جستجوی استاد راهنمای دانشگاهی

Colin Raffel , currently an Associate Professor at the University of Toronto and Associate Research Director at the Vector Institute , is a leading researcher in machine learning and natural language processing . His career spans roles at Hugging Face (Faculty Researcher), Google Brain (Senior Research Scientist), and UNC Chapel Hill (Assistant Professor). Education: PhD in Electrical Engineering (Columbia), MA in Music/Science (Stanford), BA in Mathematics (Oberlin) Key affiliations: Google Brain (2016-2020), Hugging Face (2021-present), Vector Institute (2023-present) His research focuses on language model development , attention mechanisms , efficient machine learning , and music information retrieval . Recent work explores model merging , parameter-efficient fine-tuning , and data-constrained language models . Teaching : Has instructed courses at University of Toronto and UNC Chapel Hill on Neural Networks , Deep Learning , and Information Theory . Academic service includes organizing ICLR workshops and serving as Senior Area Chair for NeurIPS and EMNLP . Notable awards : NSF CAREER (2022), Caspar Bowden Award (2023), NeurIPS Outstanding Paper (2023) Key contributions : Core developer of WT5 , Git-Theta , and mir_eval software

• Machine Learning
• Natural Language Processing
• Music Information Retrieval
• +۱۲ مورد دیگر

Ning Nan is an Associate Professor at the University of British Columbia's Sauder School of Business, specifically within the Department of Accounting and Information Systems. With a BA from Peking University, an MA from the University of Minnesota, and a PhD from the University of Michigan, Dr. Nan focuses on digital business strategy, evolvable IT infrastructure, and complex adaptive systems. His research explores blockchain applications, agent-based modeling, and the intersection of AI with societal challenges like sustainability. Education: PhD in Information Systems, University of Michigan MA in Information Systems, University of Minnesota BA in Computer Science, Peking University Research Interests: Dr. Nan investigates how technology shapes organizational and societal systems, with a focus on AI ethics, sustainability through personalized recommendations, and blockchain's role in decentralized supply chains. He employs agent-based modeling to simulate complex phenomena like innovation diffusion and online community dynamics. Recent work addresses explainable AI in smart cities and carbon-reduction gamification strategies. Teaching: In 2024-2025, he teaches Data Management for Business Analytics , emphasizing practical applications of data-driven decision-making. Key Research Themes: His articles highlight trends in AI sustainability (e.g., carbon footprint impacts of recommendation systems), digital business strategy (blockchain governance, app update strategies), and foundational IS theory (hyperturbulence and IS strategy).

• Digital business strategy
• Evolvable IT infrastructure
• Online community
• +۳ مورد دیگر

Gregory Paradis is an Assistant Professor in the Department of Forest Resources Management at the University of British Columbia (UBC) Faculty of Forestry. His research focuses on sustainable forest management, integrating operations research, mathematical optimization, and systems modeling to address complex interactions between ecosystems, industries, and society. He works with the FRESH Lab and collaborates with the Integrated Remote Sensing Studio, emphasizing ecological and economic integration in forest planning. Sustainable Forest Management Operations Research Forest Economics Data Science Risk Assessment GIS-based Methods His research spans forest inventory optimization, climate change adaptation strategies, wildfire risk modeling, and decision support systems for invasive species. He develops computational frameworks to enhance wood supply planning, carbon management, and ecological resilience. Recent work includes machine learning applications for fire safety in timber structures and automated road planning tools for wildlife conservation. Paradis’s publications highlight trends in applying optimization methods to sustainable forestry, with a focus on biodiversity, climate adaptation, and value chain innovation. He advocates for interdisciplinary approaches that bridge silviculture, industrial engineering, and data science to tackle emerging challenges in forest ecosystems. As an educator, he seeks motivated students with quantitative and creative problem-solving skills. His lab collaborates on remote sensing integration, risk assessment models, and policy-relevant forest management strategies, ensuring plans account for uncertainties like insect infestations or windthrow events.

