جستجوی استاد راهنمای دانشگاهی

Hiren Patelمشاهده پروفایل

استاد

• Real-Time Embedded Systems
• Computer Architecture
• Hardware for Machine Learning/AI
• +۹ مورد دیگر

Dr. Hiren Patel is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a Doctorate in Computer Engineering from Virginia Tech and previously worked as a postdoctoral fellow at UC Berkeley under Edward A. Lee. His research focuses on real-time embedded systems, computer architecture, machine learning hardware, and cybersecurity. He teaches courses like ECE 150 (Programming), ECE 320/429 (Computer Architecture), and ECE 327 (Digital Systems). Research Interests: Cyber-physical systems and hybrid architectures Hardware/software co-design methodologies Predictable cache coherence protocols IoT and edge computing systems Security in embedded and real-time systems Recent work emphasizes cache coherence solutions for safety-critical systems and GPU acceleration strategies. His publications address challenges in multicore predictability, FPGA bandwidth optimization, and autonomous robotics orchestration. No specific awards are listed, though his extensive publication record indicates significant contributions to embedded systems research. He currently oversees graduate student applications focusing on his core research areas.

• Energy Efficiency in Software
• Multicore Memory Systems
• Hardware/Software Co-Design
• +۳ مورد دیگر

Arrvindh Shriraman is an Associate Professor and Program Director of Software Systems at Simon Fraser University's School of Computing Science in Surrey. His research focuses on energy-efficient software, multicore memory systems, and optimizing hardware/software interfaces for parallel programming. He holds a Ph.D. (2010) and M.S. (2006) in Computer Science from the University of Rochester, and a B.Eng. (2004) from the University of Madras. He teaches courses on parallel programming and energy-conscious software design. His research interests include synchronization mechanisms for domain-specific architectures, cache optimization, and FPGA-based acceleration. He has contributed to frameworks like Mu-grind for HLS-generated RTL instrumentation and TAPAS for parallel accelerator generation. Notable projects include RANGE-BLOCKS for synchronization in domain-specific systems and TapeFlow for gradient computation in neural networks. His work emphasizes real-time verification of autonomous systems and safety-critical trajectory planning for underwater vehicles. Shriraman collaborates closely with the Tangent Lab, exploring cutting-edge solutions in hardware-software co-design and embedded systems. His teaching and research bridge theoretical computer science with applied engineering challenges, addressing scalability, efficiency, and safety in modern computing systems.

Mohamed Hassanمشاهده پروفایل

استادیار

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +۱۲ مورد دیگر

Dr. Mohamed Hassan is an Assistant Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on Cyber-Physical Systems-on-Chip (iCPSoCs) , emphasizing design, analysis, and deployment for critical domains like Unmanned Aerial Vehicles (UAVs), Autonomous Cars, and healthcare systems. Key research areas include hardware/software codesign, real-time systems, embedded systems, and security. He teaches courses such as COMPENG 4DM4 (Computer Architecture) and COMPENG 4DS4 (Embedded Systems) . His work bridges foundational theories (e.g., scheduling, AI) with infrastructure-level innovations (e.g., compilers, memory systems). The Fanos Research Lab he leads explores interdisciplinary solutions for efficient CPS-on-Chip, addressing challenges in multicore predictability, memory latency, and edge computing. Recent contributions include frameworks for explainable memory-centric workloads and techniques to accelerate TinyML inference. Dr. Hassan serves on Technical Program Committees for conferences like RTAS and OSPERT, highlighting his role in advancing real-time embedded systems research.

