Code Clones Professors and Supervisors | ApplySharif

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Katsuro InoueView profile

Professor

Osaka UniversityJapan

Katsuro Inoue is a Professor at Ritsumeikan University within the College of Information Science and Engineering. He holds a Dr. degree of Engineering from Osaka University (1984) and specializes in Software Engineering with a focus on Program Analysis , Code Clone Detection , Software Ecosystem Analysis , and Process Modeling . His work includes developing systems like CCFinder for code clone analysis and SPARS for software component significance ranking. Research Interests Program Analysis: Code Clone Analysis, Origin and Evolution Analysis, Software Ecosystems, Bug Detection, Analysis Tools and Algorithms Program Reuse: Code Search Engines, Program Archives, Searching Mechanisms Software Process: Process Modeling, Process Centered Environments, Process-Based Metrics, Quality Standards Key Publications Code Clone Analysis (2021), Library Dependency Updates (2018), Code Clone Tracking in Open Source (2012), Distributed Code Clone Detection (2007), Software Component Significance Ranking (2005), Compiler Garbage Collection (1991), Code History Tracking (2012) Professional Activities Program Committee Member in over 20 conferences (ICSE, IWPSE, PROFES) Editorial Board Member for IEEE Transactions on Software Engineering Co-Chair of multiple workshops (IWSC, IWPSE) Reviewer for SEC Journal Teaching Course: System Architect Course Developed course materials for Compiler Design and Language Processing Created exam problems and optimization examples for language processing courses

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JIANG LingxiaoView profile

Professor

Singapore Management UniversitySingapore

Professor Lingxiao Jiang is a full-time faculty member at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU) , where he serves as Director of the Centre for Research on Intelligent Software Engineering (RISE) . His research and teaching focus on software engineering , program analysis , code search & reuse , and deep learning of code to enhance software quality, development productivity, and security. PhD, University of California, Davis (2009) Professor Jiang's research explores context-aware software deep learning , code clone detection , and security & privacy through tools like DECKARD (code clone detection), EqMiner (functionally equivalent code), and SmartEmbed (smart contract security). His work leverages distributed computing , symbolic execution , and neural program models for large-scale code analysis. Recent publications highlight trends in deep learning-based code analysis , smart contract vulnerabilities , and automated program transformation . Key themes include code clone detection , semantic patches , and cross-language API mappings . Scientific Awards ACM SIGSOFT Impact Paper Award (2018) for scalable code clone detection As advisor, Professor Jiang has mentored 14 graduate students, including Lucia (Ph.D. 2014) , Shaowei Wang (Ph.D. 2015) , and current advisees in intelligent software engineering. He leads multiple grants on code mining , security of digital platforms , and AI systems governance . RISE Lab at SMU develops tools like MANDO (smart contract analysis), iTiger (issue title generation), and TreeCaps (code processing with capsule networks). The lab actively recruits researchers in software engineering and AI.

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Harutyun Ishkhanovich AvetisyanView profile

Professor

HSE UniversityRussia

Harutyun Ishkhanovich Avetisyan is a Professor and Head of the Basic Department "System Programming" at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2017 and brings 30 years of scientific and teaching experience to his role. Additionally, he serves as the Director of the Institute for System Programming of the Russian Academy of Sciences (ISP RAS), a position he has held since 2015. Avetisyan holds numerous prestigious academic distinctions, including being elected as an Academician of the Russian Academy of Sciences in 2019 and as a Corresponding Member in 2016. He earned his Doctor of Physical and Mathematical Sciences degree in 2012 and was awarded the academic title of Associate Professor in 2009. His educational background includes a specialty in "Applied Mathematics" from Yerevan State University (1993). His research focuses on three main areas: analysis and transformation of programs, software security, and parallel and distributed computing technologies. These interests are reflected in his extensive publication record and leadership in major research initiatives. His work bridges theoretical computer science with practical applications in cloud computing, secure data storage, and high-performance computing systems. Avetisyan's scholarly contributions demonstrate a consistent focus on system programming challenges, particularly in the areas of code analysis, optimization, and security. His recent publications indicate a growing interest in cloud computing paradigms, smart city infrastructure, and energy-efficient computing solutions. His research has significant implications for both academic theory and industrial applications in software development. Among his notable recognitions, Avetisyan was awarded the medal of the Order "For Merit to the Fatherland" 2nd degree in 2021 for his significant contributions to science and dedicated service. He also serves on the editorial boards of several prestigious journals including "Programming" (since 2015) and "Proceedings of the Institute for System Programming of the RAS" (since 2010). Throughout his career, Avetisyan has led and participated in numerous research grants funded by the Ministry of Education and the Russian Foundation for Basic Research. His professional trajectory shows steady progression from postgraduate studies (1997-2000) to research fellow (2000-2002), deputy director of ISP RAS (2002-2015), and ultimately director of the institute (2015-present). At HSE, Avetisyan teaches courses in parallel programming and mentor seminars for master's students in Software Engineering. His teaching philosophy emphasizes the integration of cutting-edge research with practical software development skills, preparing students for careers at the forefront of computer science.

