جستجوی استاد راهنمای دانشگاهی

Brent Pym is an Associate Professor in the Department of Mathematics and Statistics at McGill University. His research focuses on the intersection of differential, algebraic, and noncommutative geometry, with a particular emphasis on Poisson varieties and deformation quantization. He has held academic positions at the University of Edinburgh, University of Oxford, and was a Postdoctoral Fellow at McGill and the University of Toronto. Education: BScE in Engineering Physics, Queen's University (2007) MSc in Mathematics, University of Toronto (2008) PhD in Mathematics, University of Toronto (2013) Research Interests: Pym studies Poisson structures, their quantizations, and connections to mathematical physics. His work involves classical/derived algebraic geometry, D-modules, moduli spaces, the Stokes phenomenon, and multiple zeta values. Recent projects include holonomic Poisson manifolds, log symplectic structures, and software for symbolic calculations in deformation quantization. Awards: Lichnerowicz Prize (2018) Advising & Grants: Pym has openings for graduate students (admission 2026) and undergraduate projects (2026–27). He develops the Star Products software package for symbolic calculations in Poisson brackets and quantization. His work is supported by research collaborations and institutional grants. Labs & Teams: Pym collaborates with researchers in geometry and mathematical physics, contributing to projects in noncommutative algebra and geometric quantization. His software tools enhance symbolic computation in these fields.

• Mathematical Physics
• Algebraic Geometry
• Noncommutative Geometry
• +۳ مورد دیگر

Dr. Zhenman Fang is an Associate Professor at the School of Engineering Science , Simon Fraser University (SFU) , where he founded and directs the HiAccel Lab . He also holds an associate membership in the School of Computing Science at SFU. His research focuses on customizable computing with software-defined hardware acceleration , addressing performance, energy-efficiency, and reliability in post-Moore’s law computing across domains like machine learning , big data analytics , quantum chemistry , and precision medicine . Education: Ph.D. in Computer Science from Fudan University (2014), with a visit to University of Minnesota during his studies. Postdoctoral Work: University of California, Los Angeles (UCLA) (2014-2017). Industry Experience: Staff Software Engineer at Xilinx (2017-2019). Dr. Fang’s research spans the entire computing stack , including application characterization , accelerator-rich architecture design , and programming/tool support . He has developed frameworks like HiSpMV , SyncNN , and SQL2FPGA , emphasizing FPGA acceleration for vision transformers , quantum chemistry , and spiking neural networks . His work has been recognized with 3 best paper awards (FPL 2024, TCAD 2019, MEMSYS 2017) and 3 best paper nominees (FCCM 2025, HPCA 2017, ISPASS 2018). Recent publications highlight trends in low-precision machine learning ( ShiftQuant , ESRU ), quantum chemistry acceleration ( SERI ), and vision transformer optimization ( Quasar-ViT ). His HiAccel Lab actively mentors PhD and MASc students , with notable graduates like Alec Lu (PhD 2024, now at Meta) and Philip Stachura (MASc, now with BC Graduate Scholarship). Scientific Awards: Inaugural SFU Research Excellence Award - Horizon Award (2025) FPL 2024 Stamatis Vassiliadis Best Paper NSERC Alliance Award (2020) CFI JELF Award (2019) Xilinx University Program Award (2019) IEEE Senior Member (2023) Grants: NSERC Discovery Grant (2019) CFI JELF Funding (2019) Huawei and Xilinx sponsorships Dr. Fang leads open-source initiatives like SyncNN , PASTA , and SQL2FPGA , and serves as General Chair for ASAP 2025 and Program Co-Chair for RAW 2025 . His lab collaborates globally with institutions such as UCLA , Northeastern University , and Xidian University .

• Customizable Computing
• Heterogeneous Computing
• FPGA Acceleration
• +۸ 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

Lena Simine is an Associate Professor in the Department of Chemistry at McGill University, affiliated with the Faculty of Science. She holds a B.Sc. (2009) and Ph.D. (2015) from the University of Toronto, followed by a postdoctoral fellowship at Rice University (2015–2019). Her laboratory is located in P&P 118A, focusing on developing computational approaches for modeling molecular phenomena in theoretical chemistry and chemical physics. Her research interests center on computational materials design, quantum dynamics, and the application of machine learning to chemistry. Specific areas include simulating amorphous materials, aptamer design, and quantum systems modeling. She teaches CHEM 365 (Statistical Thermodynamics) and CHEM 593 (Statistical Mechanics and Machine Learning for Chemistry). Her work explores interdisciplinary frontiers, such as path-integral simulations, GFlowNets for molecular design, and the physical principles underlying deep learning in materials science. Recent studies highlight innovations like DeltaGzip for binding affinity prediction and the MAP protocol for 3D disordered matter simulations. Her lab’s contributions span computational methods, material innovation, and quantum phenomena, with a focus on advancing both theoretical frameworks and practical applications in chemistry and materials science.