• Sustainable Forest Management
• Operations Research
• Forest Economics
• +۷ مورد دیگر

Dr. Steven H. H. Ding is an Assistant Professor at McGill University's School of Information Studies, specializing in cybersecurity, machine learning, and data mining. His research focuses on AI-driven solutions for malware detection, software vulnerability analysis, and reverse engineering. He holds a PhD from McGill University and has been supported by BlackBerry Cylance and DRDC. His work bridges theoretical advancements with practical applications in military systems and avionics cybersecurity. Dr. Ding earned his PhD in 2019 with notable awards including the FRQNT Doctoral Research Scholarship and McGill's Dean’s Graduate Award. His educational background includes degrees from McGill, Concordia University, and the University of Shanghai for Science and Technology. His research interests span cybersecurity domains such as zero-day malware identification, code obfuscation countermeasures, authorship verification for digital forensics, and AI applications in avionics anomaly detection. He actively contributes to open-source tools like the Kam1n0 MapReduce-based assembly clone search system. Recent work emphasizes adversarial machine learning for evasive malware generation, transformer-based anomaly detection in avionics, and automated SBOM generation for firmware analysis. His publications reflect a focus on real-world cybersecurity challenges in both civilian and defense sectors. Dr. Ding leads the L1NNA Lab and collaborates with industry partners on cutting-edge projects. His contributions include novel techniques for phishing detection leveraging large language models and innovative approaches to reverse engineering software composition in JavaScript applications.

• Cybersecurity
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Yongjoo Park is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He leads research in data-intensive AI systems as a member of the Data and Information Systems (DAIS) lab, focusing on novel data systems that bridge database theory and practical AI applications. His work emphasizes open-source contributions through GitHub and direct societal impact. Research interests center on systems for data-intensive AI , particularly efficient Retrieval-Augmented Generation (RAG) systems for exploratory AI, data science versioning, and in-storage computing. Key projects include Kishu (the world's first undoable Jupyter notebook with time-travel capabilities), CARE (a causal-relational system for structured/unstructured data), and AirDB/AirIndex (serverless transactions and automatic index optimization). His group develops tools enabling scalable, optimized AI workflows from storage layers to LLM inference. Recent publications reveal a strong focus on interactive data systems (85% of recent work), with significant contributions to notebook environments (Kishu), vector databases (ISCA'25), and RAG optimization. Awards highlight technical innovation, including SIGMOD 2025 Best Demo Award and NSF CAREER funding. His open-source philosophy drives GitHub releases of all major systems. SIGMOD 2025 Best Demo Award (Kishu) NSF CAREER Award (Novel data science systems) SIGMOD'23 Best Artifact Award Honorable Mention (DeepOLA) IBM-Illinois Project Selection (VectorDB/RAG) Mentorship spans 12 current PhD/MS students and 6 graduated advisees, including Supawit Chockchowwat (now Postdoc at Google, future Assistant Professor at CMKL University). He teaches advanced courses like CS511 (Advanced Data Management) and recruits 1-2 new PhD students annually, prioritizing data systems research. His lab emphasizes diversity, individual respect, and concrete outcomes in a collaborative workspace.

• Data Systems for AI
• Retrieval-Augmented Generation (RAG)
• Database Systems
• +۴ مورد دیگر

Samer Faraj is a Professor and Canada Research Chair in Technology, Innovation & Organizing at McGill University's Desautels Faculty of Management. He leads the Research Group on Complex Collaboration and directs the PhD program. His research focuses on healthcare collaboration, innovation, and the impact of emerging technologies on organizations. He holds affiliations with the Department of Social Studies of Medicine and has been a visiting professor at institutions like HEC-Paris and Cambridge University. Faraj earned a BSc from the University of Wisconsin-Milwaukee (1980), an SM in Technology & Policy from MIT (1986), and a PhD in Management from Boston University (1998). His work has been funded by SSHRC, NSF, IBM, and the Quebec government, totaling over CAD $7.4M in grants. His research interests span healthcare collaboration, organizational change, and digital innovation. Notable contributions include studies on robotic surgery coordination, AI's role in organizing, and open-source health IT systems. He has authored over 130 peer-reviewed articles and serves on editorial boards for Organization Science and Information and Organization . Faraj has received prestigious awards like the FNEGE 2018 Prix Académique, AOM Best Paper Awards, and the 2013 Desautels Best Doctoral Advisor Award. His work is highly cited, with 23K+ Google Scholar citations. He advises numerous PhD students and leads interdisciplinary research initiatives, including a focus on postgenomics ecosystems and open science consortia. Current projects include the governance of open science, digital infrastructure development, and AI's implications for strategy and organization. His work bridges academic inquiry with real-world applications, emphasizing the societal and organizational impacts of technological change.