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Gail KaiserView profile

Professor

Columbia UniversityUnited States

Dr. Gail Kaiser is a Professor of Computer Science at Columbia University, where she has served for 40 years. She directs the Programming Systems Lab (PSL) and is affiliated with the Software Systems Lab (SSL). Her research focuses on software systems, program analysis, testing, security, and AI-driven software engineering. She earned her PhD from Carnegie Mellon University and a BS from MIT. Education: PhD in Computer Science, Carnegie Mellon University (1985) MS in Computer Science, Carnegie Mellon University (1980) BS in Computer Science and Engineering, MIT (1979) Research & Teaching: Dr. Kaiser teaches COMS W4156 (Advanced Software Engineering) and COMS E6156 (Topics in Software Engineering). Her work spans metamorphic testing for machine learning, secure computing, and AI in SE. Notable contributions include pioneering metamorphic testing for classifiers and secure containers research. Awards & Grants: 2025 Distinguished Journal Award (ICST) NSF grants totaling over $2M for secure computing and software assurance ACM SIGSOFT Distinguished Paper Awards (2023, 2014) Labs & Collaborations: Her labs (PSL and SSL) drive innovation in program analysis and security. Collaborations include DARPA, NIH, and industry partners like IBM and Microsoft.

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Debajyoti MondalView profile

Associate Professor

University of SaskatchewanCanada

Dr. Debajyoti Mondal is an Associate Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on algorithms, network visualization, computational geometry, and visual analytics. He holds a PhD from the University of Manitoba and has held postdoctoral positions at the University of Waterloo and Microsoft Research. Mondal's work spans interdisciplinary applications, including collaborations with Saskatoon Transit and academic medicine. He has authored over 100 peer-reviewed publications and secured grants such as NSERC Discovery, CFI, and Canada First Research Excellence grants. His awards include the 2023 New Scholar RSAW Award. Education: Ph.D. in Computer Science, University of Manitoba, 2016 MSc in Computer Science, University of Manitoba, 2012 BSc. Engg. in Computer Science, Bangladesh University of Engineering and Technology, 2009 Research Interests : Algorithms, graph drawing, computational geometry, visual analytics, and interdisciplinary applications in software engineering, transportation, and bioinformatics. His lab (VGA Lab) develops visualization systems for big data analysis. Key Contributions : Advanced theoretical foundations in computational geometry and graph drawing, developed practical visualization tools, and contributed to climate-related projects like Global Water Futures. Grants & Awards : NSERC Discovery Grant (2018-2024) CFI Grant (2021-2025) Microsoft Research Internship (2015-2016) New Scholar RSAW Award (2023) Labs/Teams : Leads the VGA Lab, collaborating with interdisciplinary teams on projects like Clone-World (software clone visualization) and SET-STAT-MAP (mixed data visualization).

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Chanchal K. RoyView profile

Professor

University of SaskatchewanCanada

Dr. Chanchal K. Roy is a Professor of Software Engineering/Computer Science at the University of Saskatchewan (USask), Canada, and Director of the NSERC CREATE SOAR program. He leads the Software Research Lab (SRLab) and is renowned for his work on code clone detection (NiCad tool) and software maintenance. His research spans software evolution, big data analytics, and quantum computing applications in software engineering. Dr. Roy holds a Ph.D. from Queen’s University, an M.Sc. from RWTH Aachen University, and a B.Sc. from Khulna University. Research interests include software clone detection, maintenance, and evolution, with emphasis on semantic analysis and cross-language clones. He has published over 240 papers (h-index 52) and attracted $6M+ in funding, including NSERC grants and CFI-JELF support. Awards include the GSA Advising Excellence Award, Outstanding Young Computer Science Researcher Award, and multiple Most Influential Paper awards. Key contributions include developing NiCad, advancing Stack Overflow search techniques, and leading collaborative projects in software analytics. His work has been featured in ACM Tech News, TechRepublic, and Stack Overflow blogs. Dr. Roy actively engages in keynotes at conferences like WCRE, IWSC, and BIM.

