Upcoming Computer Science seminars

Date: Friday, September 19, 2025
Time: 10:00 am – 11:00 am
Room: Shawenjigewining (SHA) Building – SHA 024

Google Meet Link: meet.google.com/hhz-doei-gpx

Presenter: Dr. Yann-Gaël Guéhéneuc (Professor, Computer Science and Software Engineering, Concordia university)
Host: Dr. Cristiano Politowski (Faculty of Science, Ontario Tech University)

Title: Empirical Studies on Software Quality

Abstract: Software quality has a tremendous cost, including in lives lost. Yes, software quality is difficult to define, measure, and improve. This presentation introduces software quality, focuses on maintainability, and the four aspects of maintainability that are of interest to software-engineering researchers: quality models, good practices, social studies, and developers studies. Then, it shows the importance of quality models and discusses metamodels, representations, measures. Finally, it describes and illustrates the concrete steps of the design of an empirical study: objective, design, data collection, practical considerations, data analyses, and application of the results.

Bio: Yann-Gaël Guéhéneuc is full professor at the Department of Computer Science and Software Engineering of Concordia University since 2017, where he leads the Ptidej team on evaluating and enhancing the quality of the software systems, focusing on the Internet of Things and researching new theories, methods, and tools to understand, evaluate, and improve the development, release, testing, and security of such systems. Prior, he was faculty member at Polytechnique Montréal and Université de Montréal, where he started as assistant professor in 2003. In 2018, he was awarded the NSERC Research Chair Tier I on Empirical Software Engineering for the IoT. In 2013-2014, for a sabbatical year, he visited KAIST, Yonsei University, and Seoul National University, in Korea, as well as the National Institute of Informatics, in Japan. In 2014, he received the NSERC Research Chair Tier II on Patterns in Mixed-language Systems. In 2010, he became IEEE Senior Member. In 2009, he obtained the NSERC Research Chair Tier II on Software Patterns and Patterns of Software. In 2003, he received a Ph.D. in Software Engineering from University of Nantes, France, under Professor Pierre Cointe's supervision. His Ph.D. thesis was funded by Object Technology International, Inc. (now IBM Ottawa Labs.), where he worked in 1999 and 2000. In 1998, he graduated as engineer from École des Mines of Nantes. His research interests are program understanding and program quality, in particular through the use and the identification of recurring patterns. He was the first to use explanation-based constraint programming in the context of software engineering to identify occurrences of patterns. He is interested also in empirical software engineering; he uses eye-trackers to understand and to develop theories about program comprehension. He has published papers in international conferences and journals, including IEEE TSE, Springer EMSE, ACM/IEEE ICSE, IEEE ICSME, and IEEE SANER. He was the program co-chair and general chair of several events, including IEEE ICPC'20 and '19, SANER'15, APSEC'14, and IEEE ICSM'13.

Past Seminars

Date: Friday, June 27, 2025
Presenter: Alessandro Visconti (PhD Candidate, GRaphics And INtelligent Systems Group, and the VR@POLITO Lab within the Department of Control and Computer Engineering, Politecnino Di Torino, Italy)
Supervisor: Dr. Fabrizio Lamberti (Full Professor of Computer Engineering, Chair PhD Programme in Computer and Control Engineering, Politecnico di Torino, Italy)

Title: Virtual presence and expression: The role of non-verbal communication in the Metaverse

Abstract: The rapid advancement of immersive technologies and growing interest in the Metaverse are reshaping how people communicate and connect beyond physical boundaries. Social virtual reality (VR) platforms allow users to interact through customizable avatars in shared virtual environments, offering novel opportunities for digital socialization. However, despite these advancements, replicating the richness of non-verbal communication remains a critical challenge. Human interaction relies heavily on gestures, facial expressions, body language, and other non-verbal signals to convey emotions, intentions, and engagement. Their absence in virtual settings reduces the sense of authenticity and weakens social presence. Recent research highlights how enhancing non-verbal expressiveness can significantly improve the realism and effectiveness of online interactions. This issue is particularly relevant as VR becomes more integrated into domains such as education, mental health, entertainment, and distributed teamwork. This presentation explores current limitations and emerging solutions aimed at enabling more expressive avatars and environments, such as facial tracking, gesture recognition, and AI-driven behavioral modeling. By bridging the gap between physical and virtual communication, we move closer to digital interactions that feel more human, intuitive, and emotionally engaging, paving the way for more meaningful social experiences in immersive contexts.

Bio: Alessandro Visconti received his B.Sc. and M.Sc. degrees in Cinema and Media Engineering from Politecnico di Torino in 2019 and 2021, respectively. During his studies, he developed a strong interest in immersive technologies, virtual reality, and AI-driven applications, which led him to pursue further research in these fields. He subsequently held a research fellowship, marking the beginning of his collaboration with the GRaphics And INtelligent Systems group and the VR@POLITO lab within the Department of Control and Computer Engineering. Currently, he is a PhD student in the same department at Politecnico di Torino, where he deepens his expertise in the design and development of real-time immersive applications. His primary focus areas are digital twinning, virtual presence, and enhancing social interaction within the metaverse. In particular, the aim of his research is to advance the Metaverse by devising strategies that leverage innovative consumer technologies and AI-driven methods, creating increasingly immersive, interactive, and socially engaging Metaverse experiences. Through his work, he strives to bridge the gap between users and digital environments, enhancing the realism and interactivity of virtual worlds and fostering a sense of true presence. His contributions have the potential to reshape user experiences and promote the Metaverse as a dynamic space for both social and professional interactions.

