**Ahmed Hassan** is a **Professor** and **Canada Research Chair (Tier 2) in Software Analytics** at the **School of Computing**, **Queen's University**, affiliated with the **Faculty of Arts and Science**. He holds the **NSERC/RIM Industrial Research Chair in Software Engineering for Ultra Large Scale Systems**. His research focuses on software systems, data analytics, and mining software repositories (MSR), leading the **Software Analysis and Intelligence Lab (SAIL)**. **Education**: PhD (2005), MMath (2001), BMath (1999) in Computer Science from the University of Waterloo, Canada. **Research Interests**: Software evolution, performance engineering, distributed systems debugging, cybersecurity, and AI-driven software solutions. SAIL explores tools for maintaining large-scale software systems, improving developer productivity, and integrating AI into software workflows. **Awards & Recognition**: ACM and IEEE Fellowships, patents in multiple jurisdictions, and leadership roles in MSR and ICSE conferences. Industrial experience includes RIM/BlackBerry, IBM Research, and Nortel Networks. **Current Projects**: Focus on foundation model-powered software (FMware), AIOps, and ethical AI applications. Teaching courses like CISC322: Software Architecture.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۰۶-۱۱۳ از ۱۱۳ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Wei Wangمشاهده پروفایل
استادیار
- Leadership
- Business Ethics
- Organizational Behavior
- +۳ مورد دیگر
Wei Wang is an Assistant Professor and The Associates Fellow in Leadership and Ethics at the Business Administration Department, Asper School of Business, University of Manitoba. His research focuses on leadership dynamics and ethics in the workplace, employing mixed-method approaches. He has been recognized with the 2019 Society of Business Ethics Emerging Scholar Award and the 2022 Anne Tsui Dare to Care Research Award for impactful work on employee well-being. His teaching expertise spans organizational behavior, negotiation, and business ethics. He leads the GLOW Lab, advancing research in leadership and ethical workplace practices. Key research interests include ethical leadership, workplace mistreatment, and the behavioral consequences of deviant coworker behaviors. His work has been published in leading journals such as Journal of Applied Psychology and Journal of Management . Beyond academia, he enjoys outdoor activities, running, and travel. Awards include the 2019 Emerging Scholar Award for contributions to business ethics and the 2022 Dare to Care Award for research prioritizing employee welfare. His lab, the GLOW Lab, drives innovative studies in leadership and ethical organizational practices.
Pinjia Heمشاهده پروفایل
استادیار
Pinjia He is an Assistant Professor and Presidential Young Fellow at the School of Data Science, The Chinese University of Hong Kong, Shenzhen, where he leads research in software engineering, AI systems, and log analysis. He received his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong and his B.E. from South China University of Technology. His research focuses on three interconnected areas: AI for Software Engineering : Developing LLM-based tools for automated logging, code repair, and AIOps Software Engineering for AI : Ensuring safety and reliability of AI systems through testing and validation Software Systems : Log analysis, anomaly detection, and performance optimization in distributed systems Recent publications demonstrate strong emphasis on testing methodologies for AI systems (LLMs, vision-language models), automated log analysis techniques, and AI reliability. His work consistently appears in top-tier venues including ICSE, FSE, ASE, and ICLR. He has received significant recognition including: Most Influential Paper Award (ISSRE) IEEE Open Software Services Award IEEE CS TCSE Rising Star Award He leads a substantial research team with 9 PhD and 8 Master's students, focusing on AI/SE integration. The group maintains active industry collaborations and open-source projects with over 5,000 GitHub stars.
