جست‌وجوی استاد و پژوهشگر

• Compiler Optimization
• High Performance Computing
• Computer Architecture
• +۲ مورد دیگر

Dr. J Nelson Amaral is a Professor in the Department of Computing Science within the Faculty of Science at the University of Alberta. His research focuses on compiler optimization techniques that enhance performance in modern computing architectures through clever code transformations. Educational background includes B.Sc. in Electrical Engineering (PUCRS), M.Sc. in Electrical Engineering (ITA), and Ph.D. in Electrical and Computer Engineering (University of Texas at Austin). Research interests span compiler optimizations for resource utilization, learning technology applications in compilation processes, and feedback-directed optimization efficiency improvements. Current investigations include instruction-level parallelism exploitation, code transformations for heterogeneous architectures, and machine learning-enhanced compilation. Publication analysis reveals strong focus on compiler techniques for performance optimization, particularly for matrix operations, convolution algorithms, and memory hierarchy management. Recent work emphasizes hardware-software co-design for specialized processors and auto-vectorization methods. University of Alberta Faculty of Science Excellence in Teaching Award (2015) Distinguished Engineer, Association for Computing Machinery (2014) Distinguished Speaker, Association for Computing Machinery (2012-2014) Interdepartmental Science Students' Society Award for Excellence in Teaching (2014) IBM Center for Advanced Studies Research Faculty Fellow of the Year (2012) Research includes industry collaborations through the IBM-CAS partnership. Contributes to computing education through curriculum development and student mentoring. Leads compiler optimization research at the IBM Center for Advanced Studies, focusing on performance improvements for enterprise workloads and specialized hardware.

Aniket Didolkarمشاهده پروفایل

پژوهشگر

• Deep Learning
• Cognitive Science
• Large Language Models
• +۵ مورد دیگر

Aniket Didolkar is a Ph.D. student at Mila and The University of Montreal, advised by Prof. Yoshua Bengio, Dr. Anirudh Goyal, and Prof. Michael Mozer. He is also a visiting researcher at Meta, working with Dr. Nicolas Ballas. Education: Pursuing Ph.D. in Deep Learning and Cognitive Science at The University of Montreal. Research Focus: Developing cognitive science-inspired deep learning techniques, including metacognitive LLMs for mathematical problem solving, hybrid recurrent-transformer architectures for long-context modeling, and object-centric visual representation learning. Article Trends: His work spans object-centric learning (CVPR 2025, ICLR 2025, ICLR 2024), LLM reasoning (NeurIPS 2024), hybrid neural models (NeurIPS 2022), and NLP/speech augmentation (COLING 2020, Interspeech 2020). Scientific Awards: Unique Excellence Scholarship ($15,000) at Mila (December 2023). Scholarship by University of Alberta and Amii ($1,500) for Amii AI Week (April 2022). Scholarship by University of Montreal and Quebec Ministry of Higher Education ($4,000) (April 2022). Collaborations: Worked with institutions including Valence Labs, Microsoft Research NYC, IISc Bangalore, IIIT Delhi, Preferred Networks, and Ubisoft India Studios.

Jeremy Bradburyمشاهده پروفایل

دانشیار

• Software Engineering
• Software Quality Assurance
• Testing and Analysis
• +۷ مورد دیگر

Jeremy Bradbury is an Associate Professor in the Faculty of Science at Ontario Tech University, where he has served as Undergraduate and Graduate Program Director for Computer Science and as a member of the Board of Governors. His research focuses on software testing, analysis, and quality assurance, with a particular emphasis on human-centered approaches, empirical methodologies, and concurrency issues in software systems. He leads the Software Quality Research Lab (SQRLab) and develops tools like PIE for visualizing software design patterns and GidgetML for adaptive educational gaming. Education: PhD in Computer Science from Queen's University (2007). Research interests include software visualization, open-source software analysis, flaky test detection, and the application of machine learning to software engineering challenges. His work spans both academic contributions (e.g., combinatorial testing frameworks) and practical innovations like the Run, Llama, Run game for computational thinking education. Recent work explores AI-driven bug prediction, data augmentation bias in ML models, and cybersecurity for connected autonomous vehicles. He has organized workshops on testing configurable systems (ToCaMS) and challenges in parallel computing.