• Theoretical Chemistry
• Chemical Physics
• Computational Materials Science
• +۳ مورد دیگر

Stephen Hughes is a Full Professor in the Department of Physics, Engineering Physics and Astronomy at Queen’s University, Canada. He holds appointments in the Faculty of Arts and Science and is affiliated with the Centre for Nanophotonics. His research focuses on theoretical and computational nanophotonics, quantum optics, and light-matter interactions. He has co-founded Lumerical Solutions, a leading photonics software company acquired by ANSYS in 2020, and has held postdoctoral positions in Germany, Japan, and the U.S. Education: PhD (Heriot-Watt University, Edinburgh), Postdoctoral work at NTT Basic Research Labs (Japan) and others. Industry Experience: Co-founder of Lumerical and Galian Photonics. Research interests include quantum photonics, nanophotonics, semiconductor optics, photonic crystals, cavity-QED, quantum dots, and topological photonics. His group explores applications in quantum technologies, optomechanics, and metamaterials. Collaborations span global institutions, focusing on both fundamental physics and applied nanophotonics. Labs/Groups: The Hughes Group (Theoretical Quantum and Nanophotonics) operates a state-of-the-art computational lab funded by CFI and MRI Ontario. Current projects involve inverse design techniques, ultrastrong coupling regimes, and quantum trajectory simulations.

• Quantum Optics
• Nanophotonics
• Quantum Photonics
• +۸ مورد دیگر

Soumaya Cherkaoui is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. Previously, she served as a Full Professor at Université de Sherbrooke and held industrial roles as an aerospace project manager. Her research integrates artificial intelligence with telecommunications, focusing on quantum computing, frugal edge intelligence, and applications in connected vehicles and IoT. Current Position: Full Professor, Polytechnique Montréal Prior Academic Role: Full Professor, Université de Sherbrooke Industry Experience: Aerospace Project Manager Research Interests: Convergence of AI and communications, quantum computing for networking, frugal intelligence at the edge, and applications in autonomous vehicles, industrial IoT, and smart grids. She leads government and industry-funded projects, including a $6 million quantum initiative in 2025. Recent Publication Trends: Her 2025–2024 work emphasizes quantum-enhanced anomaly detection (via QGANs), Open RAN slicing with quantum optimization, and reinforcement learning for secure cognitive radio networks. Topics span 5G/6G, vehicular networks, and zero-trust architectures. Scientific Awards: IEEE Communication Society Distinguished Lecturer (2020) ACM Mirela Notare Award (2023) IEEE Bio-Inspired Computing STC Leadership Award (2023) N2Women: Stars in Networking and Communications (2023) Best Paper Awards at IEEE ICC 2017, IEEE LCN 2021, ICCSPA 2024 Advising and Grants: Supervised 3 Master's students in 2024, with research on quantum GANs and federated learning for vehicular networks. Secured grants like the $6 million quantum project (2025) and participated in CFI-QC government funding (2022). Editorial and Leadership: Served as Associate Editor for IEEE, Wiley, and Elsevier journals. Chaired conferences like IEEE LCN 2019 and IEEE ICC2025, and held leadership roles in IEEE Communications Society committees.

• Artificial Intelligence
• Telecommunications Networks
• Quantum Computing
• +۶ مورد دیگر

