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Each talk will be followed by a moderated live question and answer session.
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Interested in presenting a webinar? Check our page for prospective presenters to find out how.
Upcoming Webinars
Stay tuned for more webinars coming soon!
What do professional software developers need to know to succeed in an age of Artificial Intelligence?
Abstract:
The media is replete with anxieties about software developers losing their jobs when Generative Artificial Intelligence (AI) is capable of simpler developer tasks such as generating code. We arrive at a different conclusion based on our research with 21 industry developers on the cutting edge of using AI. Based on our findings, we argue that the risk is less around AI displacing the developer. Instead, the risk is that of the AI-augmented developer displacing the developer who neither reskill to keep up with AI tools nor upskill to be capable of realizing the productivity benefits that AI offers while managing AI’s risks. Our qualitative research draws on “Developing A CurriculUM” (DACUM), a methodology that has been widely used for job analysis, workforce training and the development of national occupational skills standards across more than 120 occupations in over 58 countries for more than 40 years.
In this talk, we first summarize how software development along the entire lifecycle is evolving as a result of AI impacting 12 broad developer goals, together with 75 associated tasks and the skills & knowledge corresponding to each task. We present a T-shaped framework that organizes all of these skills & knowledge into four domains, highlighting how imperative it is that developers both deepen and broaden their skills & knowledge to stay relevant in an age of AI. Next, we describe an AI task workflow that shows when and how these skills & knowledge need to be deployed in tandem for developers to use AI effectively. Finally, we show how K-12 educators, professors, workforce trainers, policy-makers and other leaders can use our 50-page occupational profile — a resource we are giving to the education community — to rethink Computer Science curricula for the AI era, so as to “future proof” current and future developers.
Speaker bios:
Matthew Kam is a research leader at Google focusing on the automation of work and future of workforce skills. He spearheaded research on AI’s impact on software engineering, cited in The New York Times, informing government and academic programs to upskill over 20,000 engineers globally so far. As a pioneering member of Google for Education, Matthew co-founded three applied research teams, and managed product development research that built Chromebooks, Google Classroom and Google Forms; improving lives for over 100 million students and teachers worldwide. Earlier in his career, Matthew was briefly an assistant professor of Human-Computer Interaction (HCI) in Carnegie Mellon University’s School of Computer Science, where he also played the role of scientific advisor in commercializing his academic research and his students’ projects (one successful acquisition, and one YCombinator alum). In the field of HCI, his academic research helped to pioneer the paradigm change toward human-centered design for equitable access to opportunity. Matthew’s training from the University of California, Berkeley bridges Computer Science (PhD, BS), Education (PhD minor) and Economics (BA).
Miaoxin Wang is an MBA candidate at the University of Virginia’s Darden School of Business, where she explores how technology, design, and human insight can come together to build responsible and forward-looking business models in the AI era. A former user researcher and full-stack developer, she brings seven years of professional experience connecting human-centered design with technical problem-solving. At Google, she focused on research at the intersection of AI, learning sciences, and software engineering, informing product strategies and user experiences used by global audiences. Earlier, at Groupon, she worked on performance optimization and A/B experimentation to make e-commerce systems more responsive and intuitive. Miaoxin holds an M.S. in Human-Centered Design and Engineering from the University of Washington and a B.S. in Computer Science from the University of Michigan. Her work centers on human-centered innovation and entrepreneurship that create lasting value for both people and business, guided by the belief that technology matters most when serving human well-being.
Vikram Tiwari is a Staff Machine Learning Engineer at ClickUp and a Google Developer Expert (GDE) in Google Cloud and Machine Learning, based in San Francisco. He brings extensive experience in building scalable AI systems, having previously served as Lead Machine Learning Engineer at Assembled and as Co-founder and CTO of Omni Labs. A dedicated community leader and open source advocate, Vikram regularly speaks at global conferences such as Google Cloud Next and DevFests, sharing his expertise on high-availability architecture and the practical applications of machine learning.
Date and Time:
January 9, 2026, 12pm-1pm EST
Click here to register for the webinar
Previous Webinars
Playlist of previous webinars is available on YouTube.