Michael Beckمشاهده پروفایل

استادیار

• Machine Learning
• Digital Agriculture
• Computer Vision
• +۳ مورد دیگر

Michael Beck is an Assistant Professor in the Department of Data Analytics at the University of Winnipeg, specializing in machine learning, stochastic network calculus, and digital agriculture. He holds a Master's in Mathematics (Probability Theory) and a Doctorate in Computer Science from the University of Kaiserslautern, Germany. His postdoctoral research spanned institutions including the City University of Hong Kong and the University of Manitoba. Research Interests: Data acquisition strategies for machine learning models Digital agriculture innovations including automated plant analysis Microplastic analysis through deep learning and embedded systems Stochastic network calculus for queueing system analysis Publications span machine learning applications in agriculture, network performance analysis, and embedded systems design. Notable achievements include the Best Paper Award (2016) and contributions to open datasets like the weed seedling image collection. He supervises graduate students in machine learning and network calculus, teaches courses such as Advanced Internet Programming and Operations Research, and collaborates on projects like the TeraByte initiative for agricultural data.

Tim Rogalskyمشاهده پروفایل

دانشیار

• Mathematical Modeling
• Chaos Theory
• Mathematics Education
• +۲ مورد دیگر

Dr. Tim Rogalsky is an Associate Professor of Mathematics at Canadian Mennonite University. He holds a PhD from University of Manitoba and teaches courses spanning discrete mathematics, calculus, and chaos theory. His pedagogy focuses on making mathematics accessible and demonstrating interdisciplinary connections to science, economics, and social justice. Research Interests: Dr. Rogalsky develops mathematical models for epidemiological control, investigates connections between mathematics and art, and creates pedagogical approaches for diverse learners. Notable projects include: Optimal control methods for disease management Mathematical mysticism in Salvador Dali's work Aerodynamic optimization using Bézier parameterization Community Engagement: Regularly presents mathematical concepts to public audiences through Winnipeg Art Gallery lectures exploring beauty in nature, sacred geometry, and Renaissance mathematical influences. Teaching Philosophy: Emphasizes interactive learning that connects mathematics to real-world contexts, serving students from math-phobic general learners to mathematics majors.

Spencer Smithمشاهده پروفایل

دانشیار

• Software Engineering
• Scientific Computing
• Requirements Analysis
• +۵ مورد دیگر

Dr. Spencer Smith is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. He serves as the Undergraduate Advisor for Software Engineering and teaches courses such as Scientific Computing, Software Design, and Capstone Projects. Education: Ph.D. in Engineering (2001), McMaster University M.Eng. (1997), McMaster University B.Eng. in Computer Systems (1995), McMaster University Research Interests: Software Engineering Principles for Scientific Computing Assurance Cases for Research Software Numerical Algorithms in Engineering Problems Finite Element Method Applications Medical Imaging and Computational Medicine His work emphasizes improving software sustainability and reliability through systematic documentation, requirements analysis, and generative approaches. Notable projects include the Drasil framework for literate scientific software and the Mesh Generation Toolbox. Advising & Collaboration: He advises numerous graduate students and oversees research groups like the Software Quality Research Lab (SQRL) and the Algorithms Research Group (ARG). His collaborations span computational medicine, seismology, and nuclear safety software certification. Labs/Teams: Drasil Framework Mesh Generation Toolbox (MGT) Virtual Material Testing Laboratory

• Programming Languages
• Concurrency
• Embedded Systems
• +۳ مورد دیگر

Dr. Emil Sekerinski is a Professor in the Department of Computing and Software at McMaster University, located at ITB 215. He serves as the Undergraduate Advisor for Computer Science (Jan 1, 2025 - June 30, 2025). His research focuses on Programming Logic , Concurrency , Embedded Systems , and Programming Languages , with specialization in Computer Systems, Software Quality, and Computation Theories. He is affiliated with the Digital & Smart Systems research cluster. Recent academic contributions include advanced compiler design, concurrent system design, and formal specification techniques. His work spans theoretical aspects of computing, such as program algebra and automata, alongside practical applications in real-time monitoring and wireless sensor networks. He actively contributes to academic communities, serving as a conference co-chair (FMTea'24) and program committee member (ICTAC'24, iFM'24). Teaching highlights include courses like CAS 781 Advanced Topics: Advanced Compiler Design and Optimization (Fall 2025) and SFWR ENG 3BB4 Concurrent System Design (Fall 2024). His publications emphasize concurrency, formal methods, and algorithm optimization, bridging theoretical foundations with real-world system implementations.

Shahrukh Atharمشاهده پروفایل

استادیار

• Image and Video Processing
• Perceptual Image Quality Assessment
• Digital Signal Processing
• +۳ مورد دیگر

Dr. Shahrukh Athar is an Assistant Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on perceptual image quality assessment (IQA), degraded-reference and multiply-distorted image analysis, and digital signal/video processing. He also emphasizes educational development, particularly active learning strategies and pedagogical training for colleagues and graduate students. He teaches courses such as COMPENG 2DX3 (Microprocessor Systems Project), COMPENG 2SH4 (Principles of Programming), ELECENG 2CI4 (Introduction to Electrical Engineering), and ELECENG 3CL4 (Introduction to Control Systems). His work bridges machine learning applications in IQA with practical educational methodologies. Dr. Athar's research includes developing robust no-reference IQA algorithms using deep learning and constructing large-scale datasets. He has published extensively on topics like image debanding, blind quality assessment, and FPGA-based signal processing implementations. His LinkedIn and other professional profiles highlight interdisciplinary contributions in both technical and educational domains.