Ivan Beschastnikh is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Faculty of Science. He leads research in distributed systems, software engineering, and formal methods, with a focus on privacy-preserving technologies, blockchain systems, and machine learning. His work bridges theoretical foundations and practical system implementations, emphasizing empirical validation and real-world deployment. Research Interests: His primary areas include distributed systems (e.g., consensus algorithms, transaction processing), formal methods for system correctness (e.g., PGo compiler for verified implementations), and privacy in federated learning and blockchain. He also explores interdisciplinary topics like AI ethics, human-computer interaction for developers, and system security. Key Projects: Includes PGo (formal specification to Go compiler), Biscotti (decentralized federated learning), Erlay (Bitcoin transaction relay optimization), and Teleoscope (text corpus analysis tool). His work has practical impact in blockchain scalability, secure multi-party ML, and distributed system validation. Awards: Recognized with the ASPLOS Distinguished Artifact Award, UBC Faculty Teaching Award, and ESEM Best Paper Award. His contributions span academic excellence, pedagogy, and collaborative research. Lab Affiliations: Active in the Systopia Lab and Software Practices Lab (SPL) , and collaborates with UBC’s Data Science Institute and Blockchain@UBC. He emphasizes interdisciplinary research, mentoring students in both theoretical and applied systems work.
José Cano Reyesمشاهده پروفایل
مدرس ارشد
- Computer Architecture
- Computer Systems
- Compilers
- +۸ مورد دیگر
José Cano Reyes is a Senior Lecturer (Associate Professor) at the University of Glasgow's School of Computing Science, leading the Glasgow Intelligent Computing Lab (gicLAB) and serving as deputy Head of the GLAsgow Systems Section (GLASS). His academic career includes postdoctoral roles at the University of Edinburgh (2014-2018) and Universitat Politècnica de Catalunya (2012-2013), with a PhD and engineering degree from Universitat Politècnica de Valencia (2004-2012). He has held visiting and guest lecturer positions at Edinburgh and Glasgow across computer architecture, compilers, and embedded systems topics. Research focuses on hardware-software co-design for edge AI, including DNN acceleration (FPGA/GPU), encrypted AI systems, and secure mission-critical SoCs. Key projects include EU's dAIEDGE, EPSRC IDEAL, and UKRI AppControl. He leads over 15 research staff and students in areas like quantization, sparsity exploitation, and robust AI deployment. Notable contributions span 100+ peer-reviewed publications across top venues (ISCA, IJCNN, IEEE TPDS) and 3 authored books on ad hoc networks and embedded systems. Academic service includes organizing 20+ conferences (ISPASS, Euro-Par, ASPLOS) and serving on editorial boards for ACM TACO and IEEE TPDS. His educational efforts include teaching Computer Architecture (Year 4), Computer Systems (Year 1), and supervising over 20 PhD/MSc students since 2017.
Andreas Both is a Professor at the Faculty of Computer Science and Media at Leipzig University of Applied Sciences (HTWK Leipzig), where he leads the Web & Software Engineering (WSE) research group. His work spans multiple domains of computer science with a strong focus on bridging theoretical foundations with practical applications in software engineering, web technologies, and artificial intelligence. His research interests primarily revolve around Software Engineering (particularly test automation with AI and source code analysis), Web Engineering , Applied Artificial Intelligence (including Machine Learning, Deep Learning, and Large Language Models), Question Answering & Chatbots , and Data-driven Applications . He has developed innovative approaches in knowledge graph question answering systems, multilingual NLP applications, and privacy-preserving data sharing technologies using the Solid protocol framework. The analysis of his recent publications reveals a strong trajectory toward leveraging Large Language Models for knowledge graph applications, with particular emphasis on multilingual capabilities, explainability, and quality improvement in question answering systems. His work increasingly integrates privacy considerations with advanced AI techniques, particularly through Solid protocol implementations for data sovereignty. Best Paper Award at ICWE 2024 for AuthApp - a GDPR-compliant access granting system Outstanding Paper Award at ICWI 2024 for LLM-generated explanations in question answering systems Multiple first-place awards at the TEXT2SPARQL Challenge 2025 Best Paper Awards at ICWE 2025 and IEEE ISI 2025 CHI 2015 Honorable Mentions for search interface research Professor Both actively mentors students through the Google Summer of Code program and serves on the leadership board of the Architecture (ARC) working group of the German Computer Science Society (Gesellschaft für Informatik). His teaching portfolio includes Software Engineering, Question Answering & Chatbots, Software Projects, Project Management Practicum, Web Engineering, and Software Engineering & AI courses. His office hours are Thursdays from 11:15-12:15, requiring advance email appointment with topic specification.
