Computer-Assisted Composition Professors and Supervisors in Canada | ApplySharif

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استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۱۶-۳۰ از ۱۵۸ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Marina Freire-Gormalyمشاهده پروفایل

استادیار

York UniversityCanada

Marina Freire-Gormaly is an Assistant Professor in the Mechanical Engineering Department at York University's Lassonde School of Engineering. Her research focuses on renewable energy-powered water treatment systems, machine learning for smart design, advanced manufacturing, and sustainable engineering solutions for remote communities. She holds a PhD and M.A.Sc. from the University of Toronto, specializing in carbon capture and storage technologies. She has worked on nuclear energy projects at Ontario Power Generation and contributed to World Bank sustainability assessments. She currently chairs the Canadian Society of Mechanical Engineers' Student and Young Professional Affairs committee. Education: PhD in Mechanical Engineering, University of Toronto M.A.Sc. in Mechanical Engineering, University of Toronto Research Interests: She pioneers solar-powered reverse osmosis systems, energy recovery mechanisms, and IoT-driven smart systems. Her lab explores nanotechnology applications in environmental sustainability, including carbon capture and aquatic remediation. She integrates machine learning for optimizing energy-water nexus challenges in off-grid regions. Key Contributions: Developed models for membrane fouling in desalination systems, advanced pore network characterization for geologic CO2 storage, and designed automated renewable energy systems. Her work bridges engineering innovation with global sustainability goals. Grants & Collaborations: Engages with industries like Honda Canada and Trane Canada on sustainability initiatives. Supervises graduate students in emerging areas like nanobubble technology and direct air capture systems. Lab Activities: The Freire-Gormaly Lab focuses on clean energy-water systems, with current projects involving nano-technology for space applications (Canadian Space Agency collaboration) and life cycle assessments of carbon storage technologies.

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Ji-young Shinمشاهده پروفایل

استادیار

University of TorontoCanada

Ji-young Shin serves as an Assistant Professor in the Teaching Stream within Education Studies at the University of Toronto Mississauga's Department of Language Studies. Her position integrates teaching, research, and practical application in language education with emphasis on assessment innovation and technology integration. Her academic credentials include: PhD in English / Second Language Studies & ESL from Purdue University, USA MS in Educational Psychology & Research Methodology from Purdue University, USA MA in Teaching English to Speakers of Other Languages (TESOL) from Hankuk University of Foreign Studies, South Korea BA in English Education (Japanese minor) from Hankuk University of Foreign Studies, South Korea Shin's research program focuses on language assessment, corpus linguistics, and technology-mediated pedagogy. She employs mixed methods with quantitative emphasis, utilizing corpus-informed computational analysis and latent-trait modeling complemented by qualitative discourse analysis. Her work addresses critical gaps in second language acquisition, educational measurement, and digital learning environments, particularly regarding AI applications and test validation across diverse language contexts. Her publication trajectory from 2017-2025 demonstrates consistent innovation in language assessment methodologies and technology integration. Key themes include AI-powered chatbots for L2 Korean instruction, online vocabulary testing for Spanish, and corpus-based writing pedagogy. Her work shows increasing focus on artificial intelligence applications and cross-linguistic validation studies, reflecting evolving priorities in language education research. Shin has secured competitive research funding including: Global Classrooms Grant (2025–2026) for VR-enhanced intercultural competence Black, Indigenous, and/or Racialized Scholar Grant (2025–2026) for cross-border AI language learning IRCC Engage3 Project (2022–2024) as Co-PI on VR/AI educational advancement Advancement Fund Plus (2022) for generative AI in teacher education British Council Award (2019) for technology-mediated assessment development She teaches advanced courses including 'The Future of Ed Tech: Active Learning Classrooms and Artificial Intelligence' (EDS285) and supervises community-based experiential learning (EDS388). Her grant portfolio indicates active supervision of research assistants and collaboration with international teams focused on AI implementation and assessment validation. Current projects explore generative AI for language learning across diverse contexts and virtual reality applications in teacher education. While specific laboratory infrastructure isn't documented, her collaborative publications with researchers across Korea, Spain, and the United States suggest participation in international research networks focused on language assessment technology and corpus applications.

