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Kuldeep S. Meel is the Stephen Fleming Early-Career Associate Professor at the School of Computer Science, Georgia Institute of Technology, and an Associate Professor at the University of Toronto (on leave). He previously held a NUS Presidential Young Professorship at the National University of Singapore. His research focuses on automated reasoning, aiming to enable computing systems to handle uncertain real-world environments through scalable techniques integrating randomized algorithms, statistical inference, formal methods, distribution testing, and software engineering. Core research areas: Automated Reasoning, Formal Methods, Approximate Model Counting, Probabilistic Inference, Constraint Solving His research group has achieved significant recognition in both individual awards and publications. Key trends in his recent work include advancing model counting algorithms, developing frameworks for probabilistic explanations, and improving scalability in formal verification and constraint satisfaction. His tools have consistently ranked top in international competitions, demonstrating practical impact in automated reasoning. 2019 NRF Fellowship for AI 2022 ACP Early Career Researcher Award 2020 IEEE Intelligent Systems AI's 10 to Watch Top placements in Model Counting, SAT, and CAV competitions He mentors a diverse group of PhD and Master's students and collaborates with institutions worldwide. His group's publications span premier conferences in AI, formal methods, and design automation, reflecting interdisciplinary contributions to theoretical and applied computer science.

• Automated Reasoning
• Formal Methods
• Artificial Intelligence
• +6 more

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
• +8 more

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.

• Real-Time Embedded Systems
• Computer Architecture
• Hardware for Machine Learning/AI
• +9 more

Anoop Sarkar is a Professor in the School of Computing Science at Simon Fraser University (SFU), leading the Natural Language Lab. His research focuses on multilingual natural language processing, machine learning applications in NLP, and machine reading with visualization techniques. He has held significant grants including NSERC Discovery Accelerator Supplements (2012–2023) and multiple Google/IBM Faculty Awards. His teaching includes advanced NLP courses and compiler design. Over 38 students have graduated under his supervision, with a strong emphasis on computational linguistics and machine translation. His research explores areas such as statistical machine translation, decipherment of ancient scripts, and semi-supervised learning. Key software contributions include the TroFi toolkit and metaphor dataset. He has served as area chair for EMNLP (2023) and co-chair of NAACL (2015). The Natural Language Lab hosts weekly meetings open to collaboration. His work bridges theory and application, addressing challenges in low-resource language processing. Recent publications (2023–2024) highlight advancements in entity linking, cognate alignment, and structured prediction. Grants span foundational and applied NLP research, supported by NSERC and industry partnerships. His advising spans 12 PhD and 26 MSc graduates, reflecting a sustained impact on the next generation of NLP researchers.

• Multilingual Natural Language Processing
• Machine Learning for Natural Language Processing
• Statistical Machine Translation
• +3 more

Alexander Summers is an Associate Professor at the Department of Computer Science , University of British Columbia . He joined UBC in March 2020 after serving as a Senior Researcher (Oberassistent) at ETH Zurich from 2014-2020. His research bridges Programming Languages , Formal Methods , and Software Engineering , with a focus on automated verification tools for heap-based and concurrent programs. MSc Joint Mathematics and Computer Science, Imperial College London (2004) PhD Computer Science, Imperial College London (2009) Postdoc, ETH Zurich (2009-2014) Summers leads the Prusti Project , developing deductive verification tools for Rust, and contributes to the Viper Project for intermediate verification languages. His work addresses challenges in: Memory safety and concurrency verification Ownership models and aliasing control Automated reasoning with SMT solvers Resource-oriented programming specifications Debugging verification condition quantifiers Formal validation of verification infrastructure His research has been recognized with a Amazon Research Award and ACM SIGPLAN Distinguished Paper Awards . He teaches courses like Advanced Software Engineering and Program Verifiers and Program Verification , and supervises graduate students in formal verification and Rust-related research.

