Amr Youssef is a Professor at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on applied cryptography, network security, cyber-physical systems security, blockchain, and privacy. He has contributed extensively to securing smart grids, IoT devices, and web applications through cryptographic protocols and machine learning-driven solutions. His work addresses critical challenges in cybersecurity, including e-voting systems, fault-tolerant differential protection, and privacy-preserving communication protocols. He explores vulnerabilities in modern systems such as SSO permissions, JavaScript exploits, and stalkerware tools, while developing frameworks like MEGR-APT for APT detection and TEE-Receipt for non-repudiation. Youssef’s research integrates interdisciplinary approaches, combining cryptography with AI (e.g., vision transformers for power quality analysis) and leveraging trusted execution environments (TEE) for secure computing. His projects often involve collaboration with industrial standards (e.g., IEC 61850), emphasizing practical implementations in real-world systems.
Florian Kerschbaum is a Professor and NSERC/RBC Industrial Research Chair in Data Security at the Cheriton School of Computer Science, University of Waterloo. His research focuses on data security and privacy, applied cryptography, and confidentiality in data science. Research interests span data collection/preparation management, secure multi-party computation, homomorphic encryption, differential privacy, and machine learning robustness/privacy. His work develops cryptographic solutions for practical data management challenges in distributed systems.
Anwar Hithnawi is an Assistant Professor of Computer Science at the University of Toronto, where he leads the Privacy Preserving Systems Lab (PPS Lab). His research focuses on data privacy, applied cryptography, and secure systems, with emphasis on privacy-preserving machine learning, federated learning, and encrypted data processing. He holds a Ph.D. in Computer Science from ETH Zurich and was a postdoctoral researcher at UC Berkeley. Previously, he served as an Ambizione Fellow and research group leader at ETH Zurich. Research Interests: Data Privacy & Security Applied Cryptography (Homomorphic Encryption, Zero-Knowledge Proofs) Privacy-Preserving Systems (Federated Learning, Secure Analytics) IoT Security & Privacy Secure Collaborative Learning Awards: Google Research Award SNF Ambizione Grant ETH Medal for Outstanding Master Thesis (student Lukas Burkhalter) Microsoft Research Ph.D. Award (student Lukas Burkhalter) Lab Activities: The PPS Lab develops systems for privacy-preserving computation, secure collaborative learning, and encrypted data stream processing. Notable projects include Zeph, HECO, and Cohere. Recent achievements include acceptance of DPolicy at IEEE S&P 2025 and RoFL at Oakland 2023.
Noman Mohammed is an Associate Professor of Computer Science at the University of Manitoba’s Faculty of Science, leading the Data Security & Privacy (DSP) laboratory. He specializes in privacy-preserving techniques for data sharing, addressing challenges in healthcare, genomic, and financial data. In 2020, he received the Terry G. Falconer Memorial Rh Institute Foundation Emerging Researcher Award for his contributions to bridging privacy and data utility gaps. His research focuses on balancing data accessibility and individual privacy through technical solutions like federated learning, differential privacy, and secure genomic data processing. He emphasizes integrating policy guidelines with advanced technologies to mitigate privacy risks from interconnected data sources. Notable achievements include developing toolkits for data anonymization and federated learning frameworks, as well as advancing methods to secure cloud-based data storage and analysis. His work aligns with societal needs for robust privacy mechanisms in an era of expanding personal data collection. Future objectives involve addressing privacy challenges in emerging technologies, such as heterogeneous data integration and scalable systems for personal data management. Despite his research focus, he notably avoids social media platforms.
Xuemin (Sherman) Shen is a University Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the Royal Society of Canada, the Canadian Academy of Engineering, and the Engineering Institute of Canada. Professor Shen serves as Editor-in-Chief of multiple prestigious journals including the IEEE Internet of Things Journal and Springer Peer-to-Peer Networking and Applications. Dr. Shen received his Doctorate in Electrical Engineering from Rutgers University in 1990, following a Master of Applied Science from the same institution in 1987. His undergraduate degree is a Bachelor of Applied Science in Electrical Engineering from Dalian Marine University, China (1982). Professor Shen's research spans wireless communications and networking, with particular expertise in resource allocation, mobility management, wireless network security, and privacy preservation. His work extends to IoT applications, connected and automated vehicles, network digital twins, and satellite-terrestrial networks. His research has been applied to vehicular networks, wireless body area networks, remote e-healthcare systems, and smart grid technologies, demonstrating both theoretical depth and practical impact across multiple domains. His recent publications reveal strong trends in AI-assisted networking, security and privacy preservation for IoT applications, and energy management in vehicular and smart grid systems. The research shows an increasing focus on integrating AI techniques with traditional networking approaches, addressing critical challenges in security, privacy, and resource management for next-generation wireless systems. R.A. Fessenden Award (2019) from IEEE Canada James Evans Avant Garde Award (2018) from the IEEE Vehicular Technology Society Joseph LoCicero Award (2015) from the IEEE Communications Society Education Award (2017) from the IEEE Communications Society West Lake Friendship Award from Zhejiang Province (2023) President's Excellence in Research from University of Waterloo (2022) Canadian Award for Telecommunications Research (2021) Professor Shen has mentored over 100 graduate students and postdoctoral fellows throughout his career, with many now holding prominent academic positions at top universities worldwide. His supervision has been recognized with multiple awards including the Award of Excellence in Graduate Supervision (2006) from the University of Waterloo. He has served in numerous leadership roles including Past President of the IEEE Communications Society and has chaired major international conferences including IEEE Globecom 2024.