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Vera Pantelicمشاهده پروفایل

استادیار مدعو

McMaster UniversityCanada

Vera Pantelic is an Adjunct Assistant Professor in the Department of Computing and Software at McMaster University. Her research focuses on software engineering practices for model-based development in automotive systems, particularly centralized Electrical/Electronic (E/E) architectures, Simulink modeling, and supervisory control of probabilistic discrete event systems. Education: Not explicitly mentioned in the text. Her scholarly activity includes extensive contributions to conferences and journals in automotive software engineering, model transformation, and real-time systems. Her work addresses challenges in modularity, documentation, and compliance within automotive embedded systems. Her recent publications emphasize advancements in centralized E/E architectures, model-driven testing, and assurance cases for automotive safety. She collaborates on topics integrating software engineering principles with automotive domain requirements. Scientific Awards: No specific awards mentioned in the text. She serves as an advisor in software engineering, though specific student names are not listed. Her projects involve simulation-based testing, model refactoring, and compliance frameworks, supported by industry partnerships and academic grants. Her work contributes to labs and teams focused on automotive software reliability and model-driven engineering. No explicit lab or team affiliations are detailed in the provided text.

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Shahrzad Esmaeiliمشاهده پروفایل

استاد

University of WaterlooCanada

Shahrzad Esmaeili is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. She holds a PhD in Materials Engineering from the University of British Columbia (2002), and master’s and bachelor’s degrees in Materials Science and Engineering from Shiraz University (1988, 1980). Her research focuses on processing-structure-property relationships in light alloys, metallic biomaterials, and additive manufacturing. She has expertise in phase transformations, surface modifications, and multi-length scale characterization. Notably, she received an Early Researcher Award from the Ontario Ministry of Research and Innovation. Her work bridges experimental and computational methods to study microstructural phenomena in aluminum and magnesium alloys. Recent publications emphasize non-isothermal annealing, precipitation hardening, and bio-structure fabrication. Education: PhD, Materials Engineering, University of British Columbia (2002) MSc, Materials Science and Engineering, Shiraz University (1988) BSc, Materials Science and Engineering, Shiraz University (1980) Research Interests: Her work integrates experimental and modeling approaches to study nanostructured materials, including metallic biomaterials and light alloys. Key areas include: Precipitation hardening mechanisms in Al-Mg-Si and Mg-Zn alloys Surface functionalization via laser-assisted deposition Additive manufacturing of porous titanium bio-structures Thermal-mechanical processing of aluminum composites Publications: Over 100 peer-reviewed articles span microstructural analysis, alloy behavior under thermal treatments, and biomedical applications. Recent trends focus on non-isothermal processing effects, microalloying strategies, and advanced surface modification techniques. Awards: Early Researcher Award (Ontario Ministry of Research and Innovation) Grants & Collaboration: Her research involves interdisciplinary collaborations, though specific grants are not detailed here. She leads studies on novel processing routes for high-performance alloys and biomaterials. Labs/Teams: Active in materials characterization and computational modeling groups at the University of Waterloo, focusing on multi-scale material analysis.

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A. Sherrattمشاهده پروفایل

استادیار

Western UniversityCanada

Infiltration and Cure Modelling for Composite Manufacturing
Wastewater Treatment and Flow Modelling
Thermal Energy Storage
+۵ مورد دیگر

A. Sherratt is an Assistant Professor in the Department of Mechanical and Materials Engineering at Western University, specializing in infiltration and cure modelling for composite manufacturing, wastewater treatment and flow modelling, and thermal energy storage. His work bridges computational methods with practical applications in mechanical engineering and materials science. Education: Ph.D., Mechanical and Materials Engineering, Western University (2022) MESc., Mechanical and Materials Engineering, Western University (2018) BESc., Mechanical and Materials Engineering, Western University (2016)

