Stephen L. Bearne is a Professor in the Departments of Biochemistry and Molecular Biology and Chemistry at Dalhousie University, affiliated with the Faculty of Medicine. He has been a department member since 1996 and served as Department Head from 2012 to 2022. His research focuses on enzymology, enzyme catalysis, and protein engineering, with a particular emphasis on transition state analogues, enzyme inhibition mechanisms, and the chemical basis of disease-associated enzymes. His work integrates organic synthesis, biophysical techniques, and computational modeling to explore enzyme function and design inhibitors for therapeutic applications. Dr. Bearne holds a PhD from the University of Toronto and an MDCM from McGill University. His lab is part of the Protein Assembly Research Team and the BioActives CREATE Training Program. Current research themes include understanding carbon acid substrate catalysis in mandelate racemase, developing inhibitors for CTP synthase and racemases involved in diseases like cancer and neglected tropical infections, and proteomic tools for enzymatic activity profiling. His research leverages advanced techniques such as site-directed mutagenesis, isothermal titration calorimetry, NMR spectroscopy, and macroion mobility spectrometry. His lab supports equity, diversity, and inclusivity and has been funded by NSERC, CIHR, and other agencies. Recent publications highlight advancements in enzyme inhibition strategies, allosteric regulation mechanisms, and enzyme filamentation roles in metabolic pathways.
Arrvindh Shriraman is an Associate Professor and Program Director of Software Systems at Simon Fraser University's School of Computing Science in Surrey. His research focuses on energy-efficient software, multicore memory systems, and optimizing hardware/software interfaces for parallel programming. He holds a Ph.D. (2010) and M.S. (2006) in Computer Science from the University of Rochester, and a B.Eng. (2004) from the University of Madras. He teaches courses on parallel programming and energy-conscious software design. His research interests include synchronization mechanisms for domain-specific architectures, cache optimization, and FPGA-based acceleration. He has contributed to frameworks like Mu-grind for HLS-generated RTL instrumentation and TAPAS for parallel accelerator generation. Notable projects include RANGE-BLOCKS for synchronization in domain-specific systems and TapeFlow for gradient computation in neural networks. His work emphasizes real-time verification of autonomous systems and safety-critical trajectory planning for underwater vehicles. Shriraman collaborates closely with the Tangent Lab, exploring cutting-edge solutions in hardware-software co-design and embedded systems. His teaching and research bridge theoretical computer science with applied engineering challenges, addressing scalability, efficiency, and safety in modern computing systems.
Bertrand Jean-Claude serves as a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) at the Glen site and holds a Professorship in the Department of Medicine within McGill University's Faculty of Medicine and Health Sciences. His primary affiliation lies with the Metabolic Disorders and Complications Program under the Centre for Translational Biology. His research centers on innovative anticancer drug development, specifically focusing on the design and synthesis of multitargeted drug candidates engineered to simultaneously block multiple pathways in tumor cells. Key methodologies include kinase inhibitor development , molecular modeling , and pharmacokinetic analysis of combi-drugs—hybrid molecules designed for dual mechanisms of action such as EGFR receptor inhibition coupled with DNA damage. His publication history reveals consistent contributions to molecular oncology, with recent work emphasizing EGFR and DNA repair pathway dual targeting Fluorescence-based drug distribution tracking Overcoming P-glycoprotein-mediated drug resistance Stable combi-molecule fragmentation mechanisms His work bridges medicinal chemistry and translational cancer research, aiming to develop more effective tumor-selective therapies. Jean-Claude maintains active laboratory operations within the RI-MUHC's Centre for Translational Biology, where his team investigates combi-targeting strategies for oncology applications. His research program receives support through institutional frameworks of McGill University and the RI-MUHC, with emphasis on translating molecular discoveries into preclinical therapeutic candidates.
