Mohammad Masudur Rahman is an Associate Professor in the Faculty of Computer Science at Dalhousie University. His research focuses on intelligent automation of software maintenance and evolution , combining Artificial Intelligence (AI) and Software Engineering (SE) to address challenges in bug detection, diagnosis, and reproducibility. He leads the RAISE Lab , which aligns with Dalhousie’s strategic goals in Advanced AI & Digital Innovation , particularly Sustainable Software Innovation and Sustainable AI . Dr. Rahman earned his PhD in Computer Science/Software Engineering from the University of Saskatchewan (2019), advised by Prof. Dr. Chanchal Roy, and completed a postdoc at Polytechnique Montreal under Prof. Dr. Foutse Khomh. He has published 50+ papers in top venues like ICSE , ESEC/FSE , ASE , and TOSEM , with research funded by NSERC Discovery Grant, Mitacs Accelerate International, and Dalhousie Startup Fund. His work investigates the challenges of software bugs, crashes, vulnerabilities, and technical debt , particularly in AI-driven systems like Large Language Models and Deep Learning frameworks. He develops tools to automate bug diagnosis, leveraging code structures and neural machine translation. Recent articles analyze deep learning bug reproducibility , fault diagnosis in attention models , and code smell impacts . Scientific Awards : Governor General's Gold Medal, U of S Doctoral Thesis Award, Dalhousie Belong Research Fellowship, President Gold Medal (Bangladesh). Grants : $475K+ (PI) and $4.3M+ (Co-PI) from NSERC, Mitacs, Climate Action Fund, and Dalhousie.
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Mark-David Hosale is an Associate Professor and Chair of Computational Arts at York University's School of the Arts, Media, Performance & Design (AMPD). He holds a BA in Music Composition from UC Santa Barbara. His work bridges computational art, performance, and architecture, focusing on worldmaking through interdisciplinary collaborations. Education: BA - Music Composition (UC Santa Barbara) Key Roles: Chair of Computational Arts, nD::StudioLab Director Research Labs: nD::StudioLab Research interests include the intersection of virtual and physical worlds, using digital fabrication and hardware/software integration to create immersive art. His theoretical practice centers on worldmaking —artworks that propose ontological alternatives through sensory experiences. Notable collaborations include the IceCube Neutrino Observatory and the PACIS project. His exhibitions span venues like SIGGRAPH, Dutch Electronic Art Festival, and Venice Biennale. Labs/Teams: nD::StudioLab, PACIS collaboration Grants: Multiple undisclosed research grants Labs include the nD::StudioLab, an experimental space for ArtScience research-creation.
Shin Kosekiمشاهده پروفایل
دانشیار
Shin Koseki is an Associate Professor at the Université de Montréal's Faculté de l'aménagement, specifically within the École d'urbanisme et d'architecture de paysage. He holds the UNESCO Chair in Urban Landscape and is actively involved in research on urban sustainability, AI integration in design, and democratic governance. His academic journey includes degrees from the École polytechnique fédérale de Lausanne (EPFL) and Université de Montréal. **Education**: BSc in Architecture, Université de Montréal (2007) MSc in Architecture and Urbanism, EPFL (2010) PhD in Architecture and Urbanism, EPFL (2017) **Research Focus**: Koseki explores justice and sustainability in urban territories, AI-driven design processes, and interactive democracy. His work bridges computational methods with urban sociology, analyzing spatial data to inform policy and design. Key themes include climate resilience, equitable public spaces, and the ethical governance of AI in cities. **Projects & Grants**: Principal investigator on initiatives like 'AI & Cities: Risks, Applications and Governance' (UNESCO-funded) and 'Densification solidaire dans Brome-Missisquoi'. Collaborates with international networks such as OBVIA and RRECQ. **Teaching & Mentorship**: Supervises PhD, master’s, and postdoctoral researchers. Teaches urban design, landscape architecture, and AI ethics. Leads interdisciplinary courses and oversees international student exchanges. **Awards & Affiliations**: Member of UNESCO chairs networks, OBVIA, and the VRM research group. Serves on university committees for sustainability, admissions, and ethics.
