Dr. Juergen Rilling is a Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on global software analytics, software traceability, knowledge modeling, and security vulnerabilities, with a strong emphasis on semantic web technologies. He leads projects in software evolution, mining software repositories, and integrating crowd-based data into development practices. His work bridges software engineering theory with practical tools like SeClone and SeByte, enhancing code analysis, dependency management, and security practices. Research interests include semantic modeling for security advisories, feature location via crowd-based screencasts, and API trustworthiness assessment. He has contributed to frameworks like SE-EQUAM for software quality metamodeling and Sv-AF for vulnerability analysis. His recent work explores machine learning applications in software ecosystems and developer behavior analysis through platforms like Stack Overflow. Publications span over two decades, with a focus on scalable clone detection, ontological approaches for traceability recovery, and integrating financial pattern analysis for software quality prediction. His tools and methodologies are applied in open-source ecosystems and industrial software maintenance contexts.
Tristan Glatard is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University . He holds a Canada Research Chair (Tier II) on Big Data Infrastructures for Neuroinformatics . His work focuses on reproducible research methodologies, neuroimaging analysis pipelines, and open science frameworks. Key contributions include developing tools like NeuroCI for continuous integration of neuroimaging results and VIP (Virtual Imaging Platform) for collaborative research. Research interests span neuroinformatics , reproducibility in computational science , big data architectures , and machine learning applications in healthcare . His projects address challenges in analytical flexibility, software dependency management, and numerical stability in neuroimaging workflows. He actively promotes open data sharing through initiatives like the Neuroimaging Data Model (NIDM) and Brain Imaging Data Structure (BIDS). Recent work emphasizes cross-platform reproducibility, leveraging containerization (Docker/Guix) and cloud-based solutions. He collaborates with international teams to validate neuroimaging pipelines and benchmark computational tools for large-scale biomedical data analysis. Notably absent from the profile are explicit mentions of academic awards or named graduate students, though his work has significant impact on research methodologies. He is deeply involved in open science advocacy through platforms like Brainhack and the Montreal Neuroinformatics Ecosystem.
Dr. Ching Yee Suen is a Professor and Director of the Centre for Pattern Recognition and Machine Intelligence (CENPARMI) at Concordia University. He holds an Honorary Chair in AI & Pattern Recognition. His academic roles include former Chairman of the Department of Computer Science and Associate Dean (Research) in the Faculty of Engineering and Computer Science. Education: PhD from the University of British Columbia (UBC) and Master's from the University of Hong Kong. Research focuses on pattern recognition, handwriting analysis, document analysis, computer vision, and applications in security (e.g., counterfeit detection). Key interests include font design, computational linguistics, and facial recognition. Awarded the IAPR King-Sun Fu Prize (2020), Elsevier Award (2016), and Gold Medal from the University of Bari (2012). Recipient of over 30 industrial grants and prestigious national/international awards. Founded major conferences: ICDAR, ICFHR, and Vision Interface (VI). Lab: CENPARMI, leading research in AI and pattern recognition. Supervised 130+ graduate students and hosted 100+ visiting scholars. Editorial roles include Emeritus Editor-in-Chief of Pattern Recognition and advisory roles in multiple journals.
Pankaj Kamthan is a Lecturer in the Department of Computer Science and Software Engineering at Concordia University. His work focuses on software engineering education, agile methodologies, and user-centric software development practices. He is particularly known for integrating innovative pedagogical techniques such as mind mapping into testing education and addressing gender equity challenges in software engineering fields. His research explores the intersections between academic and industry perspectives in software projects, the impact of remote work during the pandemic on software practices, and the ethical dimensions of user story engineering. He has contributed frameworks for analyzing software projects across sectors and frameworks for improving the credibility of web applications. Notable themes in his publications include curriculum design challenges, the role of socio-technical factors in requirements engineering, and leveraging social web environments for collaborative education. He has consistently emphasized practical applications of software patterns and agile principles in both teaching and industry contexts. No scientific awards were explicitly mentioned in the provided texts. His work has implications for improving educational outcomes, fostering inclusivity in STEM, and bridging gaps between academic theory and industrial practice in software engineering.
