جستجوی استاد راهنمای دانشگاهی

Mohammad Hamdaqa is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he leads the Laboratory of Software and Emerging Technologies. His academic journey includes a Ph.D. in Electrical and Computer Engineering from the University of Waterloo (2016), a Master's in Electrical and Computer Engineering from Concordia University, an MBA from the New York Institute of Technology, and a Bachelor's in Computer Engineering from Jordan University of Science and Technology. His research focuses on the intersection of software engineering and emerging technologies, particularly examining how software engineering approaches can be adapted for complex new platforms like cloud computing and blockchain. His work spans model-driven software engineering, cloud application architecture, smart contract development, and infrastructure as code. He investigates both how traditional software engineering practices can evolve to address the challenges of modern distributed systems and how emerging technologies can transform software development processes themselves. Analysis of his recent publications reveals a strong emphasis on blockchain technologies (particularly smart contracts), cloud-native applications, and the application of AI to software engineering tasks. His work shows a consistent thread of empirical research combined with practical tool development, with increasing focus on sustainability aspects of software systems in recent years. Much of his research bridges theoretical foundations with practical implementation concerns. Professor Hamdaqa serves as a thesis supervisor for multiple graduate students, with recent completed Master's theses focusing on smart contract auditing, prompt engineering for OCL generation, model-driven epidemiology, and security practices in infrastructure as code. He actively recruits students for research projects in his laboratory. He is a member of both the IEEE Computer Society and the Association for Computing Machinery (ACM), has served on program committees for major software engineering conferences, and is on the editorial board of Service Transaction on Internet of Thing. His laboratory, the Laboratory of Software and Emerging Technologies, serves as the hub for his research activities in blockchain, cloud computing, and model-driven engineering.

• Software Engineering
• Model-Based Software Engineering
• Cloud Computing
• +۷ مورد دیگر

Zhen Ming (Jack) Jiang is an Associate Professor and York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems at York University's Department of Electrical Engineering and Computer Science. His research bridges software engineering, artificial intelligence, and computer systems with significant industrial impact. Dr. Jiang earned his Ph.D. from Queen's University's School of Computing and MMath/BMath degrees from the University of Waterloo's David R. Cheriton School of Computer Science. During his doctoral studies, he collaborated with BlackBerry's Performance Engineering team, developing tools now used daily to monitor commercial software systems. His research focuses on engineering rigor for AI-powered applications , software engineering evolution in the Generative AI era , and performance optimization of large-scale systems . Key areas include software performance engineering, mining software repositories, debugging distributed systems, source code analysis, and software visualization. His work combines empirical studies with practical tool development. Recent publications reveal strong trends in applying AI to software engineering challenges, particularly in machine learning systems reliability, blockchain efficiency, and AIOps solutions. His research consistently emphasizes empirical validation using real-world systems and industrial case studies. Scientific recognition includes: York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems NSERC Discovery Accelerator Supplements (DAS), 2020 Best Paper Award at ICST 2016 IEEE Software Best SEIP Paper at ICSE 2015 Ph.D. Research Achievement Award at Queen's University Multiple best paper awards at WCRE, MSR, and ICSE Dr. Jiang actively supervises graduate students and has secured competitive research funding including NSERC grants. His service includes program committee roles for top conferences (ICSE, ASE, ICSME) and editorial work for leading journals (TSE, TOSEM, EMSE). He leads research initiatives focused on foundation model-powered systems, collaborating with industry partners on performance monitoring and debugging solutions for large-scale distributed environments.

• Software Engineering
• Artificial Intelligence
• Computer Systems
• +۶ مورد دیگر

Muhammad Asaduzzaman is an Assistant Professor in the School of Computer Science within the Faculty of Science at the University of Windsor. His research focuses on software engineering, particularly software maintenance, mining software repositories, and recommendation systems for developers. Research interests span empirical studies of software artifacts, API usage analysis, and improving developer productivity through tools like COSTER for API element identification. Recent work examines dependency management in Maven ecosystems and AI-assisted code completion. Publications show consistent focus on analyzing developer activities through platforms like Stack Overflow and GitHub. Current investigations include LLM applications for code synthesis and technical debt impact analysis.