Pinjia Heمشاهده پروفایل
استادیار
Pinjia He is an Assistant Professor and Presidential Young Fellow at The Chinese University of Hong Kong, Shenzhen's School of Data Science. He is also recognized as a national-level young talent in China. His academic journey includes a postdoctoral position at ETH Zurich's Department of Computer Science under Prof. Zhendong Su, a Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong supervised by Prof. Michael R. Lyu, and a B.E. in Computer Science and Technology from South China University of Technology. Ph.D. in Computer Science and Engineering, The Chinese University of Hong Kong Postdoctoral Scholar, ETH Zurich B.E. in Computer Science and Technology, South China University of Technology Dr. He's research spans software engineering, natural language processing, and systems, with particular focus on (1) AI for SE (e.g., LLM for code, AIOps), (2) SE for AI (e.g., LLM safety), and (3) software testing. He is renowned for his work on robust NLP systems and software log analysis. His research has been published at top venues including ICSE, FSE, ASE, ISSTA, ICLR, and OSDI. His publication trends show a consistent focus on log analysis systems, with recent work shifting toward LLM applications in software engineering and safety evaluation of conversational AI systems. His research demonstrates strong industry impact with tools downloaded over 60,000 times by more than 450 organizations. Most Influential Paper Award (ISSRE) IEEE Open Software Services Award Dr. He actively contributes to the academic community as Social Media Co-Chair for FSE 2025, Associate Editor of TOSEM, and serves on program committees for major conferences including FSE 2025, ICSE 2025, ISSTA 2025, and ASE 2024. His GitHub repositories (logparser, loglizer, loghub) have garnered over 5,000 stars and significant industry recognition including from IBM. While specific grant information isn't detailed in the provided text, his extensive publication record and tool development suggest substantial research funding. His work has been cited over 5,000 times according to Google Scholar, and his open-source tools have been widely adopted in both academia and industry. His current research focuses on advancing the intersection of software engineering and artificial intelligence, particularly in leveraging LLMs for software development tasks while ensuring their safety and reliability.
Austin Mordahlمشاهده پروفایل
استادیار
- Static Analysis
- Taint Analysis
- Automated Testing
- +۴ مورد دیگر
Austin Mordahl is an Assistant Professor in the Department of Computer Science at the University of Illinois Chicago. His research focuses on improving the usability and reliability of software quality assurance tools, particularly static analyses and fuzz testing. Dr. Mordahl actively seeks students interested in cutting-edge research in software engineering at UIC. Dr. Mordahl's research interests span multiple areas of software engineering with a particular emphasis on: Static Analysis and Taint Analysis for software security Automated Testing techniques including fuzz testing Improving the usability and reliability of software quality assurance tools Configurable static analysis tools and their behavior Applying machine learning to triage and configure static analysis tools Lifting static analysis to work on software product lines Improving evaluations of fuzz testing tools His recent publications demonstrate a strong focus on addressing challenges in configurable static analysis tools, with particular attention to nondeterministic behavior, configuration spaces, and automatic testing and debugging approaches. Mordahl's work bridges theoretical foundations with practical applications, aiming to make software quality assurance tools more accessible and effective for developers. Dr. Mordahl has received several prestigious awards for his work: NSF Graduate Research Fellowship Awardee (2020) Eugene McDermott Graduate Research Fellowship Awardee (2020) ICSE 2019 Student Research Competition Winner Dr. Mordahl is actively involved in mentoring and seeks students interested in software engineering research. He has served on numerous program committees for top software engineering conferences including ICSE, ASE, ISSTA, and PLDI. His service to the academic community extends to artifact evaluation committees, demonstrating his commitment to research reproducibility and rigor.