Jonathan Lessard is an Associate Professor at Concordia University's Department of Design and Computation Arts, Faculty of Fine Arts. He serves as a Primary Investigator for LabLabLab and holds the Behaviour Interactive Research Chair in Game Design . His research explores intersections of game design, history, and computational technologies. Education: PhD in Cinema Studies, Université de Montréal MA in History, Université de Montréal BA in Arts and Humanities, Université de Montréal Dr. Lessard's work focuses on emergent narratives , interactive storytelling , natural language interactions , and game design history , with technical expertise in 3D modeling, rendering, and computer graphics. His research spans playful technologies, possible worlds theory, and procedural dialogue systems. Research trends in his publications reveal deep engagement with game design methodologies , narrative systems , and procedural generation . Key contributions include tools for narrative analysis, documentation frameworks for game design, and explorations of language interaction in games. Scientific Awards: Behaviour Interactive Research Chair in Game Design Second Best Paper Award (Foundations of Digital Games, 2018) As a thesis supervisor at Concordia University, Dr. Lessard guides students in Design (MDes) , Individualized PhD Programs , and Humanities PhD Programs . His LabLabLab team develops experimental games like Chroniqueur and SimHamlet , with a focus on design research.
Gabriel Vigliensoni is an Assistant Professor in Creative Artificial Intelligence within the Department of Design and Computation Arts at Concordia University. He holds a PhD in Music Technology from McGill University and maintains active research and creative practice at the intersection of artificial intelligence, music, and human-computer interaction. His work spans academic research, artistic performance, and music production. PhD in Music Technology, McGill University Assistant Professor, Department of Design and Computation Arts, Concordia University Vigliensoni's research focuses on sound and music making through machine learning, human-computer interaction, artificial intelligence, embodied musical interaction, music information retrieval, and new interfaces for musical expression. His approach merges formal musical training with extensive experience in sound recording, music production, and computational techniques. His creative work challenges traditional notions of liveness and immediacy in digital music production through procedural composition and embodied interaction. His recent publications demonstrate a strong focus on interactive machine learning for creative applications, particularly in audio and music domains. The research trends show increasing emphasis on explainable AI for the arts, ethical considerations in AI music applications, and the development of interfaces that facilitate sustained artistic practice with machine learning systems. His work spans from theoretical foundations to practical implementations in musical interfaces. 2025-2027: Co-Applicant, New Frontiers in Research Fund—Exploration 2024–2025: PI, Petro-Canada Young Innovator Award (PCYIA) 2024–2025: Collaborator, Responsible AI UK international partnerships UKRI 2023–2025: PI, Explore and Create | Research Creation (Canada Council for the Arts) 2023–2025: PI, Faculty Research Development Program (Concordia University) 2022–2023: PI, Knowledge Mobilization Grant (FRQSC) 2020–2022: PI, Postdoctoral Research Creation (FRQSC) Vigliensoni supervises graduate students in Design (MDes), Individualized Programs (MA, MSc), and Individualized Programs (PhD). His research is supported by significant grants from Canadian funding agencies as well as international collaborations. His work bridges academic research with artistic practice, creating feedback loops between theoretical exploration and creative output. His studio practice and research involve developing interactive systems for musical expression, with notable projects including Clastic Music, Telematic Awakening, and Re•col•lec•tions. These projects often combine real-time audio processing, machine learning, and gestural interfaces to create novel musical experiences that explore the relationship between human performers and AI systems.
Delphine Hennelly serves as an Assistant Professor in the Department of Studio Arts within the LTA Fine Arts faculty at Concordia University, actively contributing to art education and creative practice in Montreal, Canada. Her research centers on Studio Art methodologies, encompassing: Visual Arts: Exploration of painting, sculpture, and multidisciplinary visual forms Contemporary Art: Critical engagement with current artistic movements and societal contexts Creative Media: Experimentation with traditional and emerging artistic media Artistic Process: Investigation of conceptual development and technical execution Exhibition Practices: Curatorial approaches and presentation methodologies No recent publications were documented in the source material, preventing analysis of research trends. Similarly, no scientific awards, teaching honors, or professional recognitions were referenced. The provided text contains no information regarding graduate student supervision, research funding, laboratory facilities, or collaborative artistic teams.