Ashok Krishnamurthyمشاهده پروفایل

دانشیار

• Mathematical Modeling
• Infectious Disease Epidemiology
• Bayesian Statistics
• +۳ مورد دیگر

Ashok Krishnamurthy is an Associate Professor at Mount Royal University's Department of Mathematics & Computing, within the Faculty of Science and Technology. His research focuses on mathematical modeling of infectious diseases (e.g., Ebola, Measles, COVID-19) and Bayesian data assimilation. He emphasizes spatial and temporal tracking of disease outbreaks and has led projects in Congo, Nigeria, the Czech Republic, and historical England/Wales. PhD (2009): University of Louisville MSc (Mathematics) (2002): University of Windsor MSc (Statistics) (2000): University of Madras BSc (Statistics) (1998): University of Madras Dr. Krishnamurthy has secured multiple grants as Principal Investigator, including $5000 Internal Research Grant Funds for Ebola and measles tracking projects (2012–2020). He actively promotes mathematics, statistics, data science, and computing through undergraduate research assistantships, fostering high-impact learning opportunities. Notable awards include the 2020 MRU Undergraduate Research Supervision Award and a 2020 teaching excellence nomination. 2019–2020: Spatial tracking of Ebola in Congo 2015–2017: Redundant constraints detection in mathematical programming 2012–2013: Bayesian tracking of epidemics His work integrates interdisciplinary approaches, such as web-based dashboards for disease tracking and nature-based healthcare solutions. He teaches courses ranging from calculus to statistical data analysis and has presented research at provincial/national conferences.

• Continuum Theory
• Geometric Topology
• Topological Dynamics
• +۳ مورد دیگر

Logan C. Hoehn is an Associate Professor in the Department of Computer Science and Mathematics at Nipissing University. He holds a PhD from the University of Toronto (thesis available). His research focuses on continuum theory, geometric topology, and topological dynamics. Key areas include the study of plane embeddings, hereditarily indecomposable continua, fixed-point-free maps, and isotopies in metric spaces. His work intersects with set-theoretic topology, metric geometry, and low-dimensional topology. Recent publications (2023–2024) explore accessibility properties of arc-like continua, simplicial inverse systems, and plane embeddings. Notable contributions include a complete classification of homogeneous plane continua and advancements in shortest path parameterization in arbitrary domains. Hoehn has presented at conferences such as STDC24, STDC23, and the Summer Topology Conference. He develops interactive tools for linear transformations, puzzle games, and complex function visualization. His teaching includes advanced courses like Singular Homology (MATH 5067).

• Quantum Chemistry
• Theoretical and Computational Chemistry
• Density Functional Theory
• +۵ مورد دیگر

Paul Ayers is a Professor in the Department of Chemistry & Chemical Biology at McMaster University, Canada. He serves as a Canada Research Chair and is a leading figure in theoretical and computational chemistry. His research focuses on density functional theory (DFT), quantum chemistry, and the application of machine learning to chemical problems. He has developed influential software tools like the HORTON library for computational chemistry. His work spans topics such as electron localization/delocalization matrices, conceptual DFT, and molecular reactivity. Ayers' studies often bridge fundamental theory with practical applications, including drug design, material science, and environmental chemistry. He collaborates on interdisciplinary projects, such as predicting molecular properties using deep learning and optimizing force fields for simulations. Ayers has authored over 200 peer-reviewed articles, with recent contributions emphasizing software development (e.g., AtomDB, PyCI), reactivity descriptors, and quantum mechanical modeling. His team's work on hydrogen bond detection via molecular trajectory analysis and resummation strategies for perturbation series demonstrates his commitment to advancing computational methods. Key Awards: Canada Research Chair (McMaster) Labs/Teams: Quantum Theory Group, Computational Chemistry Lab, HORTON Development Team

