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

نمایش ۳۱۶-۳۳۰ از ۳۵۰ استاد راهنما

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

Erik Hintzمشاهده پروفایل

استادیار

University of WaterlooCanada

Erik Hintz is an Assistant Professor, Teaching Stream and Academic Advisor at the Department of Statistics and Actuarial Science, University of Waterloo, Canada. He holds a PhD in Statistics (2022), MMath in Statistics (2016), and dual MSc/BSc degrees in Mathematics and Management from the University of Ulm and Waterloo. Education: PhD in Statistics, University of Waterloo (2022) MMath in Statistics, University of Waterloo (2016) MSc in Mathematics and Management, University of Ulm (2017) BSc in Mathematics and Management, University of Ulm (2014) Research Interests: Focuses on Monte Carlo and Quasi-Monte Carlo methods, copula simulation algorithms, statistical software development (e.g., the nvmix R package), and innovative teaching methods in mathematics. His work emphasizes computational efficiency and practical applications in multidimensional statistical problems. Publications Trends: Recent work centers on quasi-random sampling techniques, computational challenges in copula modeling, and software implementations for multivariate normal variance mixtures. These studies bridge theoretical advancements with real-world applications in finance and risk management. Awards: None explicitly listed in the provided materials. Advising & Grants: No formal advisees or grant information provided. His role emphasizes teaching and software development. Labs/Teams: Not specified in the text, but his collaborations with researchers like Matthias Hofert and Christiane Lemieux suggest involvement in computational statistics networks.

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Arie Gurfinkelمشاهده پروفایل

استاد

University of WaterlooCanada

Arie Gurfinkel is a Professor at the University of Waterloo, holding a joint appointment in the Department of Electrical and Computer Engineering and the Cheriton School of Computer Science. His research focuses on automated program analysis, software model checking, automated reasoning, and abstract interpretation. He develops tools like SeaHorn, Avy, and others to enhance the verification and testing of complex computer systems. His work emphasizes formal methods, machine learning integration, and hardware/software verification. Recent publications highlight advancements in interpolation-based model checking, constrained Horn clauses, and algorithm selection for hardware verification. Gurfinkel's contributions include open-source tools and frameworks widely used in academic and industrial verification efforts. He actively seeks motivated graduate students interested in logic, automated reasoning, and formal methods. His research has been presented in top-tier conferences and journals, reflecting his expertise in formal verification and software engineering.

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Michael Godfreyمشاهده پروفایل

استاد

University of WaterlooCanada

Michael Godfrey is a Professor at the University of Waterloo's David R. Cheriton School of Computer Science, affiliated with the Department of Electrical and Computer Engineering. His work focuses on software engineering, empirical studies of software systems, code review practices, and open-source software ecosystems. He holds a Ph.D., M.Sc., and B.Sc. from the University of Toronto (1997, 1988, 1986). Research interests include software evolution, mining software repositories, provenance tracking, code duplication analysis, and program comprehension. He actively explores how developers interact with code reviews, documentation systems, and modern CI/CD pipelines. Recent work investigates app store software ecosystems, Bash scripting vulnerabilities, and deep learning API testing. Publications span empirical studies of developer communities (e.g., Stack Overflow analysis), architectural teaching methods, and automated testing techniques like documentation-guided fuzzing. His work bridges theory and practice, addressing challenges in large-scale systems maintenance and developer productivity. Leverages tools like Elasticsearch for repository mining and explores anomaly detection in software development. Engaged in curriculum development for software architecture education and has contributed to conferences like MSR and ICSE.

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Meiyappan Nagappanمشاهده پروفایل

دانشیار

University of WaterlooCanada

Academic Profile Dr. Meiyappan (Mei) Nagappan is an Associate Professor at the University of Waterloo's Cheriton School of Computer Science. He holds a Ph.D. (2011) and M.Sc. (2008) from North Carolina State University, and a B.Sc. from Anna University, India (2006). Research Focus His research spans empirical software engineering, mining software repositories, and mobile app store analysis. Current investigations focus on software security, static analysis techniques, and diversity in software engineering. Recent work critically examines AI programming assistants like GitHub Copilot, evaluating their performance, security implications, and impact on developer workflows. Key Research Areas Diversity analysis in open-source contributions and academic publishing Vulnerability detection using machine learning Bug localization and automated debugging Cross-platform app analysis Publications Research demonstrates strong focus on empirical validation of developer tools, with recent emphasis on AI-assisted programming. Work appears in top software engineering venues covering security, testing, and developer productivity.