Bernard Gamoy is a part-time lecturer in the Department of Painting and Drawing at Concordia University. Born into a working-class family in Paris, he holds a B.F.A. (1979) and M.F.A. (1982) from Concordia. His artistic practice focuses on self-portraiture and explores the artist's societal role through low-key color palettes and layered techniques. Gamoy’s work has been exhibited internationally across Paris, Mexico, Boston, Toronto, and Montreal. Research emphasizes experimental painting processes, human touch in creation, and the interplay between space and intimacy. His artistic philosophy prioritizes exploration, accidents, and discovery in visual art.
Caroline Lindsay Hart is a Part-time Instructor in the Painting and Drawing department at Concordia University. She holds a BFA from Concordia University (1989) and a BA from Trinity College, University of Toronto (1976). A Montreal-based artist, her work spans oil painting, monotype, and collage, exhibited internationally for over two decades. Her art is included in major public and private collections and she is represented by Gallery D'Este. Education: BFA, Concordia University, 1989 BA, Trinity College, University of Toronto, 1976 Artistic Practice: Hart’s interdisciplinary approach combines traditional and experimental techniques in painting and printmaking. Her work explores themes of memory, identity, and urban landscapes through layered collages and monotype processes. Her exhibitions reflect a commitment to both local and global artistic dialogues. Representation & Impact: Represented by Gallery D'Este, her work engages collectors and institutions nationally and internationally. No specific grants or awards are documented, though her sustained exhibition record underscores her contributions to contemporary visual arts. Labs/Teams: No formal labs or collaborative teams mentioned in available materials.
David LeRue is an Assistant Professor in Art Education at Concordia University. He holds a BFA, MFA, and PhD, and works at the intersection of research-creation, qualitative research, and community-engaged pedagogy. His research examines the contradictions of community through participatory arts-based methods and oral history, exploring how grassroots interpretations shape place experiences. LeRue's research interests include dialectical philosophies applied to social and physical re-imaginings of community spaces, landscape painting pedagogies, and digital-physical integration in art practices. His work emphasizes inductive methodologies to decode place-based narratives. LeRue maintains office hours on Fridays from 10:00-12:00 at EV-2-817 and is available for thesis supervision in Art Education (MA and PhD programs).
Natalie Phillips is a Professor at Concordia University and holds the Concordia University Research Chair (Tier 1) in Sensory-Cognitive Health in Aging and Dementia. She is affiliated with the Department of Psychology in the Faculty of Arts and Science and collaborates with institutions like the Lady Davis Institute. Her research integrates behavioral and electrophysiological (ERP) measures to study cognitive aging and dementia. Research Themes : Cognitive aging, bilingualism, sensory-cognitive interactions, Alzheimer's disease, and executive function assessment. Awards : Recipient of the CIHR-Institute of Aging Age Award Collaborations : Involved in major initiatives like the COMPASS-ND study on dementia. Publications highlight her work on bilingualism’s role in cognitive reserve, sensory-cognitive tradeoffs in aging, and neurophysiological markers for early dementia detection. Her research bridges auditory neuroscience, neuropsychology, and clinical applications.
Inigo Novales Flamarique is a Professor in Neuroanatomy & Physiology at the Department of Biological Sciences, Simon Fraser University. He specializes in fish visual pathways, color and polarization detection, retinal neuron regeneration, and visual adaptations. His research interests focus on the neurobiological mechanisms underlying vision in aquatic species, with particular emphasis on how environmental factors influence photoreceptor development and function. Key projects include studies on CRISPR/Cas9 knockout effects on fish retinal development and the ecological role of polarization sensitivity in foraging behaviors. Publications highlight his work on opsin expression dynamics in salmonids, flatfish visual adaptations, and the functional segregation of retinal pathways. His lab is located in B8269 with a telephone extension 778-782-3512.