Sergey Gorbunov is an Associate Professor in the Department of Computer Science at the University of Waterloo . He holds a Ph.D. from MIT (2015), an M.Sc. and H.B.Sc. from the University of Toronto (2012 and 2011, respectively). His research focuses on Cryptography, Network Security, Blockchain Technology, Secure Protocols, and Privacy-Preserving Systems . He explores advanced cryptographic techniques for decentralized systems, privacy-enhancing technologies, and secure communication protocols. His work includes pioneering contributions to blockchain security (e.g., mitigating front-running attacks, enhancing transaction privacy) and foundational cryptographic tools like homomorphic encryption and multi-signature schemes. Recent publications emphasize resilient consensus mechanisms, anonymous payment channels, and efficient cryptographic primitives for distributed systems. Notable projects include Astrape (anonymous payment channels), Algorand Agreement (fast Byzantine consensus), and StealthDB (encrypted SQL databases). His research bridges theoretical cryptography with practical applications in secure computing and decentralized technologies.
Rongxing Lu is an Adjunct Professor at the Faculty of Computer Science, University of New Brunswick (UNB), Canada, since August 2016. Previously, he held positions at Nanyang Technological University (NTU), Singapore (2012–2016) and the University of Waterloo, Canada (PhD in 2012). His research focuses on applied cryptography, privacy enhancing technologies, and IoT-big data security. He has over 7,500 citations and received prestigious awards like the Governor General’s Gold Medal (2012) and the IEEE ComSoc Asia Pacific Outstanding Young Researcher Award (2013). He is an IEEE senior member and serves on editorial boards of journals like IEEE Network. **Education**: PhD in Electrical & Computer Engineering, University of Waterloo (2012), awarded Governor General’s Gold Medal Postdoctoral Fellow at University of Waterloo (2012–2013) **Research Interests**: Developing cryptographic protocols for IoT and big data systems Privacy-preserving techniques for distributed systems Secure communication in 5G/6G networks and vehicular systems **Awards and Recognition**: Recipient of multiple best paper awards in IEEE conferences 2016–2017 Excellence in Teaching Award at UNB **Editorial and Leadership Roles**: Symposium co-chair at IEEE Globecom’16 Secretary of IEEE ComSoc CIS-TC Organized special issues on fog computing security (Elsevier) and big data security (IEEE IoT Journal) **Key Contributions**: Pioneered privacy-aware data reporting schemes for vehicular networks Designed lightweight IoT authentication protocols Advanced secure machine learning frameworks with privacy guarantees
Anne Broadbent is a Full Professor at the University of Ottawa's Department of Mathematics and Statistics within the Faculty of Science. She holds a Tier 1 Canada Research Chair in Quantum Communications and Cryptography. Her academic journey includes an MSc and PhD from the University of Montreal. Her research focuses on quantum information processing and cryptography, with a particular emphasis on quantum communication protocols, encryption, and secure computation. She has contributed to groundbreaking work in quantum homomorphic encryption, uncloneable encryption, and quantum delegation protocols. Broadbent supervises graduate students including Daniel Lovsted, Sherry Wang, Pierre Botteron, Nagisa Hara, and Peter Yuen, often in collaboration with colleagues at institutions like Toulouse. Her research group explores discrete mathematics and analysis, alongside quantum information theory. Her recent articles highlight advancements in quantum proof systems, secure quantum communication architectures, and cryptographic primitives resistant to cloning. These contributions underscore her role in advancing theoretical and applied aspects of quantum information science.
Dr. Dima Alhadidi is an Associate Professor in the School of Computer Science at the University of Windsor. His research focuses on Cybersecurity, Data Privacy, Machine Learning, and their applications in Health Informatics, Cloud Computing, and Smart Grids. He holds a PhD in Computer Science and Software Engineering from Concordia University (2010). His research interests include secure federated learning frameworks, privacy-preserving techniques for genomic and health data, and adversarial machine learning defenses. Notable contributions include Trustformer (2025), secure aggregation methods in federated learning, and hybrid malware classification using deep learning. Recent work emphasizes mitigating membership inference attacks and developing privacy-preserving analytics for distributed systems. Dr. Alhadidi actively advises graduate students on topics like social network clustering (NICASN 2022) and federated learning security. No scientific awards are explicitly listed. His research spans theoretical frameworks (e.g., λ_AOP calculus) to applied systems in smart grids and healthcare informatics.