• Software Engineering
• Mining Software Repositories
• Empirical Software Engineering
• +۲ مورد دیگر

Cristiano Politowski is an Assistant Professor in the Department of Computer Science at Ontario Tech University’s Faculty of Science. His research focuses on applying software engineering principles to video game development, with particular emphasis on software testing, artificial intelligence for software engineering (AI4SE), deep reinforcement learning, and empirical software engineering. Education includes a PhD in Computer Science and Software Engineering from Concordia University (2022), supervised by Professors Yann-Gaël Guéhéneuc and Fabio Petrillo. Prior to his current role, he held postdoctoral positions at Université de Montréal and École de Technologie Supérieure in Montréal, Canada. Research interests span game engine architecture analysis, automated testing methodologies for games, and bridging gaps between academic theory and industry practices in software engineering. His work often involves empirical studies on software quality, framework impacts, and event-driven systems. Publications reflect a focus on game development challenges, including studies on API compatibility, subsystem coupling visualization, and AI-driven game balance assessment. He actively contributes to the understanding of software processes in the video game industry through surveys and dataset curation initiatives like PlayMyData.

• Software Engineering
• Video Game Development
• Artificial Intelligence for Software Engineering (AI4SE)
• +۴ مورد دیگر

Vera Pantelic is an Adjunct Assistant Professor in the Department of Computing and Software at McMaster University. Her research focuses on software engineering practices for model-based development in automotive systems, particularly centralized Electrical/Electronic (E/E) architectures, Simulink modeling, and supervisory control of probabilistic discrete event systems. Education: Not explicitly mentioned in the text. Her scholarly activity includes extensive contributions to conferences and journals in automotive software engineering, model transformation, and real-time systems. Her work addresses challenges in modularity, documentation, and compliance within automotive embedded systems. Her recent publications emphasize advancements in centralized E/E architectures, model-driven testing, and assurance cases for automotive safety. She collaborates on topics integrating software engineering principles with automotive domain requirements. Scientific Awards: No specific awards mentioned in the text. She serves as an advisor in software engineering, though specific student names are not listed. Her projects involve simulation-based testing, model refactoring, and compliance frameworks, supported by industry partnerships and academic grants. Her work contributes to labs and teams focused on automotive software reliability and model-driven engineering. No explicit lab or team affiliations are detailed in the provided text.

• Software Engineering
• Model-Driven Engineering
• Automotive Embedded Systems
• +۳ مورد دیگر

Tushar Sharma is an Assistant Professor in the Faculty of Computer Science at Dalhousie University, Canada. His research focuses on software engineering, particularly software quality, refactoring, technical debt, and the application of machine learning in software engineering (ML4SE). He leads the SMART Lab and is actively involved in projects related to Green AI and sustainable software development. PhD : Software Engineering, Athens University of Economics and Business, Greece (2019) MS : Computer Science, Indian Institute of Technology-Madras, India His research interests span software design and architecture, code and design quality, refactoring, technical debt, mining software repositories, and applied machine learning for software engineering. He is particularly interested in sustainable AI, green software engineering, and the use of large language models for code. His work bridges empirical studies with practical tool development to improve software maintainability and quality. His recent publications highlight a strong trend in code smell detection, refactoring automation, energy-aware AI, and the reliability of large language models in software engineering. He has developed tools like Designite and DPy and contributed datasets such as MaRV and DACOS, emphasizing empirical validation and reproducibility in software engineering research. Dean's Research Excellence Award Best Artifact Award, SCAM 2023 IEEE Senior Member Tushar Sharma has secured significant research funding, including an NSERC Discovery Grant for DevQOps, Mitacs Accelerate grants with industry partners, and contributions to the $154M Canada First Research Excellence Fund project. He actively mentors students and collaborates with industry. He leads the SMART Lab at Dalhousie and has organized workshops such as SATToSE 2018. He is also a founding developer of Designite, a widely used software design quality assessment tool.