• Health Management
• Healthcare Collaboration
• Innovation Management
• +۶ مورد دیگر

Dr. Adegboyega Ojo is a Professor at the School of Public Policy and Administration (SPPA), Carleton University , holding the prestigious Canada Research Chair (Tier 1) in Governance and Artificial Intelligence since 2014. His work bridges digital government , AI governance , and smart city development , with a focus on public sector innovation and policy analytics . Research Interests Smart Cities and Urban Digital Infrastructure Open Government Data and Transparency Blockchain Applications in Public Administration AI Ethics and Algorithmic Governance Electronic Participation and Citizen Engagement Publication Trends : His research emphasizes interdisciplinary approaches to digital governance, often involving data-driven policy analysis , smart city frameworks , and open data platform design . Collaborations span institutions in Ireland, Poland, and the U.S., with citations exceeding 5,200. Scientific Awards : Canada Research Chair in Governance and AI (Tier 1) Labs & Teams : Collaborates with the Insight Centre for Data Analytics (Ireland), Delft University of Technology , and United Nations University on projects like OpenGovIntelligence and BOLD (Big and Open Linked Data).

• Digital Government
• Artificial Intelligence Governance
• Public Sector Innovation
• +۶ مورد دیگر

Olivia Di Matteo serves as an Assistant Professor in the Department of Electrical and Computer Engineering within UBC's Faculty of Applied Science, leading the Quantum Software and Algorithms Research (QSAR) group since her January 2022 appointment. Her academic foundation includes a BSc from Lakehead University and MSc/PhD in Physics (Quantum Information) from the University of Waterloo, completed in 2019. Dr. Di Matteo's research centers on quantum software engineering , with pioneering work in quantum compilation , circuit optimization , and debugging tools . She champions open-source quantum frameworks and develops accessible educational resources to democratize quantum computing. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in quantum programming infrastructure, particularly circuit analysis (33%), bug classification (20%), and qubit network optimization (15%), with strong emphasis on practical software tooling over theoretical physics. No scientific awards were documented in the source materials. She advises graduate students in the QSAR group while contributing to open-source quantum ecosystems through projects like PennyLane and The Ionizer transpiler, and teaches courses including CPEN 400Q (Gate-model quantum computing) and ELEC 221 (Signals and Systems). The QSAR group operates at the intersection of quantum software development and education, focusing on making quantum programming accessible through visual tools, real-time debugging environments, and hardware-agnostic compilation techniques.

• Quantum Computing
• Quantum Software Engineering
• Quantum Compilation
• +۵ مورد دیگر

Dominic Thibault is an Assistant Professor at the Faculty of Music, Université de Montréal . His research-creation explores human-machine interaction in musical contexts, focusing on embodied cognition through electroacoustic compositions, audiovisual performances, and musical software development. Co-director, Laboratoire Formes·Ondes Active member, CIRMMT (Centre for Interdisciplinary Research in Music Media and Technology) Research axis leader, Expanded Musical Practice (CIRMMT) Member, Québecor Millénium entrepreneurship committee Scientific committee member, ACFAS

• Digital Music
• Human-Machine Interaction
• Electroacoustic Composition
• +۳ مورد دیگر

Yuan Tian is an Assistant Professor in the School of Computing at Queen's University, Faculty of Arts and Science. She holds a PhD in Information Systems from Singapore Management University (2017) and a B.Sc. in Computer Science from Zhejiang University (2012). Her research focuses on integrating heterogeneous data sources to enhance software engineering practices, including data mining, recommender systems, and social network analysis. Prior to Queen's, she was a data scientist at Living Analytics Research Centre (LARC), SMU. She has held visiting positions at Carnegie Mellon University, INRIA Paris, and SAIL Canada. Research Interests: Data Mining Software Engineering Social Network Analysis Information Retrieval Recommender Systems Computer Security Recent Research Trends: Her work emphasizes AI-driven solutions for software bug management, code translation, vulnerability detection, and developer behavior analysis. Notable contributions include leveraging LLMs for technical debt repayment and enhancing code vulnerability detection via Graph Neural Networks. Awards: SMU Presidential Doctoral Fellowship (2015-2016) Best Paper Award at SANER 2017 Grants & Advising: No formal advisees listed, but active in collaborative projects with industry and academic partners. Labs/Teams: Previously associated with SOAR Group at SMU and currently leads research in Queen's School of Computing.

