Christian Desrosiers is a Research Professor at the Department of Software Engineering and IT, École de technologie supérieure (ÉTS), with a Ph.D. from Polytechnique Montréal. His research focuses on data mining, machine learning, and computer vision, particularly in medical imaging and optical network analysis. Research Units: Zebra Research Chair in Computer Vision for Industrial Applications, LIVE – Interventional Imaging Laboratory, LIVIA – Imaging, Vision and Artificial Intelligence Laboratory Research Axes: Intelligent and autonomous systems, Health technologies His expertise spans medical image analysis, domain adaptation, and computer vision. Recent publications highlight advancements in 3D point cloud learning, MRI harmonization, domain generalization, and real-time segmentation networks. Scientific awards include the prestigious Zebra Research Chair. He has co-supervised over 30 graduate students in topics ranging from optical network diagnostics to brain imaging and machine learning applications.
Jia Xue is an Associate Professor at the Factor-Inwentash Faculty of Social Work, University of Toronto, with a joint appointment in the Faculty of Information. She joined U of T in 2018 as an Assistant Professor and was promoted in 2025. Her research focuses on computational approaches to social justice issues, including intimate partner violence, rape myth culture, and AI ethics. She holds a Ph.D. from the University of Pennsylvania, a law degree from Tsinghua University, and postdoctoral training at Harvard University. Her research lab, the Artificial Intelligence for Justice (AIJ) Lab, develops AI tools to study social ills like image-based sexual abuse and school bullying. Key projects include AI-powered chatbots for sexual violence victims and analyzing biases in algorithmic systems. Funded by grants from Connaught, SSHRC, and CIHR, her work bridges social work, computer science, and policy analysis. Jia has authored over 50 peer-reviewed articles in journals like Journal of Interpersonal Violence and Child Abuse & Neglect . Awards include the Ontario Early Researcher Award (2025) and Deborah K. Padgett Early Career Achievement Award (2025). She leads initiatives at the Schwartz Reisman Institute for Technology and Society, focusing on tech’s societal impacts. Teaching emphasizes ethical big data use in social justice contexts. Recent work includes pandemic-related social media analysis and developing interventions for marginalized populations. Her interdisciplinary approach combines machine learning, policy analysis, and qualitative research to address systemic inequities.
Tejaswini Herath is a Professor of Information Systems at the Goodman School of Business, Brock University. Her research focuses on information security governance, mobile payment technologies, and the ethical implications of technology adoption. She has contributed extensively to understanding cybersecurity challenges, digital privacy, and the socio-economic impacts of emerging technologies. Her work often bridges technical and organizational aspects, emphasizing frameworks for risk management and innovation adoption. Recent studies include analyses of mobile payment systems in developing economies, cryptocurrency valuation ethics, and pandemic-era technology governance lessons. Her research spans interdisciplinary topics such as phishing susceptibility, user behavior in digital environments, and the integration of cybersecurity into organizational strategies. She has published over 50 peer-reviewed articles, with a focus on practical applications of theoretical models like Bayesian post-audit frameworks and technology-organization-environment (TOE) models. Her work addresses both academic and industry audiences, advocating for balanced scorecard approaches to security performance measurement. Tejaswini Herath is actively involved in curriculum development for information systems education, emphasizing student motivation and learning outcomes in IS courses. She collaborates with global institutions to study cross-cultural technology adoption patterns and policy implications.
Elaina Hyde is an Associate Professor in the Department of Physics and Astronomy at York University, serving as Director of the York Allan I. Carswell Observatory. She is affiliated with the Faculty of Science and eligible to supervise graduate students in the Physics and Astronomy program. Her research focuses on galactic archaeology, galaxy formation, and data science for astrophysics, leveraging cloud computing and machine learning. She has contributed to major initiatives like the GALAH survey and studies of the Sagittarius stream. Her work combines observational astronomy with technical leadership in telescope operations and public outreach. Hyde is also a certified Google Cloud Trainer and Engineer, integrating industry-level data science practices into academic and educational contexts. Education & Professional Background : While specific educational details are not listed, her roles indicate advanced expertise in astrophysics and data science. She has held technical and leadership positions in telescope operations and academic observatories. Research Interests : Hyde's work bridges computational and experimental astrophysics, emphasizing: Galactic archaeology via chemical and kinematic analysis of stellar populations Data-driven approaches to galaxy formation modeling Development of automated spectroscopic pipelines (e.g., GALAH survey) Machine learning applications for spectral classification and dimensionality reduction (e.g., t-SNE techniques) Astronomy education through public telescope access and interdisciplinary training Publications Overview : Her recent work focuses on the GALAH survey's chemical and kinematic inventory of the solar neighborhood, Sagittarius stream dynamics, and machine learning-enhanced spectral analysis. Key themes include stellar abundance trends in open clusters, tidal debris identification, and multi-survey data integration with Gaia. Labs & Teams : Leads the York Allan I. Carswell Observatory, fostering observational astronomy research and public engagement. Collaborates with global telescope networks and industry partners in cloud computing.