Ryan Henry is an Assistant Professor in the Department of Computer Science at the University of Calgary. His research focuses on applied cryptography, emphasizing the development of secure systems that prioritize user privacy. His work spans designing privacy-enhancing technologies, implementing cryptographic protocols, and analyzing number-theoretic attacks on cryptographic assumptions. He also explores theoretical aspects of cryptographic efficiency and practical deployment challenges. While specific educational background details are not provided in the text, his research contributions highlight expertise in cryptography, secure systems, and privacy-preserving technologies. His work has addressed topics such as Private Information Retrieval (PIR), secure messaging, and blockchain privacy. Key research interests include: Secure Multiparty Computation Privacy-Preserving Data Access Efficient Cryptographic Protocols Zero-Knowledge Proofs IoT Security Cryptocurrency and CBDC Design His recent publications emphasize advancements in distributed systems security, privacy in recommendation systems, and cryptographic efficiency. Notable contributions include the Grotto and Duoram frameworks for secure computation, and proposals for Canadian CBDC frameworks. Despite extensive research output, no scientific awards or grants are explicitly mentioned in the provided text. Collaborations and lab affiliations are not detailed, though his work suggests involvement in interdisciplinary projects on privacy and security technologies.
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.
Liang Xue is an Assistant Professor in the School of Information Technology at York University. She holds a PhD in Electrical and Computer Engineering from the University of Waterloo (2022) and completed a postdoctoral fellowship at the University of Guelph’s School of Computer Science (2022–2024). Her research focuses on applied cryptography, blockchain security, privacy-preserving AI, and cybersecurity in cloud and IoT systems. She has published in top-tier journals like IEEE Transactions on Dependable and Secure Computing, and conferences such as IEEE International Conference on Communications. Her work addresses challenges in data privacy, secure authentication, and regulatory compliance in decentralized systems. Recent projects include privacy-enhancing technologies for access control, blockchain-based data trading frameworks, and federated learning with privacy guarantees. She actively contributes to standards for cybersecurity in smart cities and next-generation wireless networks.
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.
Baochun Li is a Professor and Associate Chair, Research at the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto , with a cross-appointment to the Department of Computer Science. He holds the Bell Canada Endowed Chair in Computer Engineering since 2005. Education: B.Engr. from Tsinghua University (1995), M.S. and Ph.D. from University of Illinois at Urbana-Champaign (1997, 2000) His research interests span cloud computing , distributed systems (including federated learning), security and privacy , and networking , often integrating control theory , game theory , and network coding into practical systems. Recent work focuses on asynchronous federated learning , secure mechanisms for UAV teams , and transformer-based distributed inference . His 15 most recent publications emphasize federated learning , security in distributed systems , and transformer optimization , reflecting trends in large language models and edge computing . Awards and Recognitions: IEEE Fellow (2014) IEEE INFOCOM Achievement Award (2024) Fellow of the Canadian Academy of Engineering (2023) University of Toronto McLean Award (2009) He has contributed extensively to teaching , including launching the first Canadian university course on Rust programming in Fall 2024 and receiving a Departmental Teaching Award (2011). As a professional service leader , he has chaired major conferences like IEEE INFOCOM and IEEE ICDCS.
Aleksander Essex is an Associate Professor of Software Engineering in the Department of Electrical and Computer Engineering at Western University's Faculty of Engineering. He runs Whisper Lab, the Western Information Security and Privacy Research Laboratory, where he conducts research in cybersecurity, cryptography, and secure computation with the goal of making the world a safer, more private place. Dr. Essex's educational background includes: Ph.D. in Computer Science (2012) from the University of Waterloo M.A.Sc. in Electrical Engineering (2008) from the University of Ottawa B.E.Sc. in Computer Engineering (2004) from Western University His research focuses on both offensive and defensive aspects of information security and data privacy. In offensive research, he investigates cryptographic protocol and implementation vulnerabilities in TLS and related web security technologies. In defensive research, he specializes in secure multi-party computation with applications to trustworthy electronic voting and secure health informatics. His work aims to secure democratic institutions in the digital age through the development and standardization of trustworthy, publicly accountable election practices and technology. Dr. Essex's recent publications show a strong focus on election security, privacy-preserving technologies, and cryptographic protocols. His work spans multiple domains including election technology, health informatics, and general cybersecurity applications. Many of his recent papers examine verifiable online voting systems, genomic data privacy, and secure computation techniques. His scientific achievements include: Recipient of the Best Paper Award for "Online Voting in Ontario Municipal Elections: A Conflict of Legal Principles and Technology?" (2019) NSERC Alexander Graham Bell Canada Graduate Scholar during his Ph.D. studies Dr. Essex actively advises graduate students, with several current and completed Ph.D. and Master's students. He serves on multiple university committees including CyberSmart and the Working Group on Information Security (WIGIS). His research bridges theoretical cryptography with practical applications that address real-world security and privacy challenges.
