جستجوی استاد راهنمای دانشگاهی

Dr. Khurram Aziz is a Senior Instructor in the Faculty of Computer Science at Dalhousie University , Halifax, Canada. He is actively engaged in teaching and research, with a focus on optical networks, data center interconnects, and network performance modeling. Education: PhD in Electrical Engineering, Vienna University of Technology, Austria (2008) MSc in Electrical Engineering, National University of Singapore (2003) BSc (Hons) in Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan (1998) His research interests include optical packet and burst switched networks , optical interconnects for data centers , analytical modeling and simulation , and network routing and switching . He has contributed extensively to the design and performance evaluation of scalable optical switches and hybrid switching systems. The recent publications reflect a strong trend in data center optical networks , focusing on performance, blocking probability, signal degradation, and architectural classification. His work bridges theoretical modeling with practical simulation frameworks, such as CloudNetSim++ in OMNeT++, contributing to cloud and high-capacity network research. Dr. Aziz has no listed scientific awards in the provided text. He teaches several core computer science courses including CSCI 2141: Intro to Database Systems , CSCI 3171: Network Computing , CSCI 3132: Object Orientation and Generic Programming , and CSCI 3120: Operating Systems . There is no mention of graduate student supervision or external research grants. He has co-authored book chapters in major handbooks on data centers and switched systems. Dr. Aziz has not listed any formal lab or research team affiliations in the provided content.

• Optical Networks
• Data Center Networks
• Optical Interconnects
• +۷ مورد دیگر

Henry Yuen is the Srivani Family Associate Professor of Computer Science at Columbia University, with affiliations in the CS Theory group, Data Science Institute, and Columbia Quantum Initiative. His work bridges theoretical computer science and quantum information, focusing on the computational foundations of quantum systems. Yuen received his BA in Mathematics from the University of Southern California (2010) and PhD in Computer Science from MIT (2016). His research explores quantum complexity theory, quantum cryptography, and quantum information through both theoretical frameworks and practical applications. His recent publications reveal a strong focus on quantum pseudorandomness, quantum circuit complexity, and quantum cryptographic primitives. The research trajectory demonstrates increasing sophistication in connecting quantum computational models with fundamental questions in complexity theory, particularly through the lens of quantum interactive proofs and quantum state complexity. His work frequently intersects with operator algebras and quantum information theory, reflecting the interdisciplinary nature of modern quantum computing research. NSF CAREER award Sloan Fellowship Yuen actively mentors graduate students, with several PhD students having graduated to postdoctoral positions or faculty roles. His service includes co-organizing the Columbia CS Theory Seminar and serving on program committees for major conferences including QIP, STOC, and ITCS. He has organized multiple workshops on quantum computing challenges and cryptography. As a member of the Columbia Quantum Initiative, Yuen contributes to Columbia's growing quantum ecosystem, collaborating across departments to advance both theoretical foundations and potential applications of quantum information processing.

• Quantum Computing
• Complexity Theory
• Cryptography
• +۲ مورد دیگر

Professor Peter F. Driessen is a faculty member in the Department of Electrical and Computer Engineering at the University of Victoria, with a cross-appointment in the School of Music. He holds a BSc and PhD from the University of Victoria and is a Professional Engineer (PEng). His research focuses on communication systems, signal processing, control, and interdisciplinary projects in computer music and wireless technologies. Key areas include audio/video signal processing, radio propagation, sound recording, and multimedia systems. He leads the University of Victoria Propagation Laboratory, which explores radio wave propagation and Amateur radio integration with engineering education. His work spans theoretical research and applied projects like ECOSat satellite systems, software-defined radio (SDR), and innovative musical instruments such as the Radio Drum. He supervises undergraduate and graduate projects in these domains through ELEC 499 courses. Notable contributions include the APEGBC Editorial Board Award for Best Paper (2002) and patents in wireless networking and signal processing. His teaching includes courses in signal analysis and electromagnetics, and he collaborates on interdisciplinary programs like the Music/Computer Science degree. Education: BSc in Electrical Engineering, University of Victoria PhD in Electrical Engineering, University of Victoria Research Interests: Audio and video signal processing for music and media Software-defined radio and Amateur radio technologies Satellite communication and ground station development Gesture-based interfaces and musical instrument design Error mitigation in streaming audio/video Optical and microwave-photonic systems Labs & Collaborations: Propagation Laboratory (radio wave research) UVic Experimental Radio Group (Amateur radio club) UVic Satellite Design Team (ECOSat projects) UVic Centre for Aerospace Research Grants & Awards: APEGBC Editorial Board Award (2002) Multiple US patents in wireless systems and signal processing