Jamshid Beheshtiمشاهده پروفایل

استاد

• Information Behavior
• Bibliometrics
• Altmetrics
• +۵ مورد دیگر

Jamshid Beheshti is a Professor at McGill University's School of Information Studies, with over 30 years of academic experience. He has held roles including Director of the School (1998–2004), Interim Dean of the Faculty of Education (2007–2008), and Associate Dean (2004–2009). His research focuses on children's information behavior, bibliometrics, and human-computer interaction. Beheshti has secured over $5 million in research funding and supervised 12 PhD students. He is also a former Visiting Professor at Kuwait University and has collaborated with institutions globally. Education: PhD, School of Library and Information Science, University of Western Ontario MLS, School of Library and Information Science, University of Western Ontario BA (History), Simon Fraser University Diploma (Mining Technology), British Columbia Institute of Technology Research Interests: Beheshti's work explores information behavior in children and millennials, design of web portals for youth, virtual environments in education, and bibliometric analysis. He emphasizes interdisciplinary approaches, such as integrating cognitive science and technology design. Grants & Projects: Major grants include SSHRC-funded studies on metaliteracy, children's web portals, and virtual learning environments. Notable projects include the Treasures of Islam CD-ROM and the Virtuel Age Canada initiative. Labs & Teams: Affiliated with labs like the Accessible Computing Technology Research Group and Multimodal Interaction Lab, focusing on inclusive design and educational technology.

Teresa Dobsonمشاهده پروفایل

استاد

• Digital Literacy
• Literary Education
• Critical Literacies
• +۴ مورد دیگر

Dr. Teresa Dobson is a Professor in the Department of Language and Literacy Education at the University of British Columbia's Faculty of Education. Her research bridges literary education, digital literacy, and digital humanities, with a focus on developing innovative browsing interfaces for text visualization through interdisciplinary collaborations. Her research explores critical digital literacies, multimodal storytelling, and pedagogical applications of digital tools. Primary interests include digital research methodologies, online pedagogies, place-based literacies, and narrative inquiry in teacher education contexts. Dobson's publications demonstrate consistent focus on digital literacy development, educational technology integration, and visual methodologies in humanities research. Recent work examines observational modeling, visual literacy, and digital book production for early literacy across cultural contexts.

Margo Seltzerمشاهده پروفایل

استاد

• Computer Systems
• Operating Systems
• Database Systems
• +۷ مورد دیگر

Margo Seltzer is a Professor and Co-Head of the Department of Computer Science at the University of British Columbia (UBC). She holds the Canada 150 Research Chair in Computer Systems and the Cheriton Family Chair in Computer Science. Her research focuses on computer systems, including operating systems, databases, data provenance, graph analytics, and interpretable machine learning. She is also involved in educational initiatives and has held leadership roles in academia, including serving as Dean of Computer Science and Engineering at Harvard University. Education: PhD in Computer Science from UC Berkeley (1992), AB in Applied Mathematics from Harvard (1983). Professional roles include Chief Technology Officer at Sleepycat Software and architect at Oracle Corporation. She has received prestigious awards such as the ACM Athena Lecturer Award, Killam Teaching Prize, and membership in the National Academy of Engineering. Research Interests: Systems, databases, transaction processing, provenance capture, healthcare informatics, and cybersecurity. Her work emphasizes practical applications of systems research, including optimizing storage, improving operating system performance, and enhancing data security. She has contributed to open-source projects like Berkeley DB and CamFlow provenance system. Key Contributions: Developed systems for provenance-aware storage, sparse decision trees (e.g., GOSDT), and intrusion detection (FRAPpucino). She advocates for reproducible research through tools like Encapsulator and Rclean. Her teaching and mentorship have influenced countless students and junior faculty in computer science. Awards: ACM Athena Lecturer (2023), SIGMOD Systems Award (2020), USENIX Lifetime Achievement Award (2019), and election to the American Academy of Arts and Sciences (2021). Her work bridges theoretical computer science with real-world applications, emphasizing both technical innovation and societal impact.

Anthony Wachsمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Particulate Flow
• Numerical Simulation
• +۵ مورد دیگر

Anthony Wachs is an Associate Member of the Department of Mathematics at the University of British Columbia (UBC), affiliated with the Faculty of Science. His research focuses on computational fluid dynamics (CFD), particulate flows, and multiphase systems, with emphasis on numerical methods like DEM-CFD coupling and high-fidelity simulations of complex fluid-particle interactions. He develops scalable solvers for non-spherical rigid bodies and fluid-structure interactions, contributing to fields such as granular media, viscoplastic fluids, and biological capsule dynamics. His work bridges computational approaches with real-world applications in energy, biomedical engineering, and environmental systems. Research interests include particle-resolved direct numerical simulations (DNS), fluidized beds, and the development of tools like Grains3D and PeliGRIFF for particle dynamics. His studies address challenges in flow past irregular geometries, hydrodynamic force modeling, and machine learning-enhanced fluid dynamics. Wachs collaborates across disciplines, integrating advanced numerical techniques with experimental validation to advance understanding of multiphase flow phenomena.