• Programming Languages
• Formal Methods
• Software Engineering
• +4 more

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
• +5 more

Dr. Leila Notash is a Professor in the Department of Mechanical and Materials Engineering at Queen's University, where she has been a faculty member since 1997. She is a Fellow of Engineers Canada (FEC) and a licensed Professional Engineer with Professional Engineers Ontario (PEO), with significant contributions to engineering education and professional service. Her educational background includes: Bachelor of Science in Mechanical Engineering, Middle East Technical University (Ankara, Turkey) - High Honor Student (2nd out of 166) Master of Applied Science in Mechanical Engineering, University of Toronto PhD in Mechanical Engineering, University of Victoria Dr. Notash's research centers on robotics and mechatronics, with specialized expertise in cable-driven parallel manipulators. Her work integrates kinematics, fault-tolerant design, and neural network applications to address challenges in robot calibration, workspace analysis, and motion control under real-world constraints like cable mass and elasticity. She investigates both theoretical frameworks and practical implementations for industrial and specialized robotic systems. Analysis of her recent publications (2020-2024) reveals a clear trajectory toward intelligent control systems, where machine learning techniques—particularly neural networks and reinforcement learning—are increasingly applied to solve complex problems in cable-driven robotics. This includes motion control optimization, path generation, and kineto-static analysis while accounting for physical limitations such as cable elasticity and mass effects, demonstrating a shift from traditional mechanical analysis to data-driven adaptive control methodologies. Her scientific recognition includes: Fellow of Engineers Canada (FEC) University of Toronto Open Fellowship University of Toronto International Differential Fee Waiver Charles S. Humphrey Graduate Student Award NSERC Doctoral Prize Nominee (1996) Dr. Notash has mentored 161 undergraduate students as Faculty Advisor for the Mechanical '06 cohort and pioneered international educational initiatives like the International Undergraduate Student Design project (IVDS), connecting Queen's University with Middle East Technical University and Union College. Her service extends to editorial leadership for Mechanism and Machine Theory and ASME journals, and governance roles including Faculty Senator at Queen's University (2009-2025) and PEO Council Councillor-at-Large (2019-2025). She has established collaborative research networks through initiatives like the Reading Week shop course 'Design Basics 1.0' and sustained leadership in the Canadian Committee for the Promotion of Mechanism and Machine Science (CCToMM) and the International Federation for the Promotion of Mechanism and Machine Science (IFToMM), where she chaired the Permanent Commission on Communications (2006-2011).

• Robotics
• Mechatronics
• Kinematics
• +3 more

Dr. Mahesh Tripunitara is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, serving as Associate Chair for Undergraduate Studies. He holds a PhD (2005) and Master's (1995) in Computer Science from Purdue University, along with a BSc (1993) in Computer Science from Dalhousie University. His research focuses on information security, authorization mechanisms, cryptographic key management, and hardware security, with industry experience at Motorola's R&D labs and Silicon Valley. His work spans theoretical advancements like access control policy analysis and practical applications such as secure payments systems and IoT device reliability. Notable awards include the Best Student Paper at Usenix Security 2013 and Best Paper at ACM SACMAT 2013. He actively serves on program committees for major security conferences including CCS, CODASPY, and SACMAT. Recent publications highlight innovations in cellular security (SUCI-Catchers defense), role-mining optimization, and blockchain smart contract auditing. Teaching includes advanced algorithm design courses (ECE 406/606) and digital computation (BME 121). His research emphasizes balancing security rigor with usability in authorization systems and hardware protection mechanisms.

• Information Security
• Authorization and Access Control
• Cryptographic Key Transport
• +7 more

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.

• Energy Efficiency in Software
• Multicore Memory Systems
• Hardware/Software Co-Design
• +3 more

Elena Grigorescu is a Professor at the University of Waterloo, Department of Computer Science. She holds a Ph.D. from the Massachusetts Institute of Technology (2010), an M.S. from MIT (2006), and a B.A. from Bard College (2004). Her research focuses on sublinear-time algorithms, error-correcting codes, computational complexity, and learning theory. She explores foundational aspects of algorithms with constraints on time/space, privacy-preserving computation, and applications in graph theory and optimization. Her work includes advancements in spanner algorithms for network design, differential privacy in sublinear-time settings, and learning-augmented approaches for online optimization. Recent publications address trace reconstruction, privacy-utility trade-offs, and combinatorial optimization techniques. Grigorescu is actively involved in conferences like APPROX/RANDOM and IEEE Foundations of Computer Science, contributing to algorithmic theory and practical implementations. Her research emphasizes theoretical rigor while addressing real-world challenges in data analysis and distributed systems. No awards or formal advisees are explicitly listed in the provided information.