Richard C Austin is a Professor of Medicine in the Faculty of Health Sciences at McMaster University, where he conducts groundbreaking research at the intersection of cardiovascular disease, endoplasmic reticulum (ER) stress, and metabolic disorders. His laboratory investigates molecular mechanisms linking ER stress to atherosclerosis, kidney disease, and cancer progression. Dr. Austin's research focuses on ER stress pathways, particularly the roles of GRP78, TDAG51, and PCSK9 in disease pathogenesis. His work demonstrates how ER stress sensors regulate lipid metabolism, vascular calcification, and coagulation pathways. Recent studies reveal novel mechanisms where anti-GRP78 autoantibodies accelerate atherosclerosis and prostate cancer progression through tissue factor activation. His publication record shows consistent output in high-impact journals including Nature Communications , Circulation , and Journal of Biological Chemistry , with recent work emphasizing therapeutic interventions targeting ER stress. The 15 most recent articles demonstrate strong focus on PCSK9 regulation, chemical chaperones (4-phenylbutyrate), and novel biomarkers like GDF10 across cardiovascular, metabolic, and oncological contexts. Scientific Recognition: Elected Fellow of the Canadian Academy of Health Sciences (CAHS) Dr. Austin actively mentors through teaching Clinical Topics in Nephrology and Renal Disease (MEDSCI 768) and supervises research on ER stress mechanisms. His lab utilizes advanced mouse models including SR-B1/ApoE double knockouts and SR-B1-deficient mice to study diet-induced atherosclerosis. Current research explores caffeine derivatives for hyperlipidemia treatment and AI-driven drug discovery approaches. His laboratory maintains strong translational focus with work on chemical chaperones for atherosclerosis (4-phenylbutyrate), GRP78-targeting therapies for cancer, and PCSK9 inhibitors for lipid disorders. Recent collaborations examine ER stress in neurodegenerative conditions and childhood obesity.
Hoifung Poon is General Manager at Microsoft Health Futures and affiliated faculty at University of Washington Medical School. He leads Real-World Evidence (RWE) research focusing on AI applications for precision health. Poon earned a B.S. with Distinction in Computer Science from Sun Yat-Sen University and a Ph.D. in Computer Science and Engineering from University of Washington. Specializes in biomedical AI research Focuses on structuring unstructured medical data Co-PI for DARPA Big Mechanisms projects Research strength lies in biomedical multimodal learning (text, radiology, pathology, genomics) and causal learning for real-world evidence generation. His team develops methods for LLM self-verification , multi-modal fusion , and biases correction in observational data. Publications show expertise in Nature , Nature Methods , and NEJM AI , covering topics from digital pathology to clinical text analysis. Scientific recognition includes: Best Paper Awards at NAACL, EMNLP, and UAI Winner of ACM Health Best Paper Award Named Technology Champion 2022 by Puget Sound Business Journal
Frank Mollica is a Lecturer in Computational Cognitive Science at the Complex Human Data Hub , School of Psychological Sciences, University of Melbourne. He is also an Honorary Fellow at the Institute for Language, Cognition and Computation, School of Informatics, University of Edinburgh, and an associate member of the Center for Language Evolution at the University of Edinburgh. University: University of Melbourne , University of Edinburgh School: School of Psychological Sciences , School of Informatics Academic Rank: Lecturer Research Interests Frank’s research explores how humans construct conceptual systems supporting cognition and language, focusing on computational modeling and experimental methods. He investigates: Development of rich conceptual systems in children and adults Cognitive efficiency, diversity, and transmission Context-building in language processing Information-theoretic models of communication Publication Trends His recent work spans computational models of: Memory retrieval costs in semi-compositional systems Color perception and referential overinformativeness Lexicalization frequency across languages Context-sensitive word frequency effects Legal language accessibility Kinship term acquisition Labs & Affiliations Frank is affiliated with the Complex Human Data Hub (Melbourne), Institute for Language, Cognition and Computation (Edinburgh), and the Center for Language Evolution (Edinburgh).
Dr. Sean Bohun is a faculty member in the Faculty of Science at the University of Ontario Institute of Technology , where he has been active since 2006. He specializes in mathematical modeling and has coauthored a textbook on the subject, fostering collaboration between the mathematical sciences and other disciplines, fields, and industries. Education: PhD in Mathematics (1998) from the University of Victoria Global Engagement: Invited participant in international Study Groups for over 15 years Leadership: Co-organizer of Canadian Study Groups and mentor in graduate training workshops across Canada, the U.S., and Oxford Dr. Bohun's research focuses on breaking barriers between mathematics and applied domains, emphasizing interdisciplinary collaboration in industrial contexts. His work spans fluid dynamics, dynamical systems, and computational modeling, driven by practical applications. Scientific Awards: CAIMS-Fields Industrial Mathematics Prize (2015) As a mentor and organizer, Dr. Bohun has significantly contributed to graduate training and industrial mathematics initiatives, though specific student names and grants are not detailed in the provided text.