Trevor Brownمشاهده پروفایل

دانشیار

• Concurrent Data Structures
• Lock-Free Algorithms
• Transactional Memory
• +۴ مورد دیگر

Trevor Brown is an Associate Professor in the Computer Science department at the University of Waterloo, affiliated with the Cheriton School of Computer Science. He leads the Multicore Lab and specializes in concurrent data structures, non-blocking algorithms, and memory management. His research bridges theory and systems, focusing on practical implementations of lock-free trees, transactional memory, and techniques for non-uniform memory architectures. Education includes a PhD in Computer Science from the University of Toronto and a B.Sc. in Computer Science and Mathematics from York University. Research interests center on concurrent systems, with recent work exploring hardware-accelerated indexing, memory reclamation techniques, and performance anomalies in microbenchmarks. His publications demonstrate consistent innovation in parallel computing, with articles frequently appearing at top conferences like PPoPP, SPAA, and DISC. Sustainable energy research includes optimizing hybrid power systems and battery storage solutions. Awards include multiple best paper/artifact recognitions at SPAA and PPoPP, teaching excellence honors, and nominations for the Governor General’s Gold Medal. Extensive advising includes 13+ graduate students and PDFs, with research grants exceeding $965K from NSERC, Huawei, and CFI. He directs the Multicore Lab, developing open-source tools like SetBench for rigorous performance benchmarking.

Meng Xuمشاهده پروفایل

استادیار

• System Security
• Software Security
• Automated Program Analysis
• +۴ مورد دیگر

Meng Xu is an Assistant Professor in the Cheriton School of Computer Science at the University of Waterloo, Canada. He is affiliated with the Cryptography, Security, and Privacy (CrySP) group and the Cybersecurity and Privacy Institute (CPI). His research focuses on system and software security, emphasizing secure-by-design languages (e.g., Rust, Move), automated program analysis, and runtime defense techniques. Education : Ph.D., Computer Science (2020), Georgia Institute of Technology B.Eng. and B.Business (First Class Honors), Nanyang Technological University (2014) Research Interests : Secure-by-design languages Automated security analysis (fuzzing, symbolic execution) Runtime defense mechanisms (moving target defense, secure hardware) Key Awards : EAPLS Best Paper Award (2022) USENIX Security Distinguished Paper Award (2018) Grants & Funding : BlackBerry Research Grant (CAD $200,000) Amazon Research Award (USD $60,000) NSERC Discovery Grant (CAD $170,000) Labs & Collaborations : CrySP (Cryptography, Security, and Privacy Group) Cybersecurity and Privacy Institute (CPI)

Lesley Shannonمشاهده پروفایل

دانشیار

• Computer Engineering
• Reconfigurable Computing
• FPGA CAD Tools
• +۶ مورد دیگر

Lesley Shannon is an Associate Professor in the School of Engineering Science at Simon Fraser University (SFU), specializing in computing system design and reconfigurable computing. She leads the Reconfigurable Computing Lab (RCL), focusing on FPGA-based architectures, heterogeneous multicore systems, and CAD tools. Her academic journey includes a B.Sc. from the University of New Brunswick (1999), M.A.Sc. and Ph.D. from the University of Toronto (2001 and 2006). Her research spans FPGA CAD algorithms, Networks-on-Chip (NoCs), dynamic partial reconfiguration (DPR), and application-specific architectures. Key projects include FUSE (OS abstraction for hardware accelerators), PolyBlaze (multicore system emulation), and uROAMs (microfluidic reconfigurable devices). She has secured funding from NSERC, Xilinx, and Altera, among others. Education: B.Sc., Electrical Engineering (Computer Option), University of New Brunswick, 1999 M.A.Sc., Applied Science, University of Toronto, 2001 Ph.D., Applied Science, University of Toronto, 2006 Roles: NSERC Chair for Women in Science and Engineering (BC/Yukon) Faculty Advisor, SFU WEST (Women in Engineering, Science, and Technology) Her lab employs 5 current students and has graduated 7, including work on FPGA CAD, microfluidics, and embedded systems. Courses taught include Advanced Digital Systems Design and Real-Time/Embedded Systems. Her research emphasizes reducing design time through on-chip profiling and CAD tools, with applications in biomedical imaging and quantum computing. Awards & Grants: NSERC Discovery Grant NSERC Strategic Grant (Lead PI, 2009; Co-PI, 2010) SFU Startup Grant and President’s Research Grant Lab & Collaborations: The RCL develops silicon and non-silicon architectures, including quantum computing and microfluidic systems. Partnerships include industry collaborations and open-source tools like Odin II synthesis framework.