Kudret Demirli, PhD, PEng, is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on Lean Manufacturing, Lean Supply Chain, and Lean Healthcare, with a strong emphasis on integrating simulation and fuzzy logic techniques for process optimization. He teaches courses including Production Engineering (INDU 320), Lean Manufacturing (INDU 321), and graduate-level Production and Inventory Management (INDU 6211). His work bridges operational research and healthcare systems, addressing challenges in patient flow efficiency, resource utilization, and waste reduction in outpatient clinics and manufacturing systems. Dr. Demirli’s recent research highlights the application of lean principles to healthcare, such as developing frameworks for outpatient departments and oncology centers. He has also contributed to aerospace manufacturing through scheduling optimization in composite production systems. His methodologies often employ discrete-event simulation and fuzzy logic for uncertainty management, as seen in studies on steel rolling industries and automated defect detection in manufacturing processes. Dr. Demirli’s publications demonstrate expertise in both theoretical and applied aspects of lean systems, including maturity models, genetic algorithms for scheduling, and system modeling. His interdisciplinary approach spans healthcare, aerospace, and industrial engineering, emphasizing practical solutions for operational efficiency.
Suprio Ray is an Associate Professor in the Faculty of Computer Science at the University of New Brunswick, Canada, leading the Big Data Systems and Analytics Lab. He holds a PhD from the University of Toronto, an M.Sc. from the University of British Columbia, and a B.E. from NIT Trichy. Previously, he worked in industry roles at Oracle, Bell Labs, and Webtech Wireless, and completed a PhD internship at SAP. His research focuses on scalable data systems, spatial/spatio-temporal data management, and modern hardware utilization. Key projects include the Jackpine spatial database benchmark , DaskDB (a scalable data science system), and NUMA-aware query processing . He collaborates across disciplines with ECE and GGE departments, supported by grants from NBIF, NSERC, and industry partners. Research interests span Big Data systems, privacy/security in databases, blockchain analytics, and parallel/distributed computing. He has pioneered techniques like STILT multi-dimensional indexes , privacy-preserving spatial queries (Pystin) , and learned spatial indexes . Over 60 publications appear in top venues like SIGMOD, ICDE, and IEEE BigData. Education: PhD (Computer Science), University of Toronto (2015) M.Sc. (Computer Science), University of British Columbia (2003) B.E. (Computer Science & Engineering), NIT Trichy (2000) Teaching includes courses on big data systems (CS4545/6545), database foundations (CS6585), and data science (CS2545). He advises graduate students in scalable analytics and spatial systems, emphasizing industry-relevant software skills. Key awards include the 2024 ACM SIGSPATIAL best poster award , IBM Best Student Paper (2014) , and Harrison McCain Foundation award (2016) . His work has been recognized with 7 best paper awards and 3 patents. Current projects explore FPGA-accelerated joins , serverless data analytics , and privacy-preserving blockchain queries . Past contributions include the GEMM mobility model (2003) and foundational spatial benchmarks.
Dr. J Nelson Amaral is a Professor in the Department of Computing Science within the Faculty of Science at the University of Alberta. His research focuses on compiler optimization techniques that enhance performance in modern computing architectures through clever code transformations. Educational background includes B.Sc. in Electrical Engineering (PUCRS), M.Sc. in Electrical Engineering (ITA), and Ph.D. in Electrical and Computer Engineering (University of Texas at Austin). Research interests span compiler optimizations for resource utilization, learning technology applications in compilation processes, and feedback-directed optimization efficiency improvements. Current investigations include instruction-level parallelism exploitation, code transformations for heterogeneous architectures, and machine learning-enhanced compilation. Publication analysis reveals strong focus on compiler techniques for performance optimization, particularly for matrix operations, convolution algorithms, and memory hierarchy management. Recent work emphasizes hardware-software co-design for specialized processors and auto-vectorization methods. University of Alberta Faculty of Science Excellence in Teaching Award (2015) Distinguished Engineer, Association for Computing Machinery (2014) Distinguished Speaker, Association for Computing Machinery (2012-2014) Interdepartmental Science Students' Society Award for Excellence in Teaching (2014) IBM Center for Advanced Studies Research Faculty Fellow of the Year (2012) Research includes industry collaborations through the IBM-CAS partnership. Contributes to computing education through curriculum development and student mentoring. Leads compiler optimization research at the IBM Center for Advanced Studies, focusing on performance improvements for enterprise workloads and specialized hardware.
