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Xichen Zhang is an Assistant Professor at the Department of Finance, Information Systems and Management Science within the Sobey School of Business at Saint Mary's University. His research focuses on cybersecurity, privacy-preserving techniques, federated learning, fake news detection, and machine learning applications in edge-cloud collaboration and mobile crowdsensing. He holds a Ph.D. in a relevant field and has contributed to interdisciplinary projects involving blockchain-based voting systems and IoT security solutions. His work emphasizes practical solutions to modern challenges in data privacy, misinformation detection, and distributed computing. Notable contributions include the development of the TruthSeeker dataset for real/fake content analysis and frameworks like SCORE for scalable contact tracing. His articles explore topics from adversarial machine learning defenses to temporal user credibility models in social networks. Dr. Zhang's research integrates technical innovations with societal impact areas like healthcare informatics and election security. He collaborates across disciplines to address privacy challenges in both academic and industrial contexts. Current projects investigate federated reinforcement learning for IoT systems and multimodal fake news detection using image-text consistency analysis.

• Cybersecurity
• Machine Learning
• Privacy-Preserving Techniques
• +7 more

Dr. Shikharesh Majumdar is the Chancellor’s Professor and Director of the Real-Time and Distributed Systems Research Centre at Carleton University's Department of Systems and Computer Engineering. He holds a Ph.D. from the University of Saskatchewan. His research focuses on parallel and distributed systems, performance modeling, cloud computing, and IoT. He teaches undergraduate and graduate courses in operating systems and distributed systems engineering. His work includes pioneering contributions to resource management on clouds and grids, energy-efficient systems, and middleware for distributed computing. He has supervised numerous graduate and undergraduate students, many of whom have received awards such as the University Senate Medal and NSERC scholarships. Dr. Majumdar has authored over 100 peer-reviewed publications and delivered keynotes at major conferences like IEEE Cloud and ACM ICDCN. His research addresses challenges in big data analytics, sensor-based systems, and edge computing. He actively contributes to industry through collaborations with organizations like TELUS and Nortel. His current projects include optimizing resource allocation for MapReduce jobs, enhancing IoT systems, and developing frameworks for complex event processing. The Real-Time and Distributed Systems Research Centre under his leadership explores cutting-edge solutions for distributed computing challenges.

• Parallel and Distributed Systems
• Performance Modelling
• Cloud Computing
• +5 more

Xavier Fernando is a Professor and Director of the TMU Intelligent Communication and Computing Laboratory at Toronto Metropolitan University's Department of Electrical and Computer Engineering. His academic career includes leadership roles such as Chair of IEEE Canada Humanitarian Initiatives (2017-18), General Chair of IEEE International Humanitarian Technology Conference (2017), and Board Member of Ryerson University (2011-12). He has authored over 200 research papers, three books, and holds multiple patents, with research focused on optical/wireless communication systems, cognitive radio, and vehicular visible light communications. Research interests span signal processing for underground communications, MAC layer protocols, and energy-efficient networks. Notable awards include IEEE Communications Society Distinguished Lecturer (2012-2013), Engineering Excellence Award (2016), and finalist for Top 25 Canadian Immigrants (2012). His lab, established since 2008, has secured $3.185 million in funding. Contributions include pioneering work in RF energy harvesting, smart grid technologies, and underground communication systems for mining safety. Professional service includes roles as IEEE Toronto Section Chair, member of IEEE Education Board, and evaluator for ABET. Key publications address heterogeneous networks, cognitive radio performance, and VLC vehicular applications. Students and alumni are tracked via LinkedIn groups, with notable projects winning IEEE MTT prizes and engineering accolades.

• Optical Communication
• Wireless Communication Systems
• Signal Processing
• +4 more

**Ahmed Hassan** is a **Professor** and **Canada Research Chair (Tier 2) in Software Analytics** at the **School of Computing**, **Queen's University**, affiliated with the **Faculty of Arts and Science**. He holds the **NSERC/RIM Industrial Research Chair in Software Engineering for Ultra Large Scale Systems**. His research focuses on software systems, data analytics, and mining software repositories (MSR), leading the **Software Analysis and Intelligence Lab (SAIL)**. **Education**: PhD (2005), MMath (2001), BMath (1999) in Computer Science from the University of Waterloo, Canada. **Research Interests**: Software evolution, performance engineering, distributed systems debugging, cybersecurity, and AI-driven software solutions. SAIL explores tools for maintaining large-scale software systems, improving developer productivity, and integrating AI into software workflows. **Awards & Recognition**: ACM and IEEE Fellowships, patents in multiple jurisdictions, and leadership roles in MSR and ICSE conferences. Industrial experience includes RIM/BlackBerry, IBM Research, and Nortel Networks. **Current Projects**: Focus on foundation model-powered software (FMware), AIOps, and ethical AI applications. Teaching courses like CISC322: Software Architecture.

• Software Engineering
• Data Analytics
• Mining Software Repositories
• +5 more

Ivan Beschastnikh is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Faculty of Science. He leads research in distributed systems, software engineering, and formal methods, with a focus on privacy-preserving technologies, blockchain systems, and machine learning. His work bridges theoretical foundations and practical system implementations, emphasizing empirical validation and real-world deployment. Research Interests: His primary areas include distributed systems (e.g., consensus algorithms, transaction processing), formal methods for system correctness (e.g., PGo compiler for verified implementations), and privacy in federated learning and blockchain. He also explores interdisciplinary topics like AI ethics, human-computer interaction for developers, and system security. Key Projects: Includes PGo (formal specification to Go compiler), Biscotti (decentralized federated learning), Erlay (Bitcoin transaction relay optimization), and Teleoscope (text corpus analysis tool). His work has practical impact in blockchain scalability, secure multi-party ML, and distributed system validation. Awards: Recognized with the ASPLOS Distinguished Artifact Award, UBC Faculty Teaching Award, and ESEM Best Paper Award. His contributions span academic excellence, pedagogy, and collaborative research. Lab Affiliations: Active in the Systopia Lab and Software Practices Lab (SPL) , and collaborates with UBC’s Data Science Institute and Blockchain@UBC. He emphasizes interdisciplinary research, mentoring students in both theoretical and applied systems work.

• Distributed Systems
• Software Engineering
• Cloud Computing
• +5 more

Pengfei Li is an Assistant Professor in the School of Information at the Rochester Institute of Technology (RIT), where he leads research at the intersection of machine learning, sustainability, and social equity. Previously, he completed his Ph.D. in Computer Science at the University of California, Riverside under Prof. Shaolei Ren