Trevor Brownمشاهده پروفایل

دانشیار

• Concurrent Data Structures
• Lock-Free Algorithms
• Transactional Memory
• +۳ مورد دیگر

Trevor Brown is an Associate Professor in the Department of Computer Science at the University of Waterloo. Previously, he held positions as an Assistant Professor at the same institution, and completed postdoctoral research at the Institute of Science and Technology (IST) Austria under Dan Alistarh, and at the Technion – Israel Institute of Technology under Hagit Attiya. He earned his PhD from the University of Toronto under Faith Ellen's supervision, where he was part of the theory group. His research focuses on concurrent data structures, particularly lock-free algorithms, transactional memory, non-volatile memory systems, and techniques for non-uniform memory architectures (NUMA). He leads the UW Multicore Lab, which explores high-performance parallel computing and distributed systems. His work emphasizes rigorous experimental validation and practical implementations, reflected in extensive open-source code repositories. Brown has taught courses including CSC798 (Multicore Programming) and CSC341 (Algorithms), and has served as a teaching assistant for multiple computer science courses at the University of Toronto and York University. He maintains active collaborations through implementations of concurrent data structures (e.g., lock-free (a,b)-trees, B-slack trees) and benchmarks in the Setbench project.

Dhrubajyoti Goswamiمشاهده پروفایل

دانشیار

• High-Performance Scientific Computing
• Parallel and Distributed Computing
• Blockchain Sharding
• +۳ مورد دیگر

Dhrubajyoti Goswami is an Associate Professor and Graduate Program Director in the Department of Computer Science and Software Engineering at Concordia University, Montreal. He holds a PhD from the University of Waterloo, with prior degrees from McGill University and the Indian Institute of Science. His research focuses on high-performance computing, parallel algorithms, and distributed systems, with recent work emphasizing blockchain sharding and fault tolerance in distributed environments. Dr. Goswami teaches courses such as Operating Systems, Parallel Programming, and Distributed Systems, reflecting his expertise in system software and parallel computing. His publications span conferences like IEEE SBAC-PAD, IEEE ICBC, and IEEE ISPDC, addressing challenges in GPU computing, scalable algorithms, and blockchain optimization. He has secured grants including NSERC Discovery and CFI funding, supporting research in high-performance systems. Dr. Goswami’s advisory work includes supervising over 20 graduate and undergraduate students, with notable contributions in areas like efficient matrix multiplication on GPUs, hierarchical blockchain architectures, and fault-tolerant distributed systems. His professional memberships include IEEE Senior Member status.

Ali José Mashtizadehمشاهده پروفایل

دانشیار

• Operating Systems
• Distributed Systems
• Storage Systems

Ali José Mashtizadeh is an Associate Professor at the Cheriton School of Computer Science, University of Waterloo. His research focuses on operating systems, distributed systems, and storage, with expertise in system reliability, network optimization, and concurrent programming. Education: Ph.D., Computer Science, Stanford University (2017) M.S., Computer Science, Stanford University (2017) M.Eng., Electrical Engineering and Computer Science, MIT (2007) B.S., Electrical Engineering, MIT (2006) His research centers on designing scalable and reliable systems, with recent publications exploring TCP network frameworks, in-memory data persistence, and microsecond-scale scheduling. Key themes include optimizing tail latency, neutralization-based memory reclamation, and fault-tolerant distributed services. His articles consistently demonstrate innovations in low-latency networking, operating system architecture, and cloud infrastructure, with recent emphasis on serverless benchmarks and processor customization. No scientific awards or advising relationships are detailed in the provided materials.