• Software Engineering
• Software Quality
• Code and Design Quality
• +۱۰ مورد دیگر

Dr. Graziano Fiorillo is an Assistant Professor in the Department of Civil Engineering at the University of Manitoba's Price Faculty of Engineering. He holds a Ph.D. from the City University of New York and M.Sc./B.Sc. from the University of Naples, Italy. His research focuses on structural reliability, bridge systems analysis, and risk assessment, incorporating machine learning and high-performance computing. He has contributed to probabilistic frameworks for infrastructure resilience, filovirus outbreak modeling, and bridge redundancy evaluation. Education: Ph.D. Civil Engineering, City University of New York, 2016 M.Sc. Building Engineering, University of Naples Federico II, 2003 B.Sc. Building Engineering, University of Naples Federico II Research Interests: Dr. Fiorillo specializes in structural analysis of bridges, risk-based design, and machine learning applications in infrastructure. He develops probabilistic models for bridge network reliability and flood risk assessment, with a focus on Manitoba's infrastructure resilience. His work integrates computational fluid dynamics (CFD) and energy efficiency solutions for buildings. Publications: His recent work emphasizes interdisciplinary approaches to infrastructure challenges, including CFD for sediment transport, EnergyPlus-based building efficiency studies, and MPI parallel computing for reliability analysis. His 2024 studies on flood-overload interactions and additive manufacturing in construction highlight emerging trends in civil engineering. Awards: He received the 2012 New York State Intelligent Transportation Society Award for best student paper. His research has been applied to truck weight regulation strategies and bridge importance factor calibration. Advising & Grants: Offers M.Sc. opportunities in CFD, building energy efficiency, and bridge structures. Positions require expertise in OpenFOAM, EnergyPlus, or structural analysis software. No specific grants mentioned in the text.

• Civil Engineering
• Structural Analysis
• Risk and Reliability Engineering
• +۴ مورد دیگر

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.

• Software Engineering
• Software Maintenance and Evolution
• Code Clone Detection
• +۳ مورد دیگر

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.

• Software Architecture and Design
• Software Evolution and Maintenance
• Software Analysis and Navigation
• +۶ مورد دیگر

Yann-Gaël Guéhéneuc is a Professor at Concordia University's Department of Computer Science and Software Engineering. He leads the Ptidej Team, focusing on software engineering methodologies, IoT systems, and game engine architecture analysis. His research emphasizes static/dynamic analyses, service-oriented architectures, and machine learning design patterns. Current Affiliations: Concordia University (Full-time Professor) Ptidiej Team Lead Research Interests: Specializes in IoT system testing, microservices architecture, game engine design patterns, and anti-pattern detection in multi-language systems. His work bridges theoretical software engineering principles with practical industrial applications, particularly in legacy system modernization and machine learning system design. Recent Trends in Publications: Focuses on IoT testing methodologies, machine learning architecture patterns, and service-oriented system transformations. His 2025 works advance IoT system taxonomy and game engine analysis techniques. Advising: Supervises MASc and PhD programs in Software Engineering and Computer Science Labs/Teams: Ptidej Team develops software tools for system analysis (e.g., Magnet, SyDRA)

• Software Engineering
• IoT Systems
• Static and Dynamic Analyses
• +۴ مورد دیگر