H.F. Machiel Van der Loos is an Associate Professor and Associate Head – External at the Department of Mechanical Engineering, University of British Columbia. He holds a PhD from Stanford University (1992) in human-robot interaction and a Diplôme d'Ingénieur from École Polytechnique Fédérale de Lausanne (EPFL). As Director of the CARIS Lab, his research focuses on rehabilitation robotics, roboethics, design methodology, and human-robot interaction in industrial contexts. He has authored over 50 peer-reviewed journal articles and 100 conference papers, and serves as Associate Editor for the Journal of Assistive Technology . His teaching includes core design courses such as the Capstone Design Project and cross-disciplinary 'Designing for People' courses spanning Computer Science, Applied Science, and Library Science. Van der Loos organized major conferences including IEEE ICORR 2013 and ICED17 at UBC. His work includes developing assistive technologies like power-assisted wheelchairs, AR interfaces for human-robot collaboration, and rehabilitation robots. The CARIS Lab emphasizes ethical considerations in corporeal robotics and user-centered design principles. Current research projects involve multimodal robot programming through AR, gesture-based interaction, and adaptive wheelchair control systems. His lab has collaborated with industry partners like JDQ Systems Inc. and Tableau to advance practical robotics solutions.
Souradeep Dutta is an Assistant Professor in the Department of Electrical and Computer Engineering within the Faculty of Applied Science at the University of British Columbia (UBC), joining in Fall 2024 after postdoctoral research at the PRECISE center, University of Pennsylvania. His academic credentials include a PhD in Electrical and Computer Engineering from the University of Colorado Boulder and a BE in Instrumentation and Electronics Engineering from Jadavpur University, India. Education: PhD, Electrical and Computer Engineering, University of Colorado Boulder BE, Instrumentation and Electronics Engineering, Jadavpur University, India Dr. Dutta's research centers on artificial intelligence with emphasis on reinforcement learning, cyber-physical systems, and formal methods. He investigates fundamental challenges in efficient data-driven learning and assurance techniques for learned models, targeting applications in robotics and medical devices. His work bridges theoretical guarantees with practical implementations for safe human-machine knowledge transfer. Analysis of his 15 most recent publications reveals dominant trends in robustness verification for learning-enabled systems, memory-based adaptation techniques, and distribution shift handling. His research consistently addresses safety-critical applications, particularly in medical diagnostics (e.g., ECG analysis, acne grading) and autonomous control systems, while maintaining strong theoretical foundations in formal methods. Awards: Recognition at top-tier conferences including ICLR, CORL, HSCC, ICCPS, ICAPS, NFM, L4DC, CHASE, and ADHS Dr. Dutta actively seeks graduate students for Fall 2025 and welcomes interdisciplinary collaborations. He serves on program committees for AAAI, ICCPS, ICML, and NeurIPS, and is available for undergraduate research supervision. His advising philosophy emphasizes safe and efficient transfer of human expertise to machine systems. He leads a research group at UBC focused on developing verifiable AI frameworks for cyber-physical applications, with current projects spanning medical device assurance and adaptive robotics control systems.
Leanne M. Currie is an Associate Professor at the UBC School of Nursing , part of the University of British Columbia's Faculty of Applied Science. Her work bridges nursing practice with health informatics, focusing on technology-mediated stigma reduction, usability design, and equity in digital health platforms. Nursing Informatics Health Information Technology Virtual Health Systems Stigma Reduction in Digital Platforms Equity, Diversity, and Inclusion (EDI) in Technology Community and Rural Health Equity Her recent research explores EHR compatibility, mHealth adoption, and the social determinants of critical illness recovery. She develops tailored digital tools for patient self-management and integrates Indigenous knowledge frameworks into health informatics curricula. Her work emphasizes human-centered design, safety in clinical technology, and cross-sectoral collaboration. Dr. Currie's publications highlight partnerships with healthcare providers to address technology-related safety events, co-design of person-centered apps, and the impact of digital tools on nurse emotional exhaustion. She actively contributes to defining anti-stigma design guidelines and advancing fair classification systems in health equity.