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Kevin SchneiderView profile

Professor

University of SaskatchewanCanada

Dr. Kevin Schneider is a Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on software architecture, evolution, analysis, and visualization, with notable work in quantum computing applications and machine learning. He also explores collaborative software teams and domain-specific languages to enhance development processes. Education: Ph.D., Computing and Information Science, Queen’s University (2000) Research Associate, Computing and Information Science, Queen’s University (1991–94) M.Sc., Computing and Information Science, Queen’s University (1990) B.Sc.(Hon), Computational Science, University of Saskatchewan (1980) Research interests include software design principles, maintenance strategies, and the integration of AI/quantum computing into software engineering. He emphasizes reproducibility in scientific workflows and tools like VizSciFlow. His work often bridges theory and practice, addressing challenges in code clone stability, user feedback management, and healthcare-related machine learning frameworks. Scientific Awards: Most Influential Paper at SCAM 2001 for his work on software engineering via source transformation. Advising and grants: While no specific advisees are listed, his research involves large-scale projects such as the Nutrient App and automated polyp segmentation tools. He collaborates on grants related to quantum computing applications and cloud-based software systems. Labs and teams: His work centers on collaborative scientific data analysis groups and developing tools for real-time groupware systems in complex workflows. He contributes to projects like CloneCognition and FSECAM, aiming to improve software design and maintenance through advanced analytics.

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Jeff HuangView profile

Associate Professor

Texas A&M UniversityUnited States

Jeff Huang is an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on software engineering, programming languages, concurrency, and runtime verification, with notable contributions to static analysis, race detection, and vulnerability mitigation in concurrent systems. Education: Postdoc, Computer Science, University of Illinois at Urbana-Champaign (2013-2014) Ph.D., Computer Science, Hong Kong University of Science and Technology (2012) B.E., Electrical Engineering, National University of Defense Technology, China (2008) Research Interests: Huang's work bridges theoretical foundations and practical applications in concurrency debugging, static analysis tools, and cybersecurity for smart contracts. He emphasizes scalable solutions for pointer analysis, race detection, and vulnerability detection in distributed systems and blockchain technologies. Recent Trends in Publications: His recent work explores AI-driven program execution (e.g., SGLang), blockchain security (e.g., Smart Contract analysis), and dynamic/static analysis techniques for memory safety. These studies underscore advancements in automated tools for securing concurrent and distributed systems. Awards: 2023 ACM SIGSOFT Distinguished Paper Award 2019 DARPA Young Faculty Award 2016 NSF CAREER Award 2013 ACM SIGSOFT Outstanding Doctoral Dissertation Award Advising & Grants: Huang has advised PhD students including Bozhen Liu and Peiming Liu, who have contributed to OpenMP race detection and pointer analysis tools. His grants include NSF awards for pointer analysis as a service and DARPA funding for young faculty research. Labs & Teams: He leads the O2 Lab, focused on concurrency verification and cybersecurity, collaborating with industry partners like Coderrect Inc. and DOE on scalable static analysis frameworks.

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Koushik SenView profile

Professor

Max Planck Institute for Software SystemsGermany

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research focuses on developing software tools and methodologies to enhance programmer productivity and software quality, with expertise in Software Engineering, Programming Languages, and Formal Methods. Education: B.Tech from Indian Institute of Technology, Kanpur M.S. and Ph.D. in Computer Science from University of Illinois at Urbana-Champaign Research Focus: Professor Sen pioneers automated testing techniques including concolic testing and DART (Directed Automated Random Testing). His work bridges formal methods with practical software development, emphasizing bug detection, program synthesis, and AI-driven software analysis tools. Recent innovations include machine learning approaches for code recommendation and fuzzing. Publication Trends: His recent publications (2019-2023) demonstrate strong emphasis on fuzzing techniques, program synthesis, and AI/ML applications in software engineering. Notable domains include smart contract security, automated testing, and developer tooling, with frequent collaborations in top-tier conferences. Awards and Honors: NSF CAREER Award (2008) Sloan Foundation Fellowship (2011) IFIP TC2 Manfred Paul Award (2010) Okawa Foundation Research Grant (2015) Multiple ACM SIGSOFT Distinguished Paper Awards UIUC Distinguished Alumni Educator Award (2014) Leadership: Active program committee member for premier conferences (PLDI, ICSE, ISSTA) and keynote speaker. His research is supported by NSF, Okawa Foundation, and Sloan Foundation.