Cristiano Politowski is an Assistant Professor in the Department of Computer Science at Ontario Tech University's Faculty of Science. His research focuses on software engineering for video games, automated testing, AI4SE, and empirical studies. He holds a Ph.D. in Software Engineering from Concordia University (2022), an M.Sc. in Computer Science from Universidade Federal de Santa Maria (2017), and a B.Sc. in Computer Science from Universidade Regional do Estado do Rio Grande do Sul (2014). Prof. Politowski has extensive postdoctoral experience at Université de Montréal (GEODES group) and École de Technologie Supérieure (ÉTS), focusing on game engine architecture, requirements specification, and certifiable RTOS systems. He has organized workshops like ASE4Games 2021/2022 and FaSE4Games 2024, emphasizing game software engineering. His research interests span video game development challenges, software testing methodologies, and leveraging AI for software engineering. Notable projects include analyzing game engine subsystem coupling, assessing video game balance with autonomous agents, and curating datasets like PlayMyData. Prof. Politowski has secured $20K from MITACS for a 5G infrastructure project during the pandemic and received the Concordia Accelerator Award (2021). His work has been published in venues like MSR, ICSE, and IEEE Transactions.

• Software Engineering
• Video Game Development
• Artificial Intelligence for Software Engineering (AI4SE)
• +۳ مورد دیگر

Marsha Chechik is a Professor in the Department of Computer Science at the Faculty of Arts and Science, University of Toronto. She previously served as Department Chair from 2019-2022 and as Acting Dean in the Faculty of Information from July-December 2022. Her academic career spans numerous research contributions and leadership roles within the software engineering community. Professor Chechik's primary research interests focus on software engineering with emphasis on formal methods to enhance software quality. Her work encompasses scalable automated verification techniques including model-checking and theorem-proving, formal specification languages, verification of protocols, non-classical logics, and reasoning under inconsistency. She has made significant contributions to model management, software product lines, safety and security assurance, and automotive safety systems. Her research bridges theoretical foundations with practical applications, particularly in managing uncertainty in software models and developing techniques for automotive safety verification. Her recent publications demonstrate a strong focus on model management and transformations, software product lines and variability analysis, safety and security assurance cases, and semantic analysis of software evolution. The integration of formal methods with practical software engineering challenges, especially in safety-critical domains like automotive systems, represents a consistent theme throughout her work. Professor Chechik has been recognized with multiple prestigious awards including a Best Paper Award at RE'12, a SIGSOFT Distinguished Paper Award at ICSE'12, a Best Student Paper Award at CASCON'07, and a Distinguished Paper Award at ICSE'07, highlighting the impact and quality of her research contributions. She actively supervises graduate students and has successfully guided numerous Ph.D. candidates to completion. Her group has produced graduates who predominantly pursue research careers in both academic institutions and industrial research labs. She currently leads several funded projects including the Automotive Safety project (in collaboration with General Motors) and the Software Evolution project, focusing on practical applications of her research interests. Professor Chechik leads the Software Engineering Lab at the University of Toronto, where innovative projects like Matchmakers (a serious game for software engineering) are developed. Her collaborative network extends across institutions, with notable partnerships including Julia Rubin at the University of British Columbia, demonstrating her commitment to interdisciplinary research and academic collaboration.

• Software Engineering
• Formal Methods
• Safety and Security Assurance
• +۷ مورد دیگر

Shurui Zhou is an Assistant Professor at the University of Toronto , with primary appointment in the Department of Electrical & Computer Engineering and cross-appointments in the Department of Computer Science and the Department of Mechanical & Industrial Engineering . She is also affiliated with the Schwartz Reisman Institute and a member of the Data Sciences Institute . Zhou directs the FORCOLAB , focusing on enhancing collaboration in distributed software teams, especially in open-source and AI-enabled systems development. Her research integrates software engineering principles with human collaboration insights from organizational behavior, aiming to improve collaboration efficiency through tooling and interdisciplinary methods. Recent publications (2023-2025) explore LLM integration in software development , sustainability in scientific open-source communities , and collaborative challenges in computer-aided design . Education: PhD (2020) from Carnegie Mellon University's Software and Societal Systems Department , MSc from Peking University , BSc from Xi'an Jiaotong University Scientific Awards: Gordon Slemon Teaching of Design Award (2022) Grants: Collaborator on NSERC Alliance-Mitacs Accelerate Grant (2025) for LLM analysis in political data Her lab, FORCOLAB, develops tools like forks-insight.com to analyze GitHub forks and Redundant PR detection bots . Zhou organizes events like the Responsible LLM-Human Collaboration Hackathon (2024) and actively serves on conference committees including ICSE 2025 and ICSME 2024 .