• Communication
• Signal Processing
• Control Systems
• +۶ مورد دیگر

Lan Wei is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. She leads the Waterloo Emerging Integrated Systems Group, focusing on device-circuit co-optimization, cryogenic CMOS for quantum computing, and emerging technologies like GaN, RRAM, and low-dimensional materials. Her work bridges nanoelectronics and system-level applications, with notable contributions to the MIT Virtual Source GaN HEMT (MVSG) compact model, an industry-standard tool. Education: B.S. in Microelectronics and Economics, Peking University (2005) M.S. and Ph.D. in Electrical Engineering, Stanford University (2007, 2010) Research Interests: Nanoelectronic devices Cryogenic CMOS for quantum computing GaN-based circuits and systems RRAM-based neuromorphic computing Device-circuit interactive design Publications reflect her expertise in GaN modeling, quantum computing hardware, and RRAM applications. Recent work emphasizes scalable quantum control circuits and error-resilient neural networks using emerging technologies. Awards include the 2019 Ontario Early Researcher Award and the 2020 UWaterloo President's Excellence Award in Research. She has served on technical committees for IEDM, DATE, and ICCAD, and contributed to the ITRS roadmap. Teaching includes courses like ECE 240 (Electronic Circuits) and ECE 730 (Solid State Devices). Her group actively seeks graduate students with interest in integrated systems and nanoelectronics.

• Nanoelectronic devices
• Cryogenic CMOS electronics
• GaN-based devices and circuits
• +۵ مورد دیگر

Halim Yanikomeroglu is a Full Professor and Chancellor's Professor at Carleton University's Department of Systems and Computer Engineering, part of the Faculty of Engineering and Design. His research focuses on wireless communications, including 5G/6G networks, non-terrestrial systems (HAPS/LEO satellites), MIMO, and cognitive radio. He has supervised numerous graduate students and holds IEEE Fellow status and the Harold Sobol Award. His work integrates machine learning, federated learning, and sustainability into next-generation networks. Affiliations: Carleton University, IEEE Education: Ph.D. (Toronto), M.A.Sc. (Toronto), B.Sc. (Middle East Technical University) Research interests span cellular networks, relay architectures, and energy-efficient systems. He pioneered cell-switching strategies for green networks and contributed to HAPS and UAV-based infrastructure. His recent work addresses NTN integration, AI-driven spectrum management, and 6G innovations. Awards include IEEE Fellow (2017) and multiple Research.com leadership accolades. His 150+ publications span journals like IEEE Transactions and conferences like ICC. Advising over 50 students, he emphasizes interdisciplinary solutions for future wireless challenges.

• Wireless Communications
• 5G/6G Networks
• Cellular Networks
• +۹ مورد دیگر

Yuanzhu Chen is a Professor in the School of Computing at Queen’s University, affiliated with the Faculty of Arts and Science. He previously served as Professor and Department Head at Memorial University of Newfoundland (2005–2021). His research focuses on computer networking, mobile computing, complex networks, and applied machine learning, emphasizing wireless innovation beyond traditional wired systems. He holds a PhD from Simon Fraser University (2004) and a B.Sc. from Peking University (1999). Education: PhD in Computing Science (Simon Fraser University, 2004); B.Sc. in Computer Science (Peking University, 1999). Earlier roles include Post-doctoral Researcher at Simon Fraser University (2004–2005) and leadership positions at Memorial University, including Department Head (2019–2021). Research Interests: Network Coding and Opportunistic Routing Mobile and Wireless Network Protocols Complex Network Analysis Machine Learning Applications Indoor Positioning Systems Social Network Dynamics Selected Awards: Recipient of Queen’s University President's Award for Distinguished Teaching. Lab Affiliation: Director of the Wireless Networking and Mobile Computing Lab (WineMocol). Active in collaborative projects involving smartphone sensors, community-based environmental monitoring, and stock market prediction using web data.