Vassilios Tzerpos is an Associate Professor at the Lassonde School of Engineering, York University, where he has been since 2001. He holds a Ph.D. in Computer Science from the University of Toronto (2001). His research focuses on audio processing for musical applications, deep learning, digital signal processing, machine listening, and software engineering education. He directs the APTLY lab exploring music-technology intersections and leads the LaSSoftE lab developing socially-oriented software solutions. Education: Ph.D. in Computer Science, University of Toronto, 2001 Research Highlights: Dr. Tzerpos' work spans music information retrieval (e.g., automatic music classification), synthetic speech detection using neural networks, and software engineering pedagogy. His recent projects include Music-STAR for audio re-instrumentation and OER-based learning path creation systems. He has pioneered methods in design pattern detection and software clustering evaluation. Grants & Labs: Leads two research groups: APTLY (music-tech) and LaSSoftE (social impact software). Active in developing adaptive cybersecurity solutions against DoS attacks and refining software architecture recovery techniques. Key Themes in Publications: Recent work emphasizes machine learning applications in music technology and cybersecurity, with foundational contributions to software clustering methodologies and design pattern detection algorithms. His work bridges theoretical computer science with practical applications in education and creative industries.
Tao Huan is an Associate Professor in the Department of Chemistry , University of British Columbia , and holds the Canada Research Chair in Metabolomics and Exposomics . His research focuses on advancing mass spectrometry (MS) for metabolomics , integrating bioinformatics to address challenges in cancer metabolism , disease biomarker discovery , and exposome characterization . Education: Ph.D. in Analytical Chemistry (University of Alberta, 2015), Postdoctoral Research Associate (The Scripps Research Institute, 2015-2018). Dr. Huan’s work emphasizes systems biology , combining metabolomics with genomics and proteomics to decode complex biological mechanisms. He has pioneered methods for chemical isotope labeling and multimodal data integration , enhancing metabolite identification and pathway analysis. His recent publications (2020-2019) highlight innovations in LC-MS/MS workflows , freeze-thaw sample stability , and applications in colorectal cancer and Alzheimer’s disease . Dr. Huan’s lab actively recruits students and postdocs in analytical chemistry, metabolomics, and bioinformatics. Awards: Fred Beamish Award (2025), President’s Award, Metabolomics Society (2025), UBC Killam Faculty Research Award (2024), Michael Smith Health Research BC Scholar Award (2023). He serves as a faculty member in UBC’s Graduate Program in Bioinformatics , Genome Science and Technology , and the Cluster for Microplastics, Health and Environment . Lab alumni include Ph.D. and M.Sc. students now in academia and industry.
Professor Timothy P. Bender is a distinguished faculty member at the University of Toronto, holding a primary appointment in the Department of Chemical Engineering and Applied Chemistry with cross-appointments in the Department of Chemistry and the Department of Materials Science and Engineering. His research laboratory focuses on developing novel organic electronic materials for applications in sustainable energy technologies, particularly organic solar cells and light-emitting devices. Professor Bender earned his B.Sc. and Ph.D. from Carleton University before joining the University of Toronto faculty in 2006. Prior to his academic appointment, he was a research staff member at the Xerox Research Centre of Canada from 2000-2006, where he filed over 65 US patents and published numerous peer-reviewed papers. His industrial research experience provides valuable perspective on the commercialization pathway for academic discoveries. Professor Bender's research program centers on the design, synthesis, and engineering of new materials for organic electronic devices, particularly organic photovoltaics (OPVs) and organic light-emitting diodes (OLEDs). His group has made significant contributions to the understanding and application of boron subphthalocyanines (BsubPcs) and silicon phthalocyanines (SiPcs), establishing methodologies for tailoring their chemical structure to optimize device performance. The Bender Lab employs a comprehensive 'applied chemistry-device continuum' approach, integrating computational modeling, synthetic chemistry, physical characterization, and device engineering to establish molecular structure-property relationships. Their research spans fundamental chemistry to applied device engineering, with strong emphasis on sustainability considerations throughout the materials development process. Analysis of Professor Bender's recent publications reveals a strong focus on developing BsubPcs as triplet harvesting materials in organic photovoltaics, engineering silicon phthalocyanines for enhanced electron transport, and exploring halogen bonding to control solid-state arrangements of these materials. His work demonstrates how molecular engineering can overcome traditional limitations in organic electronic materials, particularly regarding solubility, charge transport, and environmental stability. The research shows consistent progression toward higher efficiency devices with improved longevity. 