Matthew Brehmer is an Assistant Professor at the University of Waterloo, specializing in Human-Computer Interaction (HCI) and data visualization. His research focuses on ubiquitous information experiences, exploring innovative ways to communicate and collaborate around data through multimodal interfaces and interactive visualizations. He holds a PhD from the University of British Columbia (2016), an MSc (2011), and a BComp from Queen's University (2009). His research interests emphasize multimodal communication , data storytelling , and collaboration platforms . Notable themes include gesture-aware augmented reality video presentations, semantic alignment of text and visual data, and adaptive visualization systems for enterprise environments. He leads efforts in designing tools like RemixTape and VisConductor to enhance data-driven narratives and remote collaboration. Recent work trends highlight advancements in dynamic data presentation , context-aware visualization , and cross-platform integration . His projects address challenges in making data accessible and interactive across diverse user contexts, from mobile devices to enterprise systems. Matthew’s contributions span over 50 peer-reviewed articles, with a focus on IEEE VIS workshops and ACM venues. He actively engages with industry through collaborations on tools like QualDash for healthcare and Charticulator for bespoke chart design.
Jeff Lupker serves as an Assistant Professor at Western University's Don Wright Faculty of Music, specializing in the intersection of artificial intelligence and musical creativity. His work develops computational tools that augment human composition through deep learning algorithms and interactive systems, positioning him at the forefront of AI-driven music innovation. Lupker completed his entire academic training at Western University: PhD in Composition (2021) Master of Music in Composition (2016) Bachelor of Music in Theory and Composition (2014) His research program focuses on artificial intelligence applications for musical creation, including deep learning models for algorithmic composition, sentiment analysis of social media as compositional input, and mobile-based spatial audio systems. Lupker investigates how transformer architectures generate musical structures and how real-time web applications enable collaborative performance, emphasizing practical tools that combat writer's block while expanding composers' stylistic range through AI-assisted creativity in electroacoustic and popular music contexts. Analysis of his 2021 publications reveals a cohesive research trajectory leveraging cutting-edge AI methodologies to solve creative challenges in music. The works demonstrate how deep learning transforms composition through systems like Score-Transformer and explore mood-pattern recognition using machine learning, collectively establishing foundational work for human-AI creative collaboration that bridges music theory with big data analytics. As founder of Staccato, Lupker leads the development of an AI co-writing platform that functions as an intelligent creative partner. The system generates lyrical content from keywords and suggests musical continuations, helping composers overcome creative blocks while expanding artistic possibilities across diverse genres through accessible, user-friendly interfaces.
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.
Dr. Tim Patterson is a Professor of Environmental Geology at Carleton University's Department of Earth Sciences within the Faculty of Science. His research focuses on paleoclimatology, limnology, and geochemistry, employing micropaleontological, sedimentological, and geochemical techniques. Key areas include studying Holocene lake and marine paleoclimate records, assessing climate variability's impact on aquatic ecosystems, evaluating land-use change effects on lake/coastal-marine ecosystems, and evaluating ecosystem remediation success. Leading the Patterson Laboratory, affiliated with the Carleton Climate and Environmental Research Group (CCERG), Global Water Institute (GWI), and Carleton Northern Studies Program. Notable work includes defining the Anthropocene boundary using Crawford Lake's varved sediments and investigating road salt contamination, arsenic bioindicators, and Itrax-XRF core scanning methodologies. Research highlights include contributions to understanding Holocene climate variability, anthropogenic impacts on aquatic systems, and innovative methodologies for high-resolution sediment analysis. His lab develops tools like freeze core microtomes and FlowCam technology for rapid ecological assessments. Publications span 40+ years, with recent emphasis on Anthropocene stratigraphy, subarctic resilience, and heavy metal contamination in northern ecosystems. Collaborations include ArcticNet and Northern geoscience projects.
Dr. Christopher Collins is a Professor of Computer Science at Ontario Tech University, leading the Visualization for Information Analysis Lab (vialab). He holds a PhD from the University of Toronto (2010) and focuses on interdisciplinary research in information visualization, human-computer interaction, and natural language processing. His work addresses challenges in information overload, text analytics, and novel interfaces such as touch, pen, VR/AR. Collins' research has been featured in top-tier venues like ACM CHI and IEEE Transactions on Visualization and Computer Graphics, earning honorable mentions and over $3M in funding as sole PI. He serves on the IEEE VIS Executive Committee and Board of Governors at Ontario Tech University. Education: PhD in Computer Science, University of Toronto (2010) MSc in Computer Science, University of Toronto (2004) BSc (Hons) in Computer Science, Memorial University (2001) Research Interests: Collins' work spans information visualization , pen+touch interfaces , visual analytics , and text-driven systems . He explores how interactive technologies can democratize complex data analysis, particularly in education, healthcare, and creative domains. Recent projects include gaze-driven learning tools, context-aware camera interfaces, and bias-mitigating product review analysis. Awards: ACM CHI Honorable Mention Award IEEE VIS Honorable Mention Award Grants & Impact: Secured $3M+ in research funding. Media coverage includes New York Times and CBS Sunday Morning for innovations in visualization and text analytics. Teaches courses in human-computer interaction, computer graphics, and information visualization. Labs & Collaborations: vialab develops tools like Lexichrome , ConToVi , and NeuroSight . Active in IEEE Visualization and ACM Interactive Media communities. Collaborates with academia and industry globally.
Dr. Fei Chiang is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. Her research focuses on data management , with emphasis on data quality, data privacy, information extraction , and contextual data cleaning . She has collaborated with IBM Global Services and Microsoft Research on improving data quality in enterprise systems. Key research themes include graph databases , temporal data analysis , and privacy-aware data processing Recent publications explore federated learning , SQL understanding in LLMs , and temporal graph constraints Industry collaborations with IBM Toronto Lab and Microsoft Research have led to innovations in data cleaning automation and semantic analysis. Her work bridges database theory with machine learning applications in healthcare inventory optimization and flight reliability prediction.
Alessandra Ponte is a full professor at the École d’architecture of Université de Montréal. She has held teaching positions at Princeton University, Cornell University, Pratt Institute, ETH Zurich, and Istituto Universitario di Architettura di Venezia. Her research focuses on architecture's relationship with environment, mapping, and information systems, particularly in extreme landscapes and post-industrial contexts. Collaborated on CCA exhibitions: Environnement Total: Montréal 1965-1975 (2009) and God & Co: François Dallegret, Beyond the Bubble (2011-2014) Authored The House of Light and Entropy (2014) and Architecture et Information 2.0 series (2017-2020) Led research projects: Mining infrastructures in Québec (2014-2016), Architecture and Information 2.0 (2017-present), and Claiming the Planet: Post-Industrial Design Experiences (2020-2022) Her current work examines machine-generated spatial representations through drones, autonomous vehicles, and AI mapping systems. This research challenges traditional horizon-based aesthetics and explores non-human territorialization processes. Publications analyze how digital technologies reshape architectural practice and environmental understanding. She has contributed to journals like Landscript , Annals of Architectural Research , and New Geographies . Her students' research includes topics like Tunisian urban modernization, architectural branding, and digital mapping systems. She co-edited the book God & Co: François Dallegret, Beyond the Bubble (2011-2014).
Mehmet Akif Demircioglu is an Assistant Professor at the School of Public Policy and Administration, specializing in public sector innovation, digital transformation, and governance. His research focuses on the intersection of technology, policy design, and organizational behavior within public institutions. Key themes include digital ethics, demographic shifts impacting public innovation, and leadership strategies in crisis contexts like VUCA environments. His work spans global comparative studies, emphasizing Asia-Pacific contexts and European case analyses. Methodologically, he employs computational policy analysis, mixed-methods frameworks, and quantitative evaluation of innovation outcomes. He has contributed significantly to understanding how public organizations adapt to demographic changes and crises through strategic digital interventions. Notable contributions include studies on reverse knowledge spillover in public entrepreneurship, leadership's role in pandemic management, and the ethical dimensions of digital governance. His research bridges theoretical innovation frameworks with practical policy implementation challenges.