• Data Mining
• Software Engineering
• Social Network Analysis
• +۳ مورد دیگر

Ariel Katz is an Associate Professor at the Faculty of Law, University of Toronto, where he teaches intellectual property, constitutional law, cyberlaw, and the intersection of competition law and intellectual property. He holds an SJD from the University of Toronto and prior degrees from the Hebrew University of Jerusalem. His research focuses on the economic analysis of competition law and intellectual property, with additional interests in digital trade, pharmaceutical regulation, and constitutional issues. LL.B., Hebrew University (1997) LL.M., Hebrew University (2001) S.J.D., University of Toronto (2005) Professor Katz’s research interests lie at the intersection of law, economics, and innovation policy. He explores how intellectual property and competition laws shape markets, innovation, and access to knowledge. His work critically examines doctrines such as fair dealing, copyright exhaustion, and collective administration of rights, often from a comparative and transatlantic perspective. He investigates the economic rationales behind legal rules and their implications for digital platforms, libraries, and global research. His recent publications demonstrate a sustained engagement with copyright and antitrust policy, particularly in digital environments. Themes include text and data mining, fair use evolution, data governance, and the impact of trade agreements on domestic law. His scholarship frequently bridges legal theory and practical policy, influencing academic and public discourse. Notable recognition includes: The Canadian Association of Research Libraries (CARL) Award of Merit (2022) Professor Katz has advised on policy matters, including submissions on copyright term extension under CUSMA. He was Director of the Centre for Innovation Law and Policy (2009–2012) and has collaborated with scholars across North America. He maintains an active blog and has written op-eds in major Canadian newspapers. His work appears in leading journals such as the University of Chicago Law Review , Antitrust Law Journal , and BYU Law Review . He is affiliated with the University of Toronto’s Faculty of Law and contributes to SSRN and public intellectual forums. Professor Katz has been involved in digital scholarship initiatives and has written on the role of libraries in knowledge ecosystems. His work connects legal doctrine with broader societal challenges, including access to medicines, digital rights, and constitutional integrity, particularly in the context of Canada and Israel.

• Competition Law
• Intellectual Property Law
• Economic Analysis of Law
• +۷ مورد دیگر

Richard Pawlowicz is a Professor in the Department of Earth, Ocean & Atmospheric Sciences at the University of British Columbia (UBC), within the Faculty of Science. His research focuses on ocean physics, seawater properties, geophysical fluid dynamics, and coastal processes. He holds a PhD from the MIT/WHOI Joint Program and has been a faculty member at UBC since 1996. His work integrates field observations, numerical modeling, and novel instrumentation, such as neutrally buoyant floats (Swish floats) and satellite-tracked drifters, to study coastal circulation, estuarine dynamics, and double diffusion processes. He leads research in the Salish Sea, Strait of Georgia, and Gulf of St. Lawrence, emphasizing subsurface mixing, dispersion, and the impacts of climate change on marine ecosystems. Education & Background: B.Sc. (Hons) from Queen's University (1987), PhD from MIT/WHOI (1994), Postdoctoral research at Institute of Ocean Sciences (1994–1996). Research Interests: Ocean circulation, nonlinear waves, estuarine mixing, double diffusion in stratified basins, and the application of TEOS-10 seawater standards. He collaborates on projects like the MEOPAR Observation Core and has developed influential software tools for oceanographic analysis. Students & Supervision: Active supervisor of graduate students and postdocs in physical oceanography. Notable supervisees include Mark Halverson, Caixia Wang, Sam Stevens, and Grace Watts. He emphasizes mathematical rigor and writing skills, requiring strong backgrounds in PDEs and fluid dynamics. Labs & Teams: Member of the MEOPAR Research Management Committee, co-chair of SCOR/IAPWS/IAPSO seawater committees, and collaborator with the Pacific Salmon Foundation's citizen science programs. His work contributes to coastal resource management and climate resilience initiatives.

• Ocean Physics
• Seawater Properties
• Geophysical Fluid Dynamics
• +۵ مورد دیگر