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Shane McIntoshمشاهده پروفایل

دانشیار

University of WaterlooCanada

Shane McIntosh is an Associate Professor and Associate Director of Graduate Studies at the Cheriton School of Computer Science, University of Waterloo. He holds a Ph.D. from Queen's University (2015) and specializes in empirical software engineering, software delivery processes, and software quality improvement through data mining techniques. His research focuses on analyzing historical and operational data from large-scale software systems to derive actionable insights. Key areas include release engineering, DevOps optimization, and software quality enhancement. McIntosh employs empirical methods to study build systems, continuous integration practices, and defect prediction. McIntosh's recent publications demonstrate a strong focus on improving software development workflows through empirical analysis of build systems, CI/CD pipelines, and code quality metrics. His work frequently addresses efficiency optimization in development operations and vulnerability detection in machine learning systems.

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Robert Nishidaمشاهده پروفایل

استادیار

University of WaterlooCanada

Robert Nishida is an Assistant Professor at the University of Waterloo, holding professional engineering (PEng) certification. His research focuses on aerosol dynamics, fuel cell technology, and advanced sensor development. He specializes in computational fluid dynamics (CFD), heat and mass transfer phenomena, and the design of precision instruments for environmental and industrial applications. His work spans aerosol measurement techniques, including bipolar and unipolar charging systems, as well as high-precision sensors for particle analysis. Notable contributions include open-source modelling frameworks for aerosol dynamics and fuel cell performance optimization. Recent studies address SARS-CoV-2 transmission via aerosols and droplets, integrating virology with engineering solutions. Nishida’s research also explores solid oxide fuel cell stacks, emphasizing thermal management and electrochemical performance. He develops novel catalysts for carbon nanotube synthesis and has pioneered methods for measuring nanoparticle charge distribution using the Aerodynamic Aerosol Classifier. His interdisciplinary approach bridges environmental science, energy systems, and advanced instrumentation. His publications emphasize practical applications of computational models and sensor technologies, with a focus on real-world validation through experimental setups. While no specific awards or grants are listed, his prolific output in high-impact journals highlights his expertise in aerosol engineering and energy systems.

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Roger Melkoمشاهده پروفایل

استاد

University of WaterlooCanada

Roger Melko is a Professor at the University of Waterloo, affiliated with research groups focused on Quantum Information & Computing and Quantum Matter. His work bridges quantum physics, machine learning, and computational methods to advance understanding of complex quantum systems. He is a prominent figure in applying neural networks to quantum state reconstruction and quantum simulation. Research interests span quantum computing architectures, condensed matter physics (e.g., quantum spin liquids, Hubbard models), and leveraging machine learning for quantum phase transitions, entanglement analysis, and device optimization. His contributions include neural network wavefunctions, quantum-assisted generative models for particle detection, and economic analysis of quantum technologies. Recent articles highlight advancements in quantum simulation using recurrent neural networks, hybrid quantum-classical algorithms for high-energy physics, and robust quantum dot autotuning. His work emphasizes interdisciplinary approaches, integrating AI with quantum hardware development.

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Jabed Tomalمشاهده پروفایل

دانشیار

Thompson Rivers UniversityCanada

Jabed Tomal is an Associate Professor in Statistics and Data Science at Thompson Rivers University (TRU), Canada. Previously, he held positions as an Assistant Professor at TRU (2018–2023) and the University of Toronto Scarborough (2014–2018), and a Postdoctoral Fellow at the University of British Columbia (2014). He earned a Ph.D. in Statistics (2013) from UBC, specializing in statistical machine learning, and dual M.Sc. degrees in Statistics (University of Windsor, 2007) and Biostatistics (University of Dhaka, Bangladesh). His research focuses on ensemble methods, Bayesian inference, and statistical ecology, with applications in drug discovery, protein homology, and environmental modeling. Key research interests include developing ensemble models for high-dimensional data, Bayesian methods for breakpoints detection in housing markets and ecological systems, and statistical approaches in healthcare. Notable contributions include work on QSAR studies, Bayesian hierarchical modeling of pandemic impacts, and ecological threshold detection. Tomal has secured grants such as the NSERC Discovery Grant ($102,500) and TRU internal funds for projects in big data and environmental thresholds. He has advised numerous graduate and undergraduate students on topics ranging from machine learning in healthcare to single-cell RNA sequencing analysis. His teaching spans courses like Bayesian Machine Learning, Multivariate Statistics, and Theoretical Machine Learning at the graduate level, alongside foundational statistics and calculus courses at TRU and the University of Dhaka. Administrative roles include Chair of the Award and Scholarship Committee for TRU’s Master of Data Science program and membership in Senate Research Committee. Education: Ph.D., Statistics (2013), UBC Vancouver M.Sc., Statistics (2007), University of Windsor M.Sc., Biostatistics (2005), University of Dhaka Awards: NSERC Discovery Grant (2021–2026) Research Training Recognition Fund (TRU,多次) SSC 2013 Talk Honourable Mention Labs/Teams: Active in interdisciplinary projects at TRU’s Department of Mathematics and Statistics, focusing on data science applications in ecology, healthcare, and genetics.