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Mahir ArzokyView profile

Lecturer

Brunel University LondonUnited Kingdom

Dr Mahir Arzoky is a Lecturer in the Department of Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. He holds a PhD from Brunel University London (2015) and has extensive research experience in artificial intelligence and software engineering. His research focuses on: Artificial Intelligence and Intelligent Data Analysis Search Based Software Engineering (SBSE) Clustering algorithms and heuristic search methods Software refactoring and quality assessment Data mining applications in healthcare and education Analysis of his 15 most recent publications (2018-2022) reveals strong interdisciplinary work bridging computer science with healthcare (diabetes patient modeling, medical imaging) and education (chatbot design, algorithm visualization). His technical focus centers on clustering optimization, refactoring impact analysis, and explainable AI, with frequent use of empirical validation methods. Key collaborations include researchers like Stephen Swift, Steve Counsell, and Giuseppe Destefanis. Dr Arzoky has secured significant research funding through EPSRC grants including: AQUATIC project (EP/M024083/1): Assessing Test Suite Quality in Industrial Code FIAR-NET (EP/N011627/1): Fault Analyses in Industry and Academic Research Network His professional network includes active collaborations across computer science, healthcare informatics, and educational technology domains, with recent work extending into transformer models for healthcare SQL conversion and graph partitioning for software modularization.

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Damián Pitalúa-GarciaView profile

Researcher

University of CambridgeUnited Kingdom

Damián Pitalúa-García is a Researcher at the Centre for Quantum Information and Foundations within the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge. His work bridges quantum foundations, cryptography, and information theory, focusing on spacetime-quantum interplay. Current research spans foundational quantum problems involving spacetime, relativistic cryptography, and experimental imperfections in secure protocols. His 15 most recent publications address topics like oblivious transfer, quantum tokens, and spacetime-constrained communication. Scientific awards include granted patents for spacetime-constrained oblivious transfer (US 10715319B2, 2020; EP 3777008 B1, 2023). He contributes to lecture courses including Part II Quantum Information and Computation and Part III Quantum Information, Foundations and Gravity .

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Miryung KimView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Miryung Kim is a Professor and Vice Chair of Graduate Studies in UCLA's Computer Science Department, where she directs the Software Engineering and Analysis Laboratory. She is renowned for her pioneering work in software evolution, code clone management, and establishing the emerging field of Software Engineering for Data Intensive Computing (SE4DA and SE4ML). Her research focuses on automated testing and debugging for Apache Spark, developer tools for heterogeneous computing, and conducting systematic studies of refactoring practices in industry. She led the first large-scale study of data scientists in industry and developed JDebloat, a Java bytecode debloating tool that made significant tech transfer impact to the Navy. Her recent publications demonstrate strong trends in fuzz testing for big data analytics and heterogeneous computing, with a focus on natural input generation, co-dependence awareness, and leveraging hardware probes for acceleration. Her work bridges software engineering with data-intensive and heterogeneous computing paradigms. ACM SIGSOFT Influential Educator Award (2022) ICSME Most Influential Paper Award (2023 and 2020) NSF CAREER award Google Faculty Research Award Okawa Foundation Research Award Humboldt Fellow ACM Distinguished Member As an academic advisor, she has produced eight tenure-track faculty members at institutions including Columbia, Purdue, and Virginia Tech. Her research has been supported by National Science Foundation, Air Force Research Laboratory, Google, IBM, Intel, Okawa Foundation, Samsung, and Office of Naval Research. She previously served as Program Co-Chair of ESEC/FSE 2022 and has delivered keynotes at ASE 2019 and ISSTA 2022. She maintains active industry collaborations, serving as an Amazon Scholar at Amazon Web Services and having spent time as a visiting researcher at Microsoft Research.