• Computer Networking
• Mobile Computing
• Complex Networks
• +۵ مورد دیگر

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
• +۳ مورد دیگر

Alaa Alameldeen is an Associate Professor in the School of Computing Science at Simon Fraser University (SFU), part of the Faculty of Applied Sciences. Previously, he worked as a Research Scientist at Intel Labs (2006–2020) and held an Adjunct Faculty position at Portland State University (2008–2018). He earned a PhD in Computer Sciences from the University of Wisconsin-Madison (2006), and earlier degrees from Alexandria University, Egypt. His research focuses on computer architecture, including memory systems (processing-in-memory, cache/memory compression, security), energy-efficient architectures, and hardware-software co-design for machine learning. He advises PhD and MSc students in these areas and teaches advanced computing science courses. Key contributions include innovations in memory hierarchies, cache compression techniques, and mitigating hardware vulnerabilities. His work has been published in top conferences (e.g., ISCA, MICRO, HPCA) and patented in areas like near-memory processing and error correction. Alameldeen currently leads a research group exploring secure and high-performance memory architectures. He has supervised multiple graduate students, with many progressing to roles at leading tech companies and academic institutions.

• Computer Architecture
• Memory Systems
• Hardware Security
• +۵ مورد دیگر

Yoshua Bengio is a Full Professor at the Université de Montréal, affiliated with the Department of Computer Science and Operations Research at the Faculty of Arts and Sciences. He is a pioneer of deep learning and a leading figure in AI safety. He co-founded Mila – Quebec Institute of Artificial Intelligence and serves as its scientific director. His work focuses on advancing AI technology while addressing ethical and safety challenges, including AI governance and catastrophic risk mitigation. Education: Ph.D. in Computer Science from McGill University (1991), postdoctoral studies at MIT. Research interests include deep learning, causal inference, AI ethics, and responsible AI development. He contributed to the Montreal Declaration for Responsible AI and leads the International Scientific Report on AI Safety. Recent articles emphasize AI safety frameworks, governance, and technical advancements in machine learning. Awards include the Turing Award (2018), Killam Prize (2019), and recognition as TIME's Most Influential Person (2024). He holds prestigious fellowships and is a member of the UN Scientific Advisory Board for Breakthrough Science and Technology. Affiliations include Mila, IVADO (as founding scientific director), and CIFAR programs. His work bridges academia, industry, and policy to ensure AI benefits humanity while minimizing existential risks.

• Artificial Intelligence
• Deep Learning
• AI Safety
• +۷ مورد دیگر

Mohammad Hajiabadi is an Assistant Professor at the University of Waterloo's Department of Computer Science. His research focuses on theoretical cryptography, including cryptographic protocols, functional encryption, and secure communication. He holds a PhD in Computer Science from the University of Victoria (2016), a Master of Science from the same institution (2011), and a Bachelor of Science from Sharif University of Technology (2009). His research explores foundational aspects of cryptography, such as cryptographic assumptions, algorithmic lower bounds, and privacy-preserving techniques. Notable areas include registration-based encryption, secret sharing schemes, and the black-box complexity of cryptographic primitives. His work often intersects with theoretical computer science, addressing challenges in secure computation and efficient protocol design. Dr. Hajiabadi's publications span topics like trapdoor functions, oblivious transfer, and private set intersection, demonstrating a commitment to advancing both the theory and practical applications of cryptography. He has secured collaborative research funding, including a National Science Foundation grant for expanding oblivious transfer tools. His contributions to academic grants and collaborative projects highlight his role in shaping modern cryptographic frameworks.

• Theoretical Cryptography
• Cryptography
• Computer Science
• +۳ مورد دیگر

Laura Collins is an Associate Professor in the Department of Education at Concordia University, specializing in applied linguistics. Her research focuses on input processing in second language acquisition, pedagogical grammar, and cross-linguistic influence among bilingual speakers. She has extensive international teaching experience across diverse age groups and serves as the 2nd VP of the American Association for Applied Linguistics and Chair of the IRIS digital repository advisory board. PhD in Humanities, Concordia University MEd in Second Language Teaching, University of Ottawa BEd in Second Language Teaching, University of Toronto BA in History, York University Collins' current projects examine the use of speech technologies to extend second language classrooms and document longitudinal grammatical development in school programs. Funded by SSHRC Insight Grants, her work bridges cognitive approaches with practical pedagogical applications. Recent publications highlight trends in classroom input optimization, frequency-based phonological learning, and intensive language program efficacy, with subfields spanning morpheme perception, vocabulary distribution, and task-based interaction dynamics. Her academic leadership includes editorial roles in The Modern Language Journal and contributions to major handbooks. She teaches courses ranging from classroom-based SLA research to pedagogical grammar, emphasizing practical applications of theoretical insights.