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Falk Herwigمشاهده پروفایل

استاد

University of VictoriaCanada

Falk Herwig is a Professor and Director of the Astrophysical Research Center (ARC) at the University of Victoria's Department of Physics and Astronomy. His research focuses on stellar hydrodynamics, nucleosynthesis, and the origin of elements. He leads the Computational Stellar Astrophysics (CSA) group, which conducts large-scale 3D hydrodynamics simulations of stellar convection and nucleosynthesis processes. The CSA group collaborates with the NSF Physics Frontier Center Joint Institute for Nuclear Astrophysics (JINA-CEE) and the NuGrid collaboration, leveraging high-performance computing resources like the Niagara supercomputer. Herwig's work includes studying convection-nuclear burning interactions in massive and binary stars, nucleosynthesis in diverse astrophysical environments, and the chemical evolution of galaxies. He has pioneered methods to model stellar yields and integrate computational models with observational data. His research spans topics from core convection in massive stars to the physics of merging white dwarfs and nova explosions. Herwig has contributed significantly to advancing computational infrastructure for astrophysics, including the development of tools like SYGMA for galactic chemical evolution modeling. His projects are supported by Compute Canada and involve collaborations with international institutions. Recent research highlights include investigating the role of neutron capture processes in element formation and refining models of white dwarf cooling and stellar evolution.

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Floris van Vugtمشاهده پروفایل

دانشیار

University of MontrealCanada

Floris van Vugt is an Associate Professor in the Department of Psychology at Université de Montréal's Faculty of Arts and Sciences. He directs research on sensorimotor integration and social connection through the Human Connection Science Lab. His interdisciplinary research examines how humans learn sensorimotor mappings (as in music performance), the role of curiosity in learning, and how interpersonal synchrony fosters social connection. He investigates these mechanisms through behavioral experiments, neuroimaging, and real-world dialogue interventions. Professor van Vugt's work demonstrates strong methodological innovation, developing open-source tools like TeensyTap for sensorimotor experiments. His recent publications explore musical training's cognitive effects, interpersonal synchronization dynamics, and technology for social neuroscience research. He actively investigates how dialogue formats like Bohm Dialogue can bridge social divides. His lab studies physiological synchrony during social interactions and develops accessible research technologies for multi-person biosignal recording.

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Susan Brownمشاهده پروفایل

استاد

University of GuelphCanada

Susan Brown is a Professor at the University of Guelph, holding a Canada Research Chair (Tier 1) in Collaborative Digital Scholarship. She is affiliated with the College of Arts and the School of Theatre, English, and Creative Writing. Her research focuses on digital humanities, critical infrastructure studies, Victorian literature, and feminist theory, particularly through her leadership of the Orlando Project, a pioneering interdisciplinary initiative. She has received significant grants from the Social Sciences and Humanities Research Council of Canada and the Canadian Foundation for Innovation. Her work bridges feminist literary history with digital innovation, emphasizing collaborative knowledge production and inclusive digital infrastructure. Brown has contributed to university administration, including roles on the Senate Awards Committee, Board of Governors, and editorial boards of journals like Victorian Review and KULA . She has also served on national and international advisory boards, including Compute Canada and the Digital Research Alliance of Canada. Research interests include feminist digital methodologies, semantic technologies, and the intersection of technology with literary studies. Awards include the Society for Digital Humanities Outstanding Achievement Award (2006) and the T-REX Best New Tool Prize (2008). She has taught extensively in Victorian studies, gender theory, and digital humanities, receiving a teaching award in 1999 for integrating digital methods. Brown founded the DH@Guelph Summer Workshops and co-created the Culture and Technology Studies program. Grants and projects include funding for the Humanities Interdisciplinary Collaboration Lab (THINC Lab) and the Canadian Writing Research Collaboratory (CWRC). Her recent work explores metadata ontologies, linked open data, and the ethical dimensions of digital cultural heritage.