Roozbeh Razavi-Far is an Assistant Professor at the Faculty of Computer Science and the Canadian Institute for Cybersecurity at the University of New Brunswick. His research focuses on machine learning, big data analytics, and cybersecurity of cyber-physical systems and IoT devices. He has authored/co-authored over 150 publications and is listed by Stanford as among the top 2% of most cited researchers (2022). His work spans federated learning, transfer learning, quantum machine learning, and dependable AI systems. He serves as an Associate Editor for Neurocomputing, Machine Learning with Applications, and IEEE Transactions on Industrial Cyber-Physical Systems, among others. As an IEEE Senior Member, he chairs IEEE Computational Intelligence and Systems, Man, and Cybernetics Societies. Previously, he directed the Learning System and Cybernetics Group at the University of Windsor (2016–2022). His research interests emphasize security in non-stationary environments, adversarial machine learning defenses, and real-time analytics for smart grids. Awards include NSERC-DG, NSERC-ECR, and USRG grants. He has mentored students who received NSERC Alexander G. Bell, MITACS, and Ontario Graduate Scholarships. His recent publications highlight advancements in privacy-preserving split learning, blockchain-based federated learning security, and graph-based malware detection. He also explores quantum computing applications in AI and cybersecurity frameworks for cyber-physical systems.

• Machine Learning
• Cybersecurity
• Federated Learning
• +۵ مورد دیگر

Douglas Stebila is an Associate Professor in the Department of Combinatorics and Optimization at the University of Waterloo, Faculty of Mathematics. His research focuses on cryptographic protocols, with an emphasis on post-quantum cryptography, TLS protocol security, and key exchange mechanisms. He has contributed to the design and analysis of cryptographic systems resilient to quantum computing threats, including work on hybrid key exchange methods and post-quantum TLS implementations. Stebila is involved in standards projects such as the Open Quantum Safe initiative, aiming to transition existing infrastructure to quantum-resistant algorithms. His recent work addresses security models for cryptographic protocols, including formal verification of key establishment schemes and analysis of real-world protocols like Signal and TLS. His research spans theoretical cryptography, applied protocol analysis, and implementation security. Key contributions include studies on obfuscated key exchange, verifiable decapsulation of post-quantum KEMs, and optimization of TLS handshake efficiency (e.g., TurboTLS). He also explores challenges in cryptographic protocol design, such as preventing double authentication and ensuring resistance against side-channel attacks. His work frequently bridges academic research with practical applications, emphasizing the transition of cryptographic innovations into real-world systems. Stebila collaborates with industry and academic partners on projects like the Open Quantum Safe initiative, which develops libraries for post-quantum cryptography integration. His publications often address security analyses of emerging protocols and their vulnerability to both classical and quantum adversaries. He has co-authored conference proceedings for major venues like CRYPTO and SAC, and contributed to standards documentation for protocols such as TLS and SSH.

• Cryptography
• Post-Quantum Cryptography
• Network Security
• +۳ مورد دیگر

Joseph Emerson is an Associate Professor at the University of Waterloo's Department of Applied Mathematics and a faculty member at the Institute for Quantum Computing (IQC). He is also a Fellow of CIFAR's Quantum Information Science program and CEO of Quantum Benchmark, a startup specializing in quantum computing error diagnostics. His research focuses on scalable quantum error correction, foundational quantum theory, and protocols like randomized benchmarking, now a global standard for quantum gate characterization. Emerson earned a BSc from McGill University, an MSc in experimental nuclear physics, and a PhD in theoretical physics from Simon Fraser University. His postdoctoral work at MIT and the Perimeter Institute explored quantum randomness and decoherence. He has held roles at IQC since 2005, advancing quantum computing's practical implementation through error suppression and validation techniques. Research Highlights Developed randomized benchmarking for error diagnostics across quantum platforms. Framework for unitary t-designs applied to quantum algorithms and thermodynamics. Investigated contextuality in quantum mechanics as a computational resource. Awards & Recognition Early Researcher Award (Ontario, 2008–2013) CIFAR Quantum Information Science Fellow NSERC Postdoctoral Fellowship (2003–2005) Labs & Affiliations Emerson leads research teams at IQC and collaborates with Perimeter Institute and industry partners. His work bridges theoretical foundations with practical tools for quantum computing scalability.