• Applied Linguistics
• Bilingualism
• Language Acquisition
• +۳ مورد دیگر

Gururaj Saileshwar is an Assistant Professor in the Department of Computer Science at the University of Toronto, within the Mathematical and Computational Sciences school. His research focuses on securing computing hardware and systems, with a focus on microarchitectural security (cache side-channels, Rowhammer attacks), system security (memory safety), and security for machine learning systems. Education: PhD in Computer Science from Georgia Institute of Technology (2019), advised by Prof. Moinuddin Qureshi. B.Tech and M.Tech from Indian Institute of Technology Bombay (India). Prior to UofT, he was with NVIDIA Research. Research interests include developing new attacks, defenses, and tools for automated security analysis. His work has received multiple awards including the IEEE Top Pick in Hardware and Embedded Security, HPCA Best Paper Award, and IEEE HOST Best PhD Dissertation Award. He teaches courses on secure computer systems and hardware security, including CSC427 (Computer Security) and a topics course on secure computer systems. His lab focuses on hardware-software co-design solutions for security and reliability challenges in modern computing systems. Labs/Teams: Leads the Secure Hardware Systems Lab at UofT, collaborating on Rowhammer mitigation, cache attack defenses, and machine learning security. Grants: Active funding from NSF, industry partnerships with NVIDIA, and other hardware security initiatives. Advising: Currently recruiting PhD students interested in hardware security, system security, and machine learning systems security.

• Microarchitectural Security
• System Security
• Memory Safety
• +۵ مورد دیگر

Guillaume Bourque is a Professor in the Department of Human Genetics at McGill University's Faculty of Medicine. He serves as an Investigator at the Victor Phillip Dahdaleh Institute of Genomic Medicine and as the Scientific Director of the Canadian Centre for Computational Genomics (C3G). His laboratory is based at 740 Dr Penfield Ave, Room 6103, Montréal, Québec, Canada, H3A 1A4, where he leads research in computational genomics and bioinformatics. Professor Bourque's research focuses on understanding mammalian genomes using comparative genomic and epigenomic analyses. His lab investigates the evolution of regulatory sequences , the role of transposable elements in gene regulation , and the impact of genome rearrangements in evolution and cancer . His team develops computational methods and resources for the functional annotation of genomes with special emphasis on sequencing-based assays including ChIP-seq, RNA-Seq, exome- and whole-genome sequencing, and single-cell analysis. The lab's work involves examining billions of DNA base pairs to interpret how variation impacts basic biology and disease. Recent publications (2024-2025) demonstrate Bourque's leadership in pangenome graph construction , transposable element analysis , epigenomic profiling , and cancer genomics . His work spans multiple disciplines from basic genome evolution to clinical applications in cancer and infectious disease. Notable projects include the development of tools like DeepPolisher for genome assembly polishing and contributions to understanding the genomic basis of long COVID. Bourque's laboratory is actively recruiting postdocs and graduate students with backgrounds in programming or statistics. The lab emphasizes quantitative approaches to biology, requiring applicants to have experience in quantitative biology as a plus. His collaborative work extends across multiple institutions and international consortia, reflecting the interdisciplinary nature of modern genomic research.

• Bioinformatics
• Computational Genomics
• Comparative Genomics
• +۵ 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

Ashish Khisti is an Associate Professor at the University of Toronto's Department of Electrical and Computer Engineering (ECE), where he directs the Signals, Multimedia and Algorithms Laboratory (SMA Lab). He holds the Canada Research Chair (Tier II) and maintains affiliations with the Vector Institute for Artificial Intelligence. His research bridges communication systems, information-theoretic security, and machine learning, with a focus on real-time streaming and privacy-preserving algorithms. Research Trends: Recent publications emphasize streaming codes for latency-sensitive networks , machine learning-driven compression , and privacy mechanisms in federated learning . Scientific Recognition: Canada Research Chair (Tier II), 2012 and 2017 renewal Cisco Research Center Award, 2017 Ontario Early Researcher Award, 2012 Best Paper at NeurIPS 2021 Deep Generative Models Workshop Academic Contributions: Supervised PhD students Ahmed Badr, Farrokh Etezadi, and Si-Hyeon Lee. Served as Associate Editor for IEEE Transactions on Communications (2012-2015) and IEEE Transactions on Information Theory (2015-2018). Labs & Collaborations: Leads the Signals, Multimedia and Algorithms Laboratory, collaborating with institutions like KAUST, Texas A&M University (Qatar), and the Vector Institute. Organized workshops at BIRS and IEEE conferences.

• Communication Systems
• Information Theoretic Security
• Machine Learning
• +۴ مورد دیگر