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Kate Milberryمشاهده پروفایل

پژوهشگر ارشد

Simon Fraser UniversityCanada

Dr. Kate Milberry is a Research Fellow in the Faculty of Information at the University of Toronto, holding a PhD from Simon Fraser University's School of Communication. Her research focuses on the democratization of technology as a tool for social justice, examining how tech activists use free software and collaborative platforms like wikis to advance democracy, equality, and environmental sustainability. She is affiliated with the Applied Communication and Technology Laboratory and has contributed to the Independent Media Centre (IMC), a global activist network. Her work bridges geek culture and social justice, emphasizing participatory technologies such as wikis and open-source software. Key projects include analyzing the IMC's technical infrastructure and the political implications of wiki-based collaboration. Her research highlights how activists reshape internet technology to challenge corporate control and promote decentralized, equitable systems. Publications include analyses of tech activism in movements like Indymedia and explorations of how activists contest technical design to align with social justice goals. She has presented globally on topics like open access, digital rights, and the socio-technical dialectic, advocating for democratized knowledge production. Milberry’s academic background includes an MA in Communication and Social Justice from the University of Windsor. Her work is accessible via her blog geeksandglobaljustice.com .

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Lindsey Heagyمشاهده پروفایل

استادیار

University of British ColumbiaCanada

Lindsey Heagy is an Assistant Professor in the Department of Earth, Ocean & Atmospheric Sciences at the University of British Columbia (UBC), Faculty of Science. Her research focuses on inverse theory, machine learning, and geophysical data analysis, with applications in mineral exploration, carbon sequestration, and groundwater systems. She leads a group developing open-source software like SimPEG for geophysical simulations and inversions, alongside GeoSci.xyz for geoscience education resources. Key research areas include geophysical inversions of electromagnetic and potential field data, detection of unexploded ordnance (UXO) using machine learning, and collaboration with industry partners on carbon sequestration projects. Heagy actively recruits graduate students and postdoctoral researchers, emphasizing interdisciplinary approaches to geophysical challenges. Her work emphasizes open science practices, with contributions to open-source tools for data processing and reproducible workflows in geophysics. Recent publications highlight advancements in electromagnetic modeling, magnetic vector inversion, and the integration of neural networks in geophysical parameterization. Her lab's projects often involve large-scale datasets and cutting-edge computational methods, reflecting a commitment to both theoretical innovation and practical applications in environmental and resource geoscience.

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Ivan Beschastnikhمشاهده پروفایل

دانشیار

University of British ColumbiaCanada

Ivan Beschastnikh is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Faculty of Science. He leads research in distributed systems, software engineering, and formal methods, with a focus on privacy-preserving technologies, blockchain systems, and machine learning. His work bridges theoretical foundations and practical system implementations, emphasizing empirical validation and real-world deployment. Research Interests: His primary areas include distributed systems (e.g., consensus algorithms, transaction processing), formal methods for system correctness (e.g., PGo compiler for verified implementations), and privacy in federated learning and blockchain. He also explores interdisciplinary topics like AI ethics, human-computer interaction for developers, and system security. Key Projects: Includes PGo (formal specification to Go compiler), Biscotti (decentralized federated learning), Erlay (Bitcoin transaction relay optimization), and Teleoscope (text corpus analysis tool). His work has practical impact in blockchain scalability, secure multi-party ML, and distributed system validation. Awards: Recognized with the ASPLOS Distinguished Artifact Award, UBC Faculty Teaching Award, and ESEM Best Paper Award. His contributions span academic excellence, pedagogy, and collaborative research. Lab Affiliations: Active in the Systopia Lab and Software Practices Lab (SPL) , and collaborates with UBC’s Data Science Institute and Blockchain@UBC. He emphasizes interdisciplinary research, mentoring students in both theoretical and applied systems work.

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Steven Weijsمشاهده پروفایل

دانشیار

University of British ColumbiaCanada

Dr. Steven Weijs is an Associate Professor and Associate Head (Graduate Programs) in the Department of Civil Engineering at the University of British Columbia (UBC), part of the Faculty of Applied Science. He leads research in water resources management, hydrology, and information theory applications in environmental systems. His work explores optimizing information flows from observations to decision-making in complex water systems. Education: PhD (2011) and M.Sc. (2004) in Water Resources Management from TU Delft, Netherlands. Postdoctoral Research: AXA Research Fund fellowship (2011–2013) at EPFL, Switzerland, followed by roles in environmental fluid mechanics and cryospheric science groups. Research Interests: Mountain hydrology, catchment dynamics, flood forecasting, uncertainty quantification, and information theory-based monitoring strategies. He teaches CIVL 418 Engineering Hydrology and contributes to UBC’s Master of Engineering Leadership in Integrated Water Management. Publications focus on sensor networks, data-driven hydrology, flood analysis, and environmental decision-making. Notable work includes novel methods for streamflow prediction in ungauged basins and optimal monitoring network design. Awards: Leading Scholar (Green College, 2016–2018), AXA Research Fund Postdoctoral Fellowship. He collaborates on projects like WeSenseIt, a citizen observatory initiative, and develops low-cost sensing technologies for hydrological monitoring. His research bridges theoretical frameworks with practical applications in water resource management.

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