2008 Professor Diran Basmadjian Teacher of the Year Award from the Department of Chemical Engineering and Applied Chemistry Corporate Special Recognition Award from Xerox Corporation for photoreceptor technology that enabled 'life of machine' parts Professor Bender actively mentors a diverse team of highly qualified personnel (HQP), including undergraduate students, graduate students, and post-doctoral fellows. His laboratory fosters cross-disciplinary collaboration between chemists, materials scientists, and chemical engineers, allowing students to engage with the complete research cycle from molecular design to environmental testing. He has secured funding from NSERC, SABIC Corporation, and other sources to support his research program, which maintains strong industrial partnerships with companies including SABIC Corporation, Siltech Corporation, and Xerox Corporation. His research bridges fundamental academic discoveries with practical commercial applications in the growing field of organic electronics. The Bender Laboratory maintains comprehensive infrastructure for organic synthesis, materials characterization, and device fabrication. Their facilities enable complete development cycles from molecular design to environmental testing of organic electronic devices. The lab's 'applied chemistry-device continuum' approach ensures that fundamental discoveries are rapidly translated into practical device applications, with particular emphasis on sustainability considerations throughout the materials development process. Current research directions include accelerated materials development, sustainable chemical processes, and life cycle analysis of organic electronic devices in real-world environments.
Muhammad Asaduzzaman is an Assistant Professor in the School of Computer Science within the Faculty of Science at the University of Windsor. His research focuses on software engineering, particularly software maintenance, mining software repositories, and recommendation systems for developers. Research interests span empirical studies of software artifacts, API usage analysis, and improving developer productivity through tools like COSTER for API element identification. Recent work examines dependency management in Maven ecosystems and AI-assisted code completion. Publications show consistent focus on analyzing developer activities through platforms like Stack Overflow and GitHub. Current investigations include LLM applications for code synthesis and technical debt impact analysis.
Sageev Oore is an Associate Professor in the Faculty of Computer Science at Dalhousie University, a Research Faculty Member at the Vector Institute for Artificial Intelligence, and a Canada CIFAR AI Chair. He previously served as Associate Professor and Chairperson in the Department of Mathematics & Computer Science at Saint Mary’s University and spent 2016–2018 as a Visiting Research Scientist at Google Brain, working on the Magenta team. Faculty of Computer Science, Dalhousie University Vector Institute for Artificial Intelligence Google Brain (2016–2018) Saint Mary’s University (former) Sageev Oore's research centers on machine learning and deep learning, with a strong focus on creative applications in music, audio processing, and computational creativity. His work bridges the gap between technical innovation and artistic expression, developing systems that generate and interact with music using neural networks. He has made significant contributions to generative models for music, including the development of PerformanceRNN and other interactive systems. His recent publications highlight advancements in out-of-distribution detection (Gram-OOD), interactive music generation, and deep learning tools for creative domains. These works reflect a consistent trend toward building intelligent, user-centered systems that enhance human creativity through AI. Canada CIFAR AI Chair (2018) Best Paper Award, CVPR ISIC Workshop (2020) Outstanding Demonstration Award (Runner-up), NeurIPS (2020) Best Demonstration Award, AAAI (2017) Best Demonstration Award, NeurIPS (2016) Sageev Oore actively mentors graduate and undergraduate students, with well-funded research positions available for motivated candidates. His collaborations span academia and industry, including major projects with Google Brain and interdisciplinary work with artists. He leads research initiatives in AI-driven creativity and is deeply involved in the Canadian AI ecosystem through the Vector Institute and CIFAR. His work is supported by significant grants and affiliations, including the Canada CIFAR AI Chair program, which funds his research in foundational AI and its applications. He is also part of the Magenta project at Google, contributing to open-source tools for art and music generation. Sageev Oore leads a research group focused on deep learning for creative applications, with projects in music generation, audio synthesis, and human-AI interaction. His lab collaborates with musicians, artists, and healthcare researchers, fostering a transdisciplinary approach to AI innovation.