Building Global Software Engineering Pipelines: Lessons from Bangladeshi Graduate Talent and LLM-Driven Research
Abstract
Bangladesh has emerged as a strong and reliable source of high-caliber graduate students in software engineering, with several universities producing candidates well prepared for advanced research in North America. This talk highlights the University of Saskatchewan’s experience recruiting and mentoring students from institutions such as Khulna University, Brac University, KUET, IUT, EWU, and CUET. Students from these institutes have excelled in areas including software clone detection, empirical studies, scientific workflows, diversity in software engineering, and data-driven development. Their contributions span automated clone benchmarking, large-scale analytics, tool explainability, and open-science replication studies that enhance research rigour and accessibility. The talk also examines the growing role of large language models (LLMs) in software engineering research and how Bangladeshi graduate students have integrated LLM-based techniques into work on bug localization, code summarization, clone detection, and peer code review support. Examples of publications and collaborations illustrate how LLMs are being used not only for automation but also for deeper insight, interpretability, and robust benchmarking. Broadening the view, the talk highlights the strong potential across many Bangladeshi universities and offers practical guidance on identifying promising applicants, building sustainable research pipelines, and fostering cross-border collaborations grounded in open science and methodological transparency. By synthesizing lessons learned and emerging opportunities, the talk encourages deeper engagement with Bangladeshi institutions and shows how expanded recruitment can enrich research programs, diversify perspectives, and strengthen the global software engineering community.
Bio
Chanchal K. Roy is Director of the industry-stream, multi-University NSERC CREATE graduate program on Software Analytics Research (SOAR) and Software Research Lab (SRLab), and Professor of Software Engineering/Computer Science at the University of Saskatchewan (USask), Canada. Dr. Roy works in the broad area of software engineering, with particular emphasis on software clone detection and management, software evolution and maintenance, recommender systems in software engineering, automated software debugging, and big data analytics in software engineering. His contributions to the software maintenance community, and particularly to the software clones community have been highly influential, winning four 10-year Most Influential Paper awards at international conferences (ICPC 2018, SANER 2018, SANER 2021 and SCAM 2025). Recently, he was awarded with the Clones Lifetime Achievement Award, and became only the second person to receive this award. He has been recognized with the New Scientist Research Award of the College of Arts and Science at USask, the University wide New Researcher Award, GSA Advising Excellence Award and an Outstanding Young Computer Science Researcher Award by Canada’s computing research community, CS-Can/Info-Can. He has attracted over $6M in external funding since joining the USask, gave invited/keynote talks at numerous conferences, extensively served as organizing chairs and in program committees of international conferences and guest editors for journals. As the lead author of the widely used NiCad code clone detection system, he has published more than 250 refereed publications, with many of them in premier software engineering conferences and journals that have been cited more than 14,000 times with an h-index of 54 (Google Scholar). Dr. Roy has been (co-)supervising or has (co-)supervised over 110 highly qualified personnel including 24 PhD, 37 MSc and 7 postdocs.
Date and Time:
December 11, 2025, 10:30am-11:30am EST
Recording is available on YouTube
Software Developer Accountability in the AI Era
Abstract
Being accountable to one’s teammates has positive effects on teamwork and efficiency. In this webinar, we introduce a series of studies we have conducted on the nature of accountability in software teams. We introduce the concepts of institutional and grassroots accountability, and expand on how intrinsic drivers of accountability, like pride in one’s code quality, impact team dynamics. We conclude by examining how the introduction of AI tools in code review influence these feelings of accountability. Our findings imply that the introduction of AI into SE must preserve social integrity and collective accountability mechanisms.
Bios
Neil Ernst, PhD, is an associate professor at the University of Victoria in the Department of Computer Science and Director, Matrix Institute for Data Science. He is a world-leading researcher in software architecture and requirements. His research focuses on building next generation software systems. He leverages past experience consulting with large government stakeholders and empirical datasets on software development and analysis. Current projects include technical debt in scientific software, climate informatics, and the impacts of AI on human aspects of software development. Neil teaches in the software engineering program, covering courses on software architecture, requirements, and data science for software analysis. Neil holds a PhD in Computer Science from the University of Toronto, and previously worked at the Software Engineering Institute, Carnegie Mellon University, as a senior researcher. Currently:
- Director, UVic Matrix Institute for Data Science
- Senior Associate Editor, Journal of Systems and Software
- Associate Editor, Journal of Empirical Software Engineering, registered reports
- program committees - among others, at various times, ICSE, RE, XP, CAISE, ER, MODELS
Adam Alami is an Associate Professor of Software Engineering at the University of Southern Denmark (SDU). He possesses extensive experience in the information technology sector, with a career spanning over two decades. Initially a software developer, Adam’s professional journey has evolved to encompass business analysis and project management. He has contributed to numerous major IT transformation projects. His research interests are centered on the cooperative, social, and human aspects of software engineering. Adam is dedicated to exploring how software development teams can enhance the quality of their output. His research examines the processes, ceremonies, and the underlying behaviors, norms, and traditions that significantly influence their pursuit of quality. Adam holds a PhD in Computer Science from the IT University of Copenhagen, Denmark, a Master’s degree in Computer Science from the University of Technology Sydney (UTS), and a Bachelor’s degree in Software Engineering from the Université du Québec à Montréal (UQAM).