• Software Engineering
• Open-Source Collaboration
• Fork-Based Development
• +۴ مورد دیگر

Patrick Lam is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, with a cross-appointment to the Cheriton School of Computer Science. His research focuses on applications of programming languages and static analysis to software engineering challenges, emphasizing verifiable software specifications and program understanding. Dr. Lam has held significant grants from NSERC and is recognized for his impactful work, including the First Decade High Impact Paper award for his Soot framework. Education: Doctorate in Computer Science, Massachusetts Institute of Technology, 2007 Master's in Computer Science, McGill University, 2000 Bachelor's in Joint Honours Mathematics and Computer Science, McGill University, 1999 Research Interests: His primary areas include static program analysis, verifiable software specifications, and compiler design, with a focus on linking high-level software designs to low-level implementations. He explores techniques like lightweight specifications and domain-specific languages to enhance software reliability and efficiency. Recent work also addresses empirical studies of programming practices and security through modularization. Publications: Dr. Lam's recent publications span advancements in static analysis tools (e.g., WasmWalker for WebAssembly), formal verification of code generated by AI tools like GitHub Copilot, and empirical studies on C++ immutability usage. His work bridges theoretical programming language research with practical software engineering applications, emphasizing tools for developer productivity and code reliability. Awards and Recognition: First Decade High Impact Paper recognition for "Soot – A Java Optimization Framework" (2010) Teaching and Grants: He has taught courses such as CS 447, ECE 453, and ECE 459 on software testing and performance programming. Active in grant-funded research, he secured NSERC Engage Grant (2013) and an ongoing NSERC Discovery Grant (2013–2018). Lam has also advised graduate students and contributed to the Software Engineering Program at Waterloo as its Director (2016–2019). Labs and Teams: His research group explores topics in program analysis and software engineering, with collaborations on projects like abstract debugging tools (GobPie) and static analysis frameworks (Soot). He maintains an open-source repository on GitHub, contributing to educational materials and research tools.

• Static Program Analysis
• Verifiable Software Specifications
• Software Engineering
• +۸ مورد دیگر

Taher Ghaleb is an Assistant Professor in the Computer Science Department at Trent University, Peterborough, Canada. He completed his Ph.D. at Queen’s University under Prof. Jenny Zou, followed by postdoctoral research at the University of Ottawa and a senior research role at the University of Toronto. His research focuses on applying data science and AI to address software engineering challenges. Education: Ph.D., Queen’s University, Software Evolution & Analytics Lab (SEAL) Postdoctoral Fellow, University of Ottawa Senior Research Position, University of Toronto Research Interests: Data-Driven Software Analytics: Empirical analysis of software development practices. AI in Software Engineering: Leveraging generative AI for code generation and bug detection. Continuous Integration/DevOps: Optimizing CI/CD pipelines for efficiency and reliability. LLM-Oriented Development: Integrating language models into software lifecycle processes. Publications: Taher’s work spans CI/CD practices, test case minimization, and AI-driven software testing. Recent trends emphasize empirical studies on open-source Android apps and flaky test prediction using language models. Awards: No explicit awards listed, but holds multiple U.S. patents related to software engineering and compiler systems. Advising & Grants: Seeks Master’s students and interns to join his team. Teaches courses like Software Design & Modelling (COIS 2240) and Software Engineering Project (COIS 4000) at Trent University. Labs & Teams: Formerly part of the Software Evolution & Analytics Lab (SEAL) at Queen’s University.

• Data-Driven Software Analytics
• Mining Software Repositories
• Continuous Integration and Delivery (CI/CD) – DevOps
• +۳ مورد دیگر