Stephen Brown is a Professor at the University of Toronto within the Department of Electrical and Computer Engineering under the Faculty of Applied Science and Engineering. He earned his B.A.Sc and M.A.Sc in Electrical Engineering from the University of Toronto and New Brunswick, respectively, and a Ph.D. in Electrical Engineering from the University of Toronto (1992). His career spans over two decades in academia and industry collaboration. Education : B.A.Sc, University of New Brunswick M.A.Sc, University of Toronto Ph.D, University of Toronto Professor Brown’s research focuses on field-programmable gate arrays (FPGAs) , CAD algorithms , and computer architecture , with applications in machine learning and high-level synthesis . He is a principal investigator in the LegUp project , an open-source high-level synthesis framework that bridges software and hardware design. His work also extends to optimizing FPGA interconnect delays, physical synthesis, and logic block architectures. Key trends in his publications include advancements in high-level synthesis tools, FPGA architecture evaluation, and timing-driven design methodologies. His contributions often intersect with design automation , resource sharing , and embedded systems . Scientific Awards : NSERC 1992 Doctoral Prize Hart Professorship for Innovation in Teaching (2017) Multiple teaching excellence awards Best Paper Award at ICCAD 1990 Best Paper Award nomination at Canadian Conference on VLSI (1989) As Director of the FPGA University Program at Intel Corporation, he leads industry-academia initiatives. His teaching portfolio includes courses like ECE253 (Digital Logic) and ECE1733F (Switching Theory).
Michael Karas is an Assistant Professor of Applied Linguistics at Brock University's Faculty of Social Sciences. He holds a PhD from the University of Western Ontario (2019). His research focuses on language teacher self-efficacy, reflective practice, and learner silence, with notable contributions to meta-analyses in language education. He teaches courses such as Second Language Acquisition (LING 3Q91) and Pedagogical Grammar (LING 5P02). Karas serves as Book Review Editor for the TESL Canada Journal and TESL Ontario Academic Coordinator, demonstrating active engagement in academic service. Education : PhD in Applied Linguistics, University of Western Ontario (2019) Research Specialization : Explores intersections between teacher proficiency, classroom dynamics, and innovative methodologies like duoethnography. His work bridges theoretical research with practical applications in teacher education and language policy. Service Contributions : Editorial roles at TESL Canada Journal (2017–present) Coordinator for TESOL Doctoral Forum (2017–2018)
Dr. Laurel Young is a Professor in the Department of Creative Arts Therapies at Concordia University, specializing in music therapy with a focus on gerontology, palliative care, and neurodiverse populations. She holds certifications in the Bonny Method of Guided Imagery and Music (FAMI) and has over 23 years of clinical experience across geriatrics/dementia, oncology, HIV care, and developmental disabilities. Her roles have included Professional Leader of Creative Arts Therapies at Sunnybrook Health Sciences Centre and teaching positions at Wilfrid Laurier University and Temple University. Dr. Young’s research spans multicultural competence in therapy, ethical frameworks, and the intersection of music with health and well-being. Key themes include end-of-life care for dementia patients, singing groups for autistic adults, and bereavement support through music. She has published extensively in peer-reviewed journals and books, including editorial leadership for Barcelona Publishers’ Qualitative Inquiries in Music Therapy Monograph Series (2012–2013). Her work emphasizes bridging research and clinical practice, with a focus on marginalized groups such as older adults, individuals with disabilities, and those facing chronic illnesses. Awards include the 2014 CAMT Research & Publications Award and teaching accolades from Wilfrid Laurier and Temple Universities. Current projects explore AI-assisted therapeutic technologies and community-based music interventions.