Date: Tuesday, November 19, 2024
Presenter: Dr. David Chandross (Department of Computer Science, Toronto Metropolitan University and Adjunct Professor, Game Development and Interactive Media Program, Ontario Tech University)
Host: Dr. Bill Kapralos (Faculty of Business and Information Technology, Ontario Tech University)

Title: Tripping the Light Fantastic, Psychedelic Science Applied to Teaching

Abstract: In this presentation we will explore how recent research on psychedelic psychotherapy impacts our views on the neuroscience of learning.

Presenter Bio: David Chandross holds a Ph.D. in curriculum for medical education, a M.Sc. in cognitive neuroscience, a M.Ed. in medical education. He has just completed 4 years of working with the WHO and the UN on game based learning. His clients include Baycrest Health Science, Alter Spark, U of T, CDN Armed Forces, Insurance Institute of Canada and other similar organizations.

Date: Wednesday, October 23, 2024
Presenter: Dr. Freda Shi (David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada.)
Host: Dr. Annie En-Shiun Lee (Faculty of Science, Ontario Tech University)

Title: Towards computational multilingualism with large language models

Abstract: In light of the remarkable accomplishments of recent large language models (LLMs), there arises a natural question on their multilingual capability, especially regarding low-resource and underrepresented languages. In this talk, I will discuss our results on cross-lingual reasoning with LLMs, where we investigate how pretrained models can be prompted to reason in a cross-lingual manner. Next, I will present our work that leverages multilingual LLMs for lexicon induction and, time permitting, cross-lingual dependency parsing. In line with existing literature, on the one hand, we show that the pretrained multilingual models benefit pre-defined cross-lingual NLP tasks across the board; on the other hand, the experimental results lead to a deeper understanding of what happens within these pretrained models.

Presenter Bio: Freda Shi is an Assistant Professor in Computer Science at the University of Waterloo, and a Faculty Member at the Vector Institute, where she also holds a Canada CIFAR AI Chair. She received her PhD in computer science from the Toyota Technological Institute at Chicago. Her research interests are in computational linguistics and natural language processing, as well as relevant machine learning aspects. Her work has been recognized by nominations for the Best Paper Award at ACL 2019, 2021 and 2024 and a Google PhD Fellowship.

Date: Wednesday, October 23, 2024
Presenter: Dr. Vered Shwartz (Department of Computer Science, University of British Columbia, Vancouver, Canada, and CIFAR AI Chair, Vector Institute, Toronto, Canada)
Host: Dr. Annie En-Shiun Lee (Faculty of Science, Ontario Tech University)

Abstract: Despite their amazing success, large language models and vision and language models suffer from several limitations. This talk focuses on one of these limitations: the models’ narrow Western, North American, or even US-centric lens, as a result of training on web text and images primarily from US-based users. As a result, users from diverse cultures that are interacting with these tools may feel misunderstood and experience them as less useful. Worse still, when such models are used in applications that make decisions about people’s lives, lack of cultural awareness may lead to models perpetuating stereotypes and reinforcing societal inequalities. In this talk, I will present a line of work from our lab aimed at quantifying and mitigating this bias.

Bio: Vered Shwartz is an Assistant Professor of Computer Science at the University of British Columbia, and a CIFAR AI Chair at the Vector Institute. Her research interests include commonsense reasoning, computational semantics and pragmatics, multiword expressions, and multimodal models. Previously, Vered was a postdoctoral researcher at the Allen Institute for AI (AI2) and the University of Washington, and received her PhD in Computer Science from Bar-Ilan University.

Date: Wednesday, October 2, 2024
Presenter: Dr. Jessie Galasso (Department of Electrical and Computer Engineering at the Faculty of Engineering, McGill University, Canada.)
Host: Dr. Cristiano Politowski (Faculty of Science, Ontario Tech University)

Title: Navigating the challenges of creating large, reproducible software datasets

Abstract: The collection and management of software datasets are fundamental to empirical software engineering. Defining and adopting proper data collection practices is essential to ensure the quality and reproducibility of research findings. In this talk, I will explore the challenges and limitations researchers face when selecting repositories from popular code forges. Specifically, I will address the issues that may hinder the reuse and reproducibility of software datasets. Following this, I will present solutions to support the creation and sharing of large, reproducible datasets of software repositories. These solutions are centered around the concept of dataset fingerprinting and leverage the unique features of the Software Heritage open archive.

Presenter Bio: Jessie Galasso is an Assistant Professor in the Department of Electrical and Computer Engineering at the Faculty of Engineering, McGill University, Canada. She received a Ph.D. in Computer Science in 2018 from the University of Montpellier, France. Her primary research interests focus on issues related to the management of software datasets, including software repository mining, knowledge extraction and representation, as well as variability management and modeling. In recent years, she has served as a program committee member for SANER'24 and ICSR'24, and has co-chaired several tracks and workshops at MODELS and SPLC.