Aurélie Labbe is a Full Professor in the Department of Decision Sciences at HEC Montréal, holding the prestigious FRQ-IVADO Chair in Data Science. Appointed as Co-Scientific Director – Academic Partnerships at IVADO in October 2023, she plays a key leadership role in establishing connections between IVADO and partner universities. Her academic journey includes a PhD in Statistics from the University of Waterloo, a Master's degree in Statistics from the University of Montreal, and dual Bachelor's degrees in Applied Mathematics and Social Sciences from Paris-Dauphine University and Pure Mathematics from Versailles-St Quentin University. Her research spans multiple interdisciplinary domains with a focus on developing advanced statistical and machine learning methodologies for big data analysis. Labbe's work bridges theoretical statistics with practical applications across diverse fields including genomics, neuroscience, transportation systems, and health informatics. She has made significant contributions to kernel methods, matrix factorization techniques, random forest applications, and spatiotemporal data analysis, with publications appearing in top journals across multiple disciplines. Analyzing her recent publications reveals a clear trend toward methodological innovation applied to complex real-world problems. Her work demonstrates expertise in handling high-dimensional data from diverse sources including neuroimaging, transportation networks, and genomic studies. The interdisciplinary nature of her research connects statistical theory with applications in healthcare, transportation safety, and biological sciences, reflecting her ability to develop methods that address domain-specific challenges while advancing statistical methodology. Holder of the FRQ-IVADO Chair in Data Science Member of the Center for Mathematical Research Training Professor Labbe actively mentors the next generation of data scientists, supervising numerous doctoral and master's students. Her supervision portfolio includes 1 doctoral thesis (2023), 4 master's theses (2022-2024), and 32 supervised projects spanning 2019-2025. Her students' work covers diverse applications including transportation safety, healthcare analytics, financial modeling, and environmental analysis. Through her leadership of the FRQ-IVADO Chair in Data Science, she coordinates research activities that integrate mathematical, statistical, and computer science expertise with domain knowledge from various data-generating fields. As Co-Scientific Director at IVADO, Professor Labbe leads efforts to establish connections with faculties and departments across five partner universities, integrating them into IVADO's research and knowledge transfer activities. Her leadership role positions her at the forefront of advancing data science research and applications in Quebec's academic ecosystem.

• Data Science
• Statistical Learning
• Machine Learning
• +۷ مورد دیگر

Zhen Ming (Jack) Jiang is an Associate Professor and York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems at York University's Department of Electrical Engineering and Computer Science. His research bridges software engineering, artificial intelligence, and computer systems with significant industrial impact. Dr. Jiang earned his Ph.D. from Queen's University's School of Computing and MMath/BMath degrees from the University of Waterloo's David R. Cheriton School of Computer Science. During his doctoral studies, he collaborated with BlackBerry's Performance Engineering team, developing tools now used daily to monitor commercial software systems. His research focuses on engineering rigor for AI-powered applications , software engineering evolution in the Generative AI era , and performance optimization of large-scale systems . Key areas include software performance engineering, mining software repositories, debugging distributed systems, source code analysis, and software visualization. His work combines empirical studies with practical tool development. Recent publications reveal strong trends in applying AI to software engineering challenges, particularly in machine learning systems reliability, blockchain efficiency, and AIOps solutions. His research consistently emphasizes empirical validation using real-world systems and industrial case studies. Scientific recognition includes: York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems NSERC Discovery Accelerator Supplements (DAS), 2020 Best Paper Award at ICST 2016 IEEE Software Best SEIP Paper at ICSE 2015 Ph.D. Research Achievement Award at Queen's University Multiple best paper awards at WCRE, MSR, and ICSE Dr. Jiang actively supervises graduate students and has secured competitive research funding including NSERC grants. His service includes program committee roles for top conferences (ICSE, ASE, ICSME) and editorial work for leading journals (TSE, TOSEM, EMSE). He leads research initiatives focused on foundation model-powered systems, collaborating with industry partners on performance monitoring and debugging solutions for large-scale distributed environments.

• Software Engineering
• Artificial Intelligence
• Computer Systems
• +۶ مورد دیگر

Dr. Sean K. Carey is a Professor in the School of Earth, Environment and Society at McMaster University, where he directs the Watershed Hydrology Group. His research focuses on hydrological and land surface processes in natural and human-impacted environments, with particular expertise in cold regions hydrology and northern environments. Dr. Carey holds a BSc (Hons) from the University of Guelph (1994), an MSc from McMaster University (1996), and a PhD from McMaster University (2000). His educational background established the foundation for his research in northern hydrology and climate change impacts. His research examines climate change processes and surface water hydrology, particularly in subarctic and alpine environments. Key interests include: Hydrological responses to climate change in cold regions Land surface processes in natural and disturbed landscapes Ecohydrological interactions in northern ecosystems Water resource management in mining-affected regions Long-term watershed monitoring and modeling Dr. Carey's extensive publication record focuses on hydrological processes in changing cold regions, with recent work examining permafrost interactions, watershed biogeochemistry, and ecosystem recovery in reclaimed landscapes. His research consistently addresses climate change impacts on northern water resources. He leads the Watershed Hydrology Group, which conducts field-based research across northern Canada including Yukon Territory and Alberta's oil sands region. Current work investigates the effects of climate warming on hydrological cycles and ecosystem functions in vulnerable northern environments.

• Climate change processes
• Surface water hydrology
• Hydrological processes
• +۲ مورد دیگر