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Joshua M. Pearceمشاهده پروفایل

استاد

Western UniversityCanada

Dr. Joshua M. Pearce is a Professor at Western University, holding appointments in the Department of Electrical & Computer Engineering and the Ivey Business School. He is the John M. Thompson Chair in Information Technology and Innovation at the Thompson Centre for Engineering Leadership & Innovation and a Fellow of the Canadian Academy of Engineering. His research focuses on open-source appropriate technology for sustainability and poverty reduction, spanning solar photovoltaics, 3D printing, distributed recycling, and policy analysis. Ph.D. in Materials Engineering from Pennsylvania State University Former Richard Witte Professor at Michigan Tech Editor-in-Chief of HardwareX Author of multiple open-source sustainability books His work integrates engineering, economics, and policy to solve global sustainability challenges. Recent projects include agrivoltaic systems, open-source medical devices, and climate-resilient food production frameworks. He leads the Free Appropriate Sustainability Technology (FAST) research group, which has produced over 200 open-access publications cited in top-tier journals like Renewable and Sustainable Energy Reviews (IF=16.3) and HardwareX (IF=2). Dr. Pearce's scientific contributions include: Fulbright-Aalto University Distinguished Chair Top 0.06% most cited scientist (Elsevier metrics) Leading open-source hardware certification frameworks Developing low-cost scientific instruments His research team includes cross-disciplinary collaborators from Mechanical Engineering, Environmental Science, and Policy Studies. The FAST group emphasizes practical open-source solutions for energy, water, and food security in both developed and low-resource contexts.

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Graziano Fiorilloمشاهده پروفایل

استادیار

University of ManitobaCanada

Dr. Graziano Fiorillo is an Assistant Professor in the Department of Civil Engineering at the University of Manitoba's Price Faculty of Engineering. He holds a Ph.D. from the City University of New York and M.Sc./B.Sc. from the University of Naples, Italy. His research focuses on structural reliability, bridge systems analysis, and risk assessment, incorporating machine learning and high-performance computing. He has contributed to probabilistic frameworks for infrastructure resilience, filovirus outbreak modeling, and bridge redundancy evaluation. Education: Ph.D. Civil Engineering, City University of New York, 2016 M.Sc. Building Engineering, University of Naples Federico II, 2003 B.Sc. Building Engineering, University of Naples Federico II Research Interests: Dr. Fiorillo specializes in structural analysis of bridges, risk-based design, and machine learning applications in infrastructure. He develops probabilistic models for bridge network reliability and flood risk assessment, with a focus on Manitoba's infrastructure resilience. His work integrates computational fluid dynamics (CFD) and energy efficiency solutions for buildings. Publications: His recent work emphasizes interdisciplinary approaches to infrastructure challenges, including CFD for sediment transport, EnergyPlus-based building efficiency studies, and MPI parallel computing for reliability analysis. His 2024 studies on flood-overload interactions and additive manufacturing in construction highlight emerging trends in civil engineering. Awards: He received the 2012 New York State Intelligent Transportation Society Award for best student paper. His research has been applied to truck weight regulation strategies and bridge importance factor calibration. Advising & Grants: Offers M.Sc. opportunities in CFD, building energy efficiency, and bridge structures. Positions require expertise in OpenFOAM, EnergyPlus, or structural analysis software. No specific grants mentioned in the text.