Dr. Anne-Marie Nicol is an Associate Professor of Professional Practice in Health Sciences at Simon Fraser University. Her multidisciplinary research spans health communication, toxicology, social marketing, risk perception, and risk assessment, with emphasis on environmental and occupational health exposures. She leads CAREX Canada, a national carcinogen surveillance program, and has developed public health campaigns including Wash with Care and Tick Talk. Her work focuses on translating scientific information about carcinogens to policymakers and cancer prevention stakeholders. She teaches Human Health Risk Assessment, Toxicology for Public Health, and Health Communication. Her research has been funded by CIHR, Michael Smith Foundation, and Canadian Cancer Society. Current projects include studies on radon exposure, infodemic communication strategies, and community resilience to wildfire smoke. She holds a BA from SFU, MES from York University, and PhD from UBC.
Dr. Kibret Mequanint is a full Professor at Western University's Department of Chemical and Biochemical Engineering, with cross-appointments in Biomedical Engineering. Holding a PhD from University of Stellenbosch and postdoctoral experience at Technical University of Darmstadt and McMaster University, his research bridges polymer science, materials engineering, and life sciences with applications in Biomaterials , Tissue Engineering , and Regenerative Medicine . His work spans both fundamental and translational research in cell-material interactions , polymer biomaterial design , and therapeutic radiation dosimeters , with technologies transferred to commercial applications. Leading scholar and educator with awards from NSERC, CIHR, and Western University Fellow of: American Institute for Medical and Biological Engineering (AIMBE), Ethiopian Academy of Sciences, International Union of Societies for Biomaterials Science and Engineering, Canadian Academy of Engineering Extensive editorial and panel service for NSERC, CIHR, and international journals His research program has produced over 170 refereed publications, focusing on conductive hydrogels , bioadhesives , and vascular tissue engineering . Recent work on endoscopy-deliverable bioadhesives and snake venom-derived hemostatic gels has attracted global media attention. He has served in leadership roles at the Canadian Biomaterials Society and university governance bodies including Senate and Board of Governors.
Xujie Si is an Assistant Professor in the Department of Computer Science at the University of Toronto. He is also a faculty affiliate at the Vector Institute and an affiliate member at Mila - Quebec AI Institute, holding a Canada CIFAR AI Chair. Previously, he served as an Assistant Professor at McGill University's School of Computer Science. Education: Ph.D., Computer and Information Science, University of Pennsylvania (advised by Mayur Naik) M.S., Computer Science, Vanderbilt University B.E. (with Honors), Nankai University Research Focus: His work bridges AI and program reasoning, emphasizing the integration of statistical and logical methods. Key areas include: Static analysis and verification using deep learning/reinforcement learning Neuro-symbolic systems for urban simulation (e.g., LogiCity) Automated theorem proving via LLMs and symbolic reasoning Program repair and compiler fuzzing Recent Article Trends: Recent work focuses on synergizing LLMs with symbolic reasoning (e.g., Olympiad inequality proving), advancing SAT solving with graph neural networks, and applying neuro-symbolic methods to Euclidean geometry formalization. Awards: Canada CIFAR AI Chair (2023) Lab/Teams: Leads research teams exploring program analysis, neuro-symbolic AI, and formal verification at the University of Toronto and Vector Institute.
Ken Wong is an Associate Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. He also serves as Associate Chair within the same department. Holding a PhD in Computer Science from the University of Victoria (1999), his research focuses on software engineering challenges such as reverse engineering, program understanding, and software visualization. He emphasizes improving software evolution through tools like architecture recovery and root cause analysis, with applications in web/mobile platforms and diverse system understanding. Teaching highlights include developing Massive Open Online Courses (MOOCs) via Coursera, including the 'Software Product Management Specialization' and courses on Agile practices, client needs analysis, and software metrics. His recent publications (2023–2025) span AI-driven healthcare innovations (e.g., medical imaging, photoacoustic tomography) and advanced computer vision techniques (e.g., diffusion models, video inpainting). Notable collaborations include EVAREST studies on heart failure management and lung transplantation outcomes. His work bridges software engineering theory and practical applications in healthcare technology, with contributions to federated learning frameworks (e.g., FedLPPA) and AI-augmented clinical decision support systems. Research also extends to autonomous driving (DriveGPT4-V2) and 3D human avatar generation (DreamAvatar), showcasing interdisciplinary impact.