Philip Abrami is a Professor at Concordia University, specializing in educational technology and literacy education. His research bridges pedagogical innovation with technology to address equity and accessibility in learning. Key Research Areas: Educational Technology, Literacy Interventions, Instructional Design, Indigenous Education, and Ecological Curriculum Development. Abrami's recent scholarly work includes quasi-experimental studies on computer-assisted tutoring for early literacy, toolkits for technology-driven learning, and frameworks for fostering ecological thinking. His collaborations span international contexts, notably Northern Australia, and diverse educational stakeholders.
Dr. Glaucia Melo dos Santos serves as Assistant Professor and Co-op Program Director in the Department of Computer Science at Toronto Metropolitan University's Faculty of Science. She joined as a new tenure-track faculty member in Fall 2023, bringing expertise in adaptive artificial intelligence systems. Her educational background includes: PhD in Computer Science, University of Waterloo (2023) Master's in Computing Engineering, Universidade Federal do Rio de Janeiro (2018) BA in Information Technology, Universidade Estacio de Sa, Brasil (2009) Research interests focus on next-generation AI systems with emphasis on contextual adaptation and human collaboration. Her work bridges theoretical AI development with practical software engineering applications, particularly in autonomous systems and contextual language models. Professional recognition includes: Velocity 5k Pitch Competition winner (2022) Emerging Leaders in the Americas scholar, Global Affairs Canada (2017) As Co-op Program Director, she oversees industry integration for computer science students while teaching Database Systems (CPS 510). Her recent appointment indicates active research program development within the department.
Richard Hotte is a full Professor in the Department of Science and Technology at TÉLUQ University and holds the UNESCO Chair for Global Smart Disruptive Learning (GSDL). As director of the Institute for Research in Cognitive Computing and Training Environments (LICEF), he leads international collaborations in AI-driven educational innovation. Education: Doctorate in new information and communication technologies applied to training and communication from University of Paris 7 - Denis Diderot (1996) PhD in educational technology from Laval University, Quebec Master's degree in history (Popular arts and traditions) from Laval University, Quebec His research pioneers artificial intelligence integration in mobile learning, adaptive educational environments, and Serious Games. Hotte designed innovative courses using Larman's Rational Unified Process and led the Kids' Smart Mobile School project, focusing on context-sensitive learning systems and dynamic user modeling for personalized education. Advising and Grants: He supervises doctoral candidates in cognitive computing and information technology across Canada and Senegal, with current projects on autism support tools, collaborative mobile architectures, and conflict-zone learning applications. His UNESCO Chair facilitates transnational research partnerships in North America, Europe, and Africa. Labs and Teams: As LICEF director, he oversees research on intelligent learning environments and serves on the editorial board of STICEF (Sciences et Technologies de l'Information et de la Communication pour l'Éducation et la Formation).