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Baishakhi RayView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Baishakhi Ray is an Associate Professor of Computer Science at Columbia University, working at the intersection of AI, Software Engineering, and Security. She received her Ph.D. from the University of Texas, Austin, and has established herself as a leading researcher in applying artificial intelligence to software engineering challenges. Her educational background includes a Ph.D. from the University of Texas, Austin, which provided the foundation for her research career at the forefront of AI and software engineering. Dr. Ray's research focuses on leveraging artificial intelligence to solve fundamental challenges in software engineering and security. Her work spans multiple areas including code generation with large language models, vulnerability detection, software testing, and program analysis. She has pioneered approaches that combine deep learning with traditional software engineering techniques to create more robust, secure, and efficient software development processes. Her research has practical implications for improving code quality, enhancing software security, and accelerating development cycles through AI assistance. Her recent work demonstrates a strong emphasis on semantic-aware code generation, execution reasoning, and addressing hallucinations in code language models. She has also made significant contributions to evaluating the functionality and security of AI-generated code, identifying critical challenges in the practical adoption of AI for software development. Dr. Ray has received numerous prestigious awards recognizing her contributions to the field: IEEE TCSE Rising Star NSF CAREER award IBM faculty award VMware Faculty award Distinguished Paper awards at FSE'17, ASE'22, and ISSTA'23 ICSME Most Influential Paper award Publications featured in CACM Research Highlights As an Amazon Visiting Academic and active participant in major software engineering conferences, Dr. Ray has established herself as a thought leader in AI for software engineering. Her research has been widely covered in trade media, indicating its relevance and impact on industry practices. She has mentored numerous students through their research and has been instrumental in shaping the next generation of researchers in this interdisciplinary field. Her work demonstrates a consistent focus on bridging theoretical advances with practical applications, ensuring that her research has tangible benefits for the software development community. The trajectory of her publications shows an evolving research agenda that has successfully adapted to the rapidly changing landscape of AI and its applications to software engineering.

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Vincenzo Della MeaView profile

Associate Professor

University of UdineItaly

Vincenzo Della Mea is an Associate Professor of Information Processing Systems at the University of Udine's Department of Mathematical, Computer and Physical Sciences. His research focuses on medical informatics, digital pathology, biomedical ontologies, and AI applications in healthcare. He holds abilitation to full professorship and is a member of the WHO Italian Collaborating Centre for International Classifications (WHO-FIC), ICHI Task Force, and ESDIP's Executive Board. He leads the EU MSCA Doctoral Network BosomShield (2022-2026) and previously managed the AIDPATH Marie Curie project. As an editor for journals like Digital Health and Journal of Pathology Informatics , he bridges academia and practice. Beyond academia, he is a poet with awards, including the Nelle terre dei Pallavicino Prize for his 2004 collection Algoritmi , and organizes interdisciplinary events merging science and literature. Education & Roles : Holds a professorship in Computer Science and teaches courses on web technologies, medical informatics, and AI across multiple degree programs. Previously served as Vice-President of SIBIM (Italian Biomedical Informatics Society). Research Interests : Specializes in digital pathology, medical AI, telemedicine, and standardization of health classifications like ICD-11 and ICF. His work emphasizes ontology harmonization and machine learning for clinical decision support. Recent Contributions : Published on WHO classification harmonization, AI-driven pathology tools, and energy-sector LLM applications. Active in editorial roles and international collaborations, including the HEROHE Challenge for breast cancer analysis. Awards & Recognition : 2023 – Poetry collection Clone 2.0 (neurally generated) 2005 – Nelle terre dei Pallavicino Award Grants & Projects : Led EU-funded projects (AIDPATH, BosomShield) and contributed to initiatives like the ICD-11 Mortality Coding System. Collaborates with institutions like AcegasApsAmga on AI for utilities. Labs & Initiatives : Involved in digital pathology workflow optimization and educational platforms for medical coding and AI ethics.

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Peter JansenView profile

Associate Professor

University of ArizonaUnited States

Peter Jansen is an Associate Professor at the University of Arizona's College of Information Science with a joint appointment at the Allen Institute for Artificial Intelligence (Ai2). He specializes in natural language processing (NLP), cognitive artificial intelligence, and automated scientific discovery. His research focuses on virtual environments for scientific reasoning, such as ScienceWorld and DiscoveryWorld, and methods for explainable AI through projects like the Explanation Bank. Education: PhD in Psychology and Neuroscience from McMaster University, and a Bachelor of Independent Studies from the University of Waterloo. His interdisciplinary background combines NLP, computer science, physics, and electrical engineering. Key projects include open-source hardware initiatives like the science tricorder (featured in over 50 media outlets and exhibited at the German Museum of Technology in Berlin) and TextWorldExpress, a text-game simulator. His work emphasizes grounding science education through sensing and developing AI systems capable of systematic reasoning and explanation generation. Current roles include advising students in automated scientific discovery and contributing to cross-listed courses in Computer Science and Linguistics. He maintains an active presence in academic outreach through teaching, conferences, and publications.

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