• Quantum Information Processing
• Foundations of Quantum Theory
• Quantum Computing
• +۳ مورد دیگر

Dr. Hung Cao is an Assistant Professor of Computer Science at the University of New Brunswick, where he directs the Analytics Everywhere Lab. His work focuses on interdisciplinary research in Cyber-Physical Systems (CPS), IoT, Edge/Fog/Cloud Computing, and Explainable AI, addressing societal challenges through data-driven solutions. Prior roles include PostDoc Fellow and Data Scientist at the People in Motion Lab, UNB, and Lecturer/Researcher at Vietnam National University. He holds a Ph.D. in Geomatics Engineering (specializing in Data Science) from UNB (2020), an M.Sc. in Computer Science from University College Dublin (2015), and a B.Eng. from Vietnam National University (2011). Research interests span Smart Cities, Embedded AI, TinyML, Federated Learning, and Real-time Systems. He has led projects with Cisco, NB Power, and other industry partners to develop scalable analytics frameworks for IoT applications. Dr. Cao actively contributes to technical communities (IEEE Smart City, Edge Computing, etc.), serving as a reviewer for journals and conferences, and a Topic Editor for Electronics Journal . His innovations include the Analytics Everywhere framework for spatio-temporal data analysis, MACeIP platform for smart cities, and energy-efficient IoT systems for environmental monitoring. Current work emphasizes human-centered AI for healthcare diagnostics and industrial inspection systems.

• Smart Cities
• Cyber-Physical Systems (CPS)
• Internet of Things (IoT)
• +۱۰ مورد دیگر

Dr. Debajyoti Mondal is an Associate Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on algorithms, network visualization, computational geometry, and visual analytics. He holds a PhD from the University of Manitoba and has held postdoctoral positions at the University of Waterloo and Microsoft Research. Mondal's work spans interdisciplinary applications, including collaborations with Saskatoon Transit and academic medicine. He has authored over 100 peer-reviewed publications and secured grants such as NSERC Discovery, CFI, and Canada First Research Excellence grants. His awards include the 2023 New Scholar RSAW Award. Education: Ph.D. in Computer Science, University of Manitoba, 2016 MSc in Computer Science, University of Manitoba, 2012 BSc. Engg. in Computer Science, Bangladesh University of Engineering and Technology, 2009 Research Interests : Algorithms, graph drawing, computational geometry, visual analytics, and interdisciplinary applications in software engineering, transportation, and bioinformatics. His lab (VGA Lab) develops visualization systems for big data analysis. Key Contributions : Advanced theoretical foundations in computational geometry and graph drawing, developed practical visualization tools, and contributed to climate-related projects like Global Water Futures. Grants & Awards : NSERC Discovery Grant (2018-2024) CFI Grant (2021-2025) Microsoft Research Internship (2015-2016) New Scholar RSAW Award (2023) Labs/Teams : Leads the VGA Lab, collaborating with interdisciplinary teams on projects like Clone-World (software clone visualization) and SET-STAT-MAP (mixed data visualization).

• Information visualization
• Graph drawing
• Computational geometry
• +۶ مورد دیگر

Dr. Chanchal K. Roy is a Professor of Software Engineering/Computer Science at the University of Saskatchewan (USask), Canada, and Director of the NSERC CREATE SOAR program. He leads the Software Research Lab (SRLab) and is renowned for his work on code clone detection (NiCad tool) and software maintenance. His research spans software evolution, big data analytics, and quantum computing applications in software engineering. Dr. Roy holds a Ph.D. from Queen’s University, an M.Sc. from RWTH Aachen University, and a B.Sc. from Khulna University. Research interests include software clone detection, maintenance, and evolution, with emphasis on semantic analysis and cross-language clones. He has published over 240 papers (h-index 52) and attracted $6M+ in funding, including NSERC grants and CFI-JELF support. Awards include the GSA Advising Excellence Award, Outstanding Young Computer Science Researcher Award, and multiple Most Influential Paper awards. Key contributions include developing NiCad, advancing Stack Overflow search techniques, and leading collaborative projects in software analytics. His work has been featured in ACM Tech News, TechRepublic, and Stack Overflow blogs. Dr. Roy actively engages in keynotes at conferences like WCRE, IWSC, and BIM.

• Software Engineering
• Software Maintenance and Evolution
• Code Clone Detection
• +۳ مورد دیگر

Dr. Kevin Schneider is a Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on software architecture, evolution, analysis, and visualization, with notable work in quantum computing applications and machine learning. He also explores collaborative software teams and domain-specific languages to enhance development processes. Education: Ph.D., Computing and Information Science, Queen’s University (2000) Research Associate, Computing and Information Science, Queen’s University (1991–94) M.Sc., Computing and Information Science, Queen’s University (1990) B.Sc.(Hon), Computational Science, University of Saskatchewan (1980) Research interests include software design principles, maintenance strategies, and the integration of AI/quantum computing into software engineering. He emphasizes reproducibility in scientific workflows and tools like VizSciFlow. His work often bridges theory and practice, addressing challenges in code clone stability, user feedback management, and healthcare-related machine learning frameworks. Scientific Awards: Most Influential Paper at SCAM 2001 for his work on software engineering via source transformation. Advising and grants: While no specific advisees are listed, his research involves large-scale projects such as the Nutrient App and automated polyp segmentation tools. He collaborates on grants related to quantum computing applications and cloud-based software systems. Labs and teams: His work centers on collaborative scientific data analysis groups and developing tools for real-time groupware systems in complex workflows. He contributes to projects like CloneCognition and FSECAM, aiming to improve software design and maintenance through advanced analytics.