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Mostafa Milaniمشاهده پروفایل

استادیار

Western UniversityCanada

Mostafa Milani is an Assistant Professor in the Department of Computer Science at Western University. His research focuses on data management, databases, and their applications in data cleaning, privacy, provenance, and fairness. Before joining Western, he held postdoctoral positions at the University of British Columbia and McMaster University, and earned his Ph.D. from Carleton University under Dr. Leopoldo Bertossi. Education: Ph.D. in Computer Science from Carleton University (supervised by Leopoldo Bertossi), Postdoctoral Fellowships at University of British Columbia and McMaster University. Research Interests: Data Quality, Privacy, Provenance, Fairness, Entity Matching, Query Optimization, and Database Systems. His work emphasizes ethical data practices and integrates machine learning for improved database interactions. He has contributed to projects like Building Trust in Data (privacy/fairness integration) and Unified Data Exploration (provenance and query recommendations). Courses taught include Databases I/II, Applied Logic, and Web Systems. Current advisees include 7 MSc and 1 PhD student. Former students have graduated across MSc and undergraduate programs. His research is supported by grants and collaborations, and he actively participates in program committees for top conferences like SIGMOD and VLDB.

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Gitanjali Kolhatkarمشاهده پروفایل

استادیار

McMaster UniversityCanada

Gitanjali Kolhatkar is an Assistant Professor in the Department of Engineering Physics at McMaster University and holds a Canada Research Chair in Bioinspired Smart Materials (Tier 2). She is also an Associate Member of the McMaster School of Biomedical Engineering. Her research focuses on developing smart materials for neuromorphic computing, leveraging ferroelectric materials to mimic synaptic functions while optimizing energy efficiency. Key techniques include microwave-assisted hydrothermal synthesis, magnetron sputtering, and advanced characterization methods like aSNOM and AFM-IR. Education: BSc and MSc in Physics, University of Ottawa (2008, 2010) PhD in Electrical Engineering, University of Sherbrooke (2014) Postdoctoral Fellowship, Institut National de la Recherche Scientifique (2015-2019) Alexander von Humboldt Fellow, University of Kiel, Germany (2019-2022) Research Interests: Neuromorphic materials, piezoelectric/ferroelectric systems, III-V semiconductors, thin films, photovoltaics, and smart sensors. Her work bridges material nanostructure and macroscopic properties to enable applications like artificial synapses, energy harvesters, and tactile sensors. Scientific Awards: Alexander von Humboldt Post-doctoral Fellowship Canada Research Chair (Tier 2) Invited Professorship at Munich University of Applied Sciences Teaching & Labs: Instructs courses in semiconductor devices (ENGPHYS 3PN4) and manufacturing (ENGPHYS 4Z04). Her lab (JHE A318/A313) focuses on interdisciplinary materials research. Current projects emphasize neuromorphic systems and bio-inspired smart materials.

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H.F. Machiel Van der Loosمشاهده پروفایل

دانشیار

University of British ColumbiaCanada

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.

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Leonie Baumannمشاهده پروفایل

استادیار

McGill UniversityCanada

Dr. Leonie Baumann is an Assistant Professor in the Department of Economics at McGill University, specializing in Economic Theory, Networks, Mechanism Design, and Game Theory. She holds a Ph.D. (summa cum laude) and M.Sc. in Economics from the University of Hamburg, and dual B.A. degrees from the University of Siegen. Currently on maternity leave, Dr. Baumann previously served as a Postdoctoral Research Associate at the University of Cambridge. Her research explores social interactions in microeconomic theory, with a focus on network formation dynamics, strategic evidence disclosure, and robust implementation mechanisms. Recent work examines how network structures influence economic decision-making and resource allocation. Dr. Baumann's publications demonstrate consistent focus on network economics and game-theoretic modeling, with emerging applications in discrimination mechanisms and evidence disclosure. Her methodological approaches combine theoretical rigor with computational innovations. Awards & Recognition: Vice-Chancellor's Innovation Award (2020) Econometric Society Travel Grant (2015) Multiple research grants including SSHRC and FQRSC funding Supervision & Service: Currently advising 4 doctoral students on topics ranging from biosolvent characterization to indoor air quality Active editorial board member for Journal of Mathematical Economics Organizes international conferences on economic theory

