterogeneous parallel machines, the FlexFlow system for deep learning parallelization, and the development of Moss, a widely-used plagiarism detection system. His research spans both theoretical foundations and practical implementations, with a strong emphasis on translating research into usable software tools. His work has significant applications in high-performance computing, software analysis, and compiler technology. His recent publications reflect a continued focus on parallel and distributed systems, with increasing attention to the intersection of programming systems and machine learning. The 15 most recent articles demonstrate his leadership in task-based programming models, verification techniques, and the application of AI to programming systems. His work spans from low-level GPU optimizations to high-level language design and verification. ACM Fellow Recipient of ACM SIGPLAN's Programming Languages Achievement Award Phi Beta Kappa's Teaching Award Professor Aiken has advised numerous Ph.D. students throughout his career, with eight current advisees including Benjamin Driscoll, Qiantan Hong, and Rupanshu Soi. His research group has received substantial funding for projects related to parallel programming systems, compiler technology, and software analysis tools. The group maintains several active open-source projects including Legion, FlexFlow, and Moss. Aiken leads the Legion research group, which focuses on developing programming models and runtime systems for heterogeneous and distributed parallel machines. The group has made significant contributions to the field of task-based parallelism and has developed several widely-used software systems that bridge the gap between theoretical research and practical implementation.

Paul CloughView profile

Professor

• Information Retrieval
• Natural Language Processing
• Multilingual Search
• +4 more

Professor Paul Clough is a faculty member at the University of Sheffield, affiliated with the School of Information, Journalism and Communication. He holds a BEng from the University of York and a PhD from the University of Sheffield. His academic career spans roles from Research Assistant to his current position as Professor of Search and Analytics, leading the Information Retrieval research group. He has coordinated major initiatives like the MSc Data Science program and contributed to international evaluation campaigns such as CLEF, TREC, and FIRE. Clough's research focuses on information retrieval, natural language processing, and applications in cultural heritage and healthcare. Notable contributions include developing evaluation resources, exploring multilingual search, and advancing techniques for plagiarism detection and user-centric information systems. His work bridges technical innovation with user needs, emphasizing practical applications in digital libraries and healthcare information systems. He has authored over 100 peer-reviewed articles, co-authored books including Geographic Information Retrieval , and led projects analyzing search logs and user interactions. His teaching spans modules on information retrieval, database design, and digital multimedia, with a focus on preparing students for modern data and information challenges.