Date and Time:
September 25, 2025, 1-2pm ET
Click here to join the webinar
Quantum Software Engineering: Building Dependable Software for Quantum Computers
Abstract
Quantum computers are becoming increasingly powerful and accessible. For instance, it is now possible to access IBM’s quantum computers of up to 156 qubits via cloud services through open access. This opens up new opportunities for building novel quantum computing applications, which are enabled through quantum software. However, developing dependable software that runs on quantum computers and delivers these applications requires new software engineering methods. To this end, a novel field of Quantum Software Engineering (QSE) is emerging. This talk will introduce the field of QSE, covering various aspects such as requirements engineering, modeling, coding, testing, and debugging of quantum software. Moreover, the talk will discuss how classical AI can potentially assist in QSE activities and briefly touch on quantum artificial intelligence, which holds the potential to help with QSE. Finally, the talk will conclude by discussing open research questions and the outlook for future work.
Bio
Shaukat Ali is a Chief Research Scientist, Research Professor, and Head of the Department at Simula Research Laboratory in Oslo, Norway. He focuses on developing novel methods for creating cyber-physical systems by applying various advanced techniques, including artificial intelligence, digital twins, and quantum computing. He has led multiple national and European projects related to testing, search-based software engineering, model-based system engineering, and quantum software engineering. He is a co-founder of the International Workshop on Quantum Software Engineering at ICSE, the International Conference on Quantum Software, and the QC+AI workshop at AAAI. He represents Simula in various national and international quantum computing research and industrial networks.
Date and Time:
Tuesday September 9, 2025, 14:00-15:00 CEST (17:30-18:30 IST)
Recording:
Working with Non-Traditional Subjects; Lessons Learned from Using VR to Help Students with ADHD Focus
Abstract
Have you ever considered working with subjects other than traditional developers? For the past three years, we have done just that. We have found the journey full of new challenges and unexpected twists, but ultimately extremely rewarding. In this webinar we will detail our multi-year research project where we studied over 100 students with ADHD, helping them increase their focus on work using virtual reality headsets. Whether you are interested in studying students with ADHD, programmers with autism, or another non-traditional population, we walk you through the techniques and procedures, often outside of the typical computer scientists’ wheelhouse, that enabled our research. By the end of this webinar you will not only understand our findings on this particular project, you will understand what it takes to work with non-traditional subjects, populations that are often eager to engage with researchers and respond dramatically to the right interventions.
Bio
David Shepherd is an Associate Professor in the Department of Computer Science at Louisiana State University. He earned his Ph.D. and M.S. in Computer Science at the University of Delaware, and his B.S. in Computer Science at Virginia Commonwealth University. David has since worked as a postdoctoral fellow in the Department of Computer Science at the University of British Columbia, built sweat equity as employee #9 at Tasktop Technologies, and risen to Senior Principal Scientist at ABB Corporate Research. His research has produced tools that have been used by thousands, innovations that have been featured in the popular press, and practical ideas that have won business plan competitions. Dr. Shepherd currently serves as the Co-Editor-in-Chief of the Journal of Systems & Software.
Date:
Wednesday July 30, 10-11am ET
Recording:
From SBOM to Trusted Software Supply Chain: How Far Are We?
Dec 13, 2022 7:00 PM Eastern Standard Time
Registration and more information
Speaker: Xin Xia, moderator: Xing Hu
Abstract:
The security and transparency of the software supply chain have been an emergency problem met by the government, industry, and academia. Software Bill of Materials (SBOM), which records the ingredients that makeup software components, is widely used as a key building block to support the trusted software supply chain (TSSC). Except for SBOM, do we need to invent other technologies to support TSSC? What is the future road of TSSC? In this talk, I will present our recent progress in this area. I will introduce our initial works on SBOM generation and consumption, and then I will present our works relevant to vulnerability management (e.g., silent vulnerability bug reports and fixes identification, vulnerability detection, and CVE improvement) and supply chain attack prevention. Finally, I will briefly mention the future direction of TSSC.