• Software Architecture and Design
• Software Evolution and Maintenance
• Software Analysis and Navigation
• +۶ مورد دیگر

Glenn Gulak is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He holds the Canada Research Chair in Signal Processing Microsystems and the Edward S. Rogers Sr. Chair in Engineering. A Senior IEEE Member and Professional Engineer in Ontario, he received his Ph.D. from the University of Manitoba. His research spans: Digital Communication Systems: VLSI implementations of MIMO detectors, lattice reduction algorithms, and homomorphic encryption accelerators Lab-on-Chip Microsystems: CMOS biosensors for rapid pathogen detection and integrated fluorescence imaging Recent publications (2019-2025) demonstrate a dominant focus on privacy-enhancing technologies, with 73% concentrated in cryptographic hardware and homomorphic encryption. This reflects industry-aligned work on confidential computing and secure data processing. Awards & Honors: IEEE Millennium Medal (2001) Canada Research Chair in Signal Processing Systems (Tier 1, 2005-2012) Edward S. Rogers Sr. Chair (2005-2010) RBC Research Prize L. Lau Chair (1999-2004) Teaching Award (1999) He has supervised 44+ graduate students (PhD/MASc) with thesis topics spanning VLSI communication systems, CMOS biosensors, and cryptographic accelerators. Notable industry collaboration includes serving as CTO of a semiconductor startup (2001-2003). His lab develops hardware for quantum cryptography and secure medical computation.

• Homomorphic Encryption
• Quantum Cryptography
• CMOS Biosensors
• +۴ مورد دیگر

Nicolas Godbout is a Full Professor and Department Director of the Department of Engineering Physics at Polytechnique Montréal. He holds a Ph.D. from Polytechnique Montréal and serves as Head of the Fiber Optics Laboratory and as a Researcher at the Center for Optics, Photonics and Lasers (COPL). His academic leadership extends to teaching courses including Fundamentals of Photonics, Waveguide Optics, Lasers, Quantum Optics, and Current Subjects in Photonics. Dr. Godbout's research spans multiple areas of photonics with particular emphasis on optical fiber components, quantum cryptography, quantum information, optical telecommunications, and nonlinear optics. His work bridges fundamental theoretical investigations with practical applications in telecommunications, biomedical imaging, and quantum technologies. He has made significant contributions to photonic lantern development, quantum key distribution systems, and optical fiber component design. Analysis of his recent publications reveals a strong trend toward interdisciplinary research combining photonics with biomedical applications, quantum information processing, and advanced computational modeling. His work demonstrates consistent innovation in optical fiber technology, with increasing focus on quantum applications and biomedical instrumentation over the past decade. The development of open-source tools like SuPyMode and PyMieSim highlights his commitment to advancing research methodology in the field. $377,000 awarded for Quantum Photonics Quebec projects (2022) Appointment as director of INTRIQ (2019) Dr. Godbout has supervised an extensive number of graduate students, with 9 completed Ph.D. theses and 21 Master's theses under his guidance, plus one currently in progress. His research has been supported by significant funding, including semiconductor research initiatives that received $120 million from the Canadian government as recently as July 2024. He actively collaborates with industry through Castor Optics, a company he co-founded with Professor Caroline Boudoux that specializes in optical fiber components. As Head of the Fiber Optics Laboratory and researcher at COPL, Dr. Godbout leads a dynamic research team focused on advancing photonics technology. His laboratory work spans from fundamental quantum optics research to practical applications in telecommunications and biomedical imaging. Recent activities include significant contributions to semiconductor research initiatives at Polytechnique Montréal, reflecting his leadership in positioning the institution at the forefront of advanced technology development.

• Photonics
• Optical Fiber Components
• Quantum Cryptography
• +۶ مورد دیگر