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Marta Kryvenمشاهده پروفایل

استادیار

Dalhousie UniversityCanada

Marta Kryven is an Assistant Professor in the Faculty of Computer Science at Dalhousie University. Her research integrates artificial intelligence, cognitive science, and experimental psychology to develop computational models of human cognition, focusing on planning, perception, and behavior. She is actively engaged in interdisciplinary research and is accepting graduate students. Research Interests: Computational models of cognition and behavior Large Language Models and their alignment with human thought Spatial navigation and environmental interaction Program synthesis and induction Representation learning and cognitive modeling Human-AI alignment and interpretability Her recent publications demonstrate a strong trend in combining symbolic AI with neural models to simulate human-like reasoning, particularly in spatial and social contexts. She frequently collaborates with leading researchers at MIT, especially Joshua Tenenbaum. Her work appears in top-tier venues such as NeurIPS, Cognitive Science, and Nature Computational Science. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Marta Kryven is currently accepting applications from graduate students and has several projects available for both undergraduate and graduate researchers. While specific grants are not listed, her active publication record in high-impact journals suggests ongoing funded research. She also offers consulting in AI system design, behavioral modeling, and data science for businesses. Labs and Teams: She is part of the Big Data Analytics, AI & Machine Learning research cluster at Dalhousie University. Her work is closely affiliated with cognitive science and AI research groups, likely involving collaboration with MIT’s Center for Brains, Minds and Machines. She leads a research group focused on human-like AI and computational cognitive modeling.

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Stella Daskalopoulouمشاهده پروفایل

استاد

McGill UniversityCanada

Dr. Stella Daskalopoulou is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) and a Professor in the Department of Medicine at McGill University's Faculty of Medicine and Health Sciences. She specializes in translational cardiovascular research with a focus on vascular health, atherosclerosis, and hypertension management. Senior Scientist, RI-MUHC Glen site Professor, Department of Medicine, McGill University Member, Cardiovascular Health Across the Lifespan Program Research Focus: Her work integrates biomedical technology with clinical investigation to identify early vascular impairment markers. Key areas include: Arterial stiffness and hemodynamic assessment Adiponectin signaling pathways in atherosclerosis Sex-specific cardiovascular risk stratification Biomarker discovery for plaque instability Pregnancy-related vascular complications Machine learning applications in plaque classification Scientific Engagement: Dr. Daskalopoulou contributes to hypertension guideline development (2024 ESC Guidelines) and explores environmental impacts on vascular health (household pollution studies). Her recent publications emphasize: Deep learning for plaque characterization Sex hormone receptor pathways in atherosclerosis Adipokine interactions with HDL metabolism Clinical decision tools for preeclampsia prediction Laboratory: Leads the Vascular Health Unit at RI-MUHC, combining histopathology, immunophenotyping, and advanced imaging for translational research.

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Zhao Zhaoمشاهده پروفایل

استادیار

University of GuelphCanada

Zhao Zhao is an Assistant Professor at the School of Computer Science, University of Guelph. Her work focuses on wearable systems, human-robot interaction, and gamification for health and education. She holds a PhD from Carleton University (2019) and completed a postdoctoral fellowship at the University of Toronto (2019–2023) before roles at McMaster University and her current position. Education includes a BSc in Computer Science from University of Electronic Science and Technology of China (2011), MSc from Carleton University (2014), and PhD in Electrical and Computer Engineering (2019). Research interests span physiological computing, AI-assisted creativity tools, and adaptive systems leveraging wearable sensors. Key research areas include: 1) Wearable-based gamification for health and education, 2) Emotion sensing via physiological signals, and 3) Human-robot interaction enhanced by wearable data. Her lab uses Empatica EmbracePlus wristbands and Emotiv EEG headsets to analyze real-time physiological responses in diverse interaction scenarios. Recent publications (2020–2025) emphasize personalized exergame systems, child-robot interaction studies, and AI linguistic competency analysis. She actively seeks graduate students and industry partnerships in wearable technology, education tech, and HRI.

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Jeff Lupkerمشاهده پروفایل

استادیار

Western UniversityCanada

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.

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