Bin Guoمشاهده پروفایل

استادیار

• Parallel and Distributed Computing
• Graph Algorithms
• Graph Mining
• +۵ مورد دیگر

Bin Guo is an Assistant Professor at the Computer Science Department of Trent University (since Jan. 2024) and an Adjunct Assistant Professor at the Computing & Software Department of McMaster University. He holds a PhD in Computer Science from McMaster University (2023) and an MSc in Applied Computer Science from Winnipeg University (2018). His research focuses on parallel/distributed computing, graph algorithms, and computer security for data analytics, with notable contributions to federated k-core decomposition and secure distributed algorithms. He teaches courses in database systems, operating systems, and computer security at Trent University and has taught at McMaster University. Education: PhD in Computer Science, McMaster University (2023) MSc in Applied Computer Science, Winnipeg University (2018) Research Interests: Parallel and Distributed Computing Graph Algorithms and Mining Computer Security & Privacy Federated Learning Concurrent Data Structures Advising & Grants: Current advisees: Gregory Prouty, Michael Abiona, Syed Zarif Past advisees: Igor Jardim-Martins, Issec Lee Funding sources: Graduate Teaching Assistantships, Research Fellowships, Trent University Research Development Grants Labs & Teams: Leading research projects in parallel graph algorithms and federated security algorithms Collaborating with McMaster University on PhD/Master's co-supervision

Kenneth B. Kentمشاهده پروفایل

استاد

• Hardware/Software Co-Design
• Virtual Machines
• Reconfigurable Computing
• +۷ مورد دیگر

Professor Kenneth B. Kent is a full-time academic at the Faculty of Computer Science , University of New Brunswick, holding the Barrett Chair in Entrepreneurship for Digital Transformation and directing the IBM Centre for Advanced Studies - Atlantic. His research focuses on Hardware/Software Co-Design , Virtual Machines , Reconfigurable Computing , and Embedded Systems , with collaborations at the Institute for Visual Computing, Hochschule Bonn-Rhein-Sieg. Ph.D. & M.Sc. - University of Victoria B.Sc. - Memorial University of Newfoundland Kent's work bridges FPGA architecture optimization, cloud computing resource management, and Java virtual machine enhancements. He supervises numerous graduate students including Alireza Azadi (PhD) and Scott Young (MCS), while mentoring alumni like Maria Patrou (PhD) and Konstantin Nasartchuk (PhD). His recent publications (2020-2014) span FPGA modeling ( VTR 8.0 ), garbage collection interference, and workflow-aware storage systems. He teaches advanced topics including Virtual Machines and FPGA CAD , while maintaining technical expertise in runtime optimization and reconfigurable architectures. Outside academia, Kent is known for his 1968 Mustang restoration and extensive cycling adventures across the Greek Islands , Newfoundland, and the Canadian Maritimes.

Ziqiang Patrick Huangمشاهده پروفایل

استاد آموزشی

• Computer Architecture
• Software/Hardware Co-design
• Compiler Performance Optimization
• +۳ مورد دیگر

Ziqiang Patrick Huang is an Assistant Professor, Teaching Stream in the Department of Electrical and Computer Engineering at the University of Waterloo, School of Engineering. His research focuses on high-performance and energy-efficient computer architectures, with an emphasis on software/hardware co-design under power and thermal constraints, compiler-assisted performance optimization, and dynamic resource allocation mechanisms. He holds a PhD (2019) and MS (2014) in Electrical and Computer Engineering from Duke University, and a BS (2012) from East China University of Science and Technology. He has taught multiple courses including CS 450/650 (Computer Architecture), ECE 222 (Digital Computers), ECE 250 (Algorithms and Data Structures), ECE 350 (Real-Time Operating Systems), and ECE 621 (Computer Organization) in recent years. His publications span topics such as FPGA NoC design, thermal management in microarchitectures, and dynamic resource allocation strategies. No scientific awards are explicitly listed. He is not currently accepting graduate students.