• Sublinear-time algorithms
• Error-correcting codes
• Computational complexity
• +3 more

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.

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +12 more

Kashif Raza is a Postdoctoral Fellow at the Department of Educational Studies (EDST) within the Faculty of Education at the University of British Columbia (UBC). His research focuses on multilingual education, TESOL (Teaching English to Speakers of Other Languages), language policies, and systemic issues in education, such as racism and immigration integration. He examines topics like racialized voter behavior, institutional racism in educational leadership, and the role of language in immigrant integration. His work often intersects with critical race theory, sociolinguistics, and policy analysis. Raza’s research spans diverse contexts, including Canadian, Gulf, and South Asian educational systems. He has explored challenges faced by immigrant professionals in healthcare, the impact of digital networks on political engagement, and the design of multilingual curricula. His contributions also include practical guidance for scholars, such as advice on publishing and navigating language policies in higher education. While his profile does not explicitly list educational credentials, his articles indicate deep engagement with global educational challenges. He has collaborated on projects addressing pandemic-era language education and climate action through EDST’s initiatives. No awards or grants are mentioned in the provided texts.

• Educational Policy
• TESOL (Teaching English to Speakers of Other Languages)
• Multilingual Education
• +3 more

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

• Ocean Physics
• Seawater Properties
• Geophysical Fluid Dynamics
• +5 more

Dr. Min Sun is an Associate Professor and Director of the Undergraduate Program in the Department of Civil Engineering at the University of Victoria (UVic). He holds a PhD from the University of Toronto. His research focuses on structural engineering and steel structures, particularly in the areas of steel connections, seismic resilience, and numerical modeling. Dr. Sun has extensive academic and professional experience, including roles as Assistant Professor at UVic (2016–2022), Lecturer at the University of Toronto, and structural design roles in industry. His research interests emphasize the performance of steel structures under extreme loads, including earthquake engineering and material behavior. Recent work includes studies on stress concentration factors in steel connections, thermal integrity of piles, and wood-frame building reliability under lateral loads. He actively contributes to professional organizations, such as serving as Vice President (Western Region) for the Canadian Society for Civil Engineering (2018–2020). Dr. Sun teaches courses including Advanced Structural Analysis (CIVE 421) and Solid Mechanics (CIVE 220) at UVic. He currently supervises graduate students in structural steel design and construction. His publications span experimental and numerical analyses, with a focus on improving design standards for steel and wood structures. Labs/Teams: Affiliated with UVic's Engineering and Computer Science faculty and the IESVIC (Institute for Energy Systems and Sustainability at UVic), though specific lab names are not explicitly stated in the text.

• Structural Engineering
• Steel Structures
• Civil Engineering
• +3 more

Grant Weddell is an Associate Professor in the David R. Cheriton School of Computer Science at the University of Waterloo. His research focuses on database technology for real-time applications, including large-scale schema management, information clustering, dependency theory, and query optimization for heterogeneous data sources. He teaches courses such as CS338 (Introductory Databases), CS348 (Advanced Databases), CS446 (Software Engineering), and CS848 (Advanced Database Systems). His research interests emphasize the interplay between description logics and database systems, particularly in optimizing query processing and managing complex schemas. Recent work explores path agreements, functional dependencies, and ontology-mediated querying to enhance data integration and schema management efficiency. Teaching responsibilities include foundational database courses (CS338/348), software engineering (CS446), and advanced topics in information integration (CS848). No scientific awards are explicitly listed, though his contributions to database theory and optimization are extensive.

• Database Technology
• Real-Time Applications
• Schema Management
• +5 more