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The Winter 2025 edition of the Tech Trends Speaker Series delves into cutting-edge developments at the intersection of artificial intelligence, cybersecurity, and software engineering. Participants will explore how large language models are transforming software observability and debugging practices, discover AI applications in malware detection and digital forensics, and examine the complex challenges of Android fragmentation in mobile app development. These topics reflect the evolving demands facing today's tech professionals and researchers.
Each hour-long online session features distinguished speakers from leading Canadian institutions, combining theoretical insights with practical applications drawn from industry collaborations. Sessions include interactive a Q&A space at the end, allowing participants to engage directly with the panelists and to gaining valuable perspectives on emerging technologies that can enhance their professional practice and technical expertise.
Event 1: Software Observability in the Era of Large Language Models 鈥� Challenges and Opportunities
Date: March 31, 2025
Time: 11 a.m.
Delivery Mode: Online
Language of Delivery: English
The complexity of modern cloud platforms and the highly distributed nature of today鈥檚 software systems present significant challenges for debugging, anomaly detection, and root cause analysis. Traditional methods for software debugging, monitoring, and performance analysis are often limited, as they focus primarily on known issues. The rise of large language models (LLMs) has further transformed software development by automating tasks, often reducing developers鈥� direct engagement with code and decreasing system awareness. This lack of awareness introduces new challenges, particularly in maintaining security, performance, and reliability. This talk will explore the concept of software observability and discuss mechanisms that support debugging, fault diagnosis, anomaly detection, and AIOps. It will highlight examples from ongoing research in the telecom domain and examine how observability can address the gaps in system understanding created by LLM-assisted coding. The discussion will conclude with an analysis of broader challenges and research opportunities in advancing observability for the modern era.
Speaker
Naser Ezzati-Jivan, PhD, is an Associate Professor in the Department of Computer Science at Brock University, Ontario, Canada. His research focuses on Software Performance Engineering and Software Analysis, supported by over 16 years of experience as a professor, software engineer, and team leader. He has collaborated on several research projects with major industrial partners, including Google Montreal, Ericsson, and Ciena. An active member of the academic community, Nazer has served as a reviewer and program committee member for major journals and conferences. He completed his PhD at Polytechnique Montr茅al, where his thesis was recognized with a special mention award.
Event 2: AI for Malware and Authorship Analysis
Date: April 4, 2025
Time: 1 p.m.
Delivery Mode: Online
Language of Delivery: English
The seminar will start with an introduction to general concepts of machine learning followed by two research directions. The first research direction is to illustrate how to use AI for malware analysis. Assembly code analysis is one of the critical processes for mitigating the exponentially increasing threats from malicious software. However, it is a manually intensive and time-consuming process even for experienced reverse engineers. An effective and efficient assembly code clone search engine can greatly reduce the effort of this process. The second research direction is on authorship analysis for crime investigation. The objective is to identify the author or infer the author's characteristics based on their writing style.
Speaker
Prof. Benjamin Fung is a Canada Research Chair in Data Mining for Cybersecurity, a Full Professor of the School of Information Studies (SIS) at 9I制作厂免费, and an Associate Editor of Elsevier Sustainable Cities and Society (SCS). He received a Ph.D. degree in computing science from Simon Fraser University in 2007. Collaborating closely with the national defense, transportation, and healthcare sectors, he has published over 180 refereed articles that span across the research forums of data mining, machine learning, privacy protection, and cybersecurity with over 17,000 citations and h-index 60. His data mining works in crime investigation and authorship analysis have been reported by media, including the New York Times, BBC, CBC, etc. Prof. Fung is a licensed professional engineer in software engineering. See his research website for more information.
Event 3: Android Fragmentation: The Blessing and the Curse
Date: April 11, 2025
Time: 11 a.m.
Delivery Mode: Online
Language of Delivery: English
The world is going mobile. Android has surpassed its counterparts and become the most popular operating system all over the world. The openness and fast evolution of Android are the key factors that lead to its rapid growth. However, these characteristics have also created the notorious problem: Android fragmentation. There are numerous different Android device models and operating system versions in use, making it difficult for app developers to exhaustively test their apps on these devices. An Android app can behave differently on different device models, inducing various compatibility issues that reduce software reliability. Such fragmentation-induced compatibility issues (compatibility issues for short) have been well-recognized as a prominent problem in Android app development. In this talk, Professor Lili Wei will introduce the problem of Android compatibility issues, review the past efforts to address Android compatibility issues, and discuss potential research opportunities surrounding Android compatibility issues.
Speaker
Lili Wei is an assistant professor in the Department of Electrical and Computer Engineering at 9I制作厂免费. Prior to joining 9I制作厂免费, she received her Ph.D. degree and worked as a post-doctoral fellow at the Hong Kong University of Science and Technology. Her research interests lie in program analysis and testing with a focus on mobile apps, smart contracts and IoT software. Her research outcomes were recognized by several awards, including an ACM SIGSOFT Distinguished Paper Award, an ACM SIGSOFT Distinguished Artifact award, a Google PhD Fellowship and a Microsoft Research Asia PhD Fellowship. She is also actively serving the software engineering research community. She received a Distinguished Reviewer Award from ASE 2022. More information can be found on her personal website: .