Nachiket Kapreمشاهده پروفایل

دانشیار

• Concurrent and Spatial Architectures
• Parallel Processing
• Heterogeneous Architectures
• +۴ مورد دیگر

Nachiket Kapre is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada (2023–present). He previously held positions as Associate Professor (2016–2021) and on leave as Research Director at Xilinx Labs (AMD Research, Singapore, 2022–2023). Before that, he was an Assistant Professor at Nanyang Technological University (NTU), Singapore (2012–2016) and a Junior Research Fellow at Imperial College London (2010–2012). He earned a Ph.D. and two M.S. degrees from the California Institute of Technology (2010), and a B.E. from the University of Pune (2002). His research focuses on Concurrent and Spatial Architectures , Parallel Processing , and Communication-Centric Design , with a strong emphasis on FPGA-based acceleration for applications like machine learning, graph algorithms, and embedded systems. Key contributions include Hoplite NoC architectures and CaffePresso for deep learning acceleration. Notable awards include the FPT Best Paper Award (2024), TRETS Best Paper Award (2023), and the CASES 2016 Best Paper Award. He has led multiple grants, including NSERC Discovery Grants and A*STAR-funded projects. His advising spans 15+ students across PhD and MSc levels, contributing to FPGA toolflows, NoC design, and hardware acceleration. He has authored over 50 publications in top venues like FPGA, FPL, and ACM TRETS, and serves as a program chair for FCCM 2023. His work bridges theory and practice, emphasizing energy-efficient computing and reconfigurable systems.

Gabriel A. Wainerمشاهده پروفایل

استاد

• Discrete-Event Modeling and Simulation
• Real-Time Systems
• Cellular Models
• +۴ مورد دیگر

Professor Gabriel A. Wainer holds a Ph.D. from the Universidad de Buenos Aires and is a Full Professor at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. His research focuses on Discrete-Event Modeling and Simulation (DEVS), Real-Time Systems, and Parallel/Distributed Simulation. He leads the Advanced Real-Time Simulation (ARS) Lab at Carleton's V-Sim Centre, collaborating with industry partners like Ericsson Canada on projects such as channel reconstruction for wireless networks and AI-driven spectrum sharing. Wainer is a Fellow of the Society for Modeling and Simulation International (SCS) and an ACM Distinguished Speaker, with over 450 publications and significant grant funding. He has mentored numerous students and researchers, contributing to Carleton's academic and research excellence. Education: Ph.D. (Computer Science, Universidad de Buenos Aires, 1998), M.C.S. (Universidad de Buenos Aires, 1993). He has held visiting roles at institutions worldwide, including INRIA and the University of Nice. Research interests include DEVS formalism, cellular models, and real-time operating systems. His work bridges theory and application, addressing challenges in embedded systems, IoT, and pandemic modeling. Awards include the McLeod Founder Award (2022), SCS Outstanding Professional Achievement (2020), and IEEE Outstanding Engineering Award (2019). Labs/Teams: Advanced Real-Time Simulation Lab (ARS), part of Carleton's V-Sim Centre. Grants: Over $4.3M as PI and $1.2M as co-applicant, totaling $30M+ in collaborative funding. Advising: Supervised 12 postdocs, 19 PhDs, 16 RAs, 71 MSc students, and 150+ undergrads since 1997.

Rodolfo Pellizzoniمشاهده پروفایل

استاد

• Real-Time Systems
• Embedded Systems
• Computer Architecture
• +۳ مورد دیگر

Rodolfo Pellizzoni is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. His research focuses on real-time systems, embedded systems, and computer architecture, with an emphasis on time-predictable computing, multicore systems, and FPGA networks. He has contributed extensively to cache management, memory resource coordination, and security-aware scheduling in critical systems. His work includes designing frameworks like HopliteRT for FPGA NoCs, optimizing memory bandwidth regulation, and addressing challenges in mixed-criticality systems. Pellizzoni is affiliated with the Faculty of Engineering and maintains a research group focused on hardware-software co-design for real-time applications. His research bridges theoretical models (e.g., Network Calculus) with practical implementations, emphasizing latency reduction and resource predictability in heterogeneous platforms. Recent publications highlight advancements in cache partitioning, dynamic memory allocation, and scheduling algorithms for multicore processors. His work often appears in top-tier conferences like Euromicro Conference on Real-Time Systems (ECRTS) and journals focusing on embedded and real-time systems.