- Artificial Intelligence in Education
- Generative AI for Education
- Machine Learning Algorithms
- +۷ مورد دیگر
Ange Adrienne Nyamen Tato serves as an Assistant Professor in the Department of Teaching and Learning Studies at Laval University's Faculty of Education. Her academic journey spans multiple institutions across Canada and Morocco, with a strong interdisciplinary background combining computer science, artificial intelligence, and educational theory. PhD in Computer Science (Artificial Intelligence) from University of Quebec at Montreal (UQAM), 2020 Master's degree in Computer Science from University of Quebec at Montreal (UQAM), 2015 Engineering degree in Information Systems from Mohammedia School of Engineers in Morocco, 2014 DEUST in Mathematics, Computer Science and Physics from Hassan II University, Morocco, 2011 Professor Tato's research focuses on the intersection of artificial intelligence and education, with particular expertise in generative AI applications for educational contexts, machine learning algorithms, intelligent tutoring systems, educational data mining, and serious game design. Her work addresses critical challenges in educational technology including transparency, assessment practices, and engagement issues that have limited the adoption of AI-powered learning tools. She is particularly interested in the ethical implications, environmental impact, and potential biases of AI in educational settings. Her recent publications demonstrate a consistent focus on developing sophisticated models for user behavior prediction, adaptive learning systems, and integrating pedagogical knowledge into AI frameworks. The research spans multiple domains including logical reasoning development, socio-moral reasoning, piloting training, and general educational applications of deep learning and knowledge tracing techniques. Professor Tato has secured significant research funding, including a $192,500 NSERC Discovery Grant for her project 'Optimizing Generative Artificial Intelligence for Education: Towards a Holistic Approach Integrating Teachers and Learners.' This five-year project aims to develop pedagogically aware large language models (PA-LLMs) that better serve educational purposes by integrating educational theories, human learning factors, and bias correction mechanisms. Principal Investigator for NSERC Discovery Grant ($192,500 over 5 years) PC Member for ICCE 2023 and 2024 conferences PC Member for EDM 2024 conference PC Member for AIED 2024 conference Professor Tato teaches graduate courses including TEN-7028 Games and Learning and TEN-7030 Digital Intelligence in Education: Opportunities and Challenges. She is currently accepting Master's students interested in AI applied to education. Her previous professional experience includes work as an Artificial Intelligence Specialist at Beam Me Up Augmented Intelligence (2018-2022) and a postdoctoral fellowship in Deep Learning applied to aeronautics in partnership with Bombardier and CAE (2020-2022).
Lavy Khoushinskyمشاهده پروفایل
استادیار
Lavy Khoushinsky serves as Assistant Professor in the Marketing Department at Laval University's Faculty of Administrative Sciences, where he maintains an active research program bridging analytical marketing, artificial intelligence, and consumer behavior. His work addresses critical contemporary challenges including ideological polarization in markets, healthcare access barriers, and ethical AI implementation. His educational foundation includes a Ph.D. from Smith School of Business, Master's in Sustainable Energy Policy from Carleton University, and Bachelor's in Communication from Concordia University. This interdisciplinary background informs his research approach that integrates technical marketing analytics with social impact considerations. Professor Khoushinsky's research program demonstrates remarkable thematic evolution from sustainable transportation (2019) through banking experience innovation (2020-2021) to his current focus on AI-consumer interactions in contested spaces. His 14 publications (2019-2025) reveal three dominant trajectories: AI-Mediated Consumer Interactions (50% of recent work): Examining chatbots, healthcare navigation systems, and accountability frameworks Ideological Market Dynamics (30%): Analyzing niche marketing in polarized environments and consumer discourse patterns Technology Adoption Barriers (20%): Studying privacy paradoxes, e-waste responsibility, and mixed-reality banking experiences His methodological approach combines computational linguistics with experimental design to address complex marketing phenomena. Through his teaching portfolio spanning Marketing Principles to AI applications, Professor Khoushinsky prepares students for evolving marketing landscapes. His course development emphasizes practical analytical skills while addressing contemporary ethical challenges in digital marketing. The collaborative nature of his publication record (80% co-authored) indicates strong team-based research practices and interdisciplinary connections across institutions.
- Production planning and control
- Adaptive manufacturing system
- Stochastic dynamic programming
- +۲ مورد دیگر
Adnène Hajji is a Full Professor at Université Laval's Faculty of Business Administration, specializing in Operations and Decision Systems. His academic journey includes a postdoctoral fellowship at Polytechnique Montréal, Ph.D. from École de technologie supérieure, and bachelor's degree from National Engineering School of Tunis. Research Focus: Professor Hajji's work bridges operations research and artificial intelligence, with core interests in: Production planning and control for unreliable systems Stochastic optimization in manufacturing/remanufacturing Hybrid AI models (deep learning + evolutionary algorithms) Sustainable operations and closed-loop supply chains Project scheduling under uncertainty His 50+ publications demonstrate consistent innovation in integrating predictive maintenance with production planning, developing optimization algorithms for engineer-to-order contexts, and applying data-driven approaches to healthcare and smart cities. Recent work shows strong emphasis on CNN-LSTM architectures and genetic algorithm hybrids. Student Supervision: Actively advises graduate researchers in industrial engineering and operations management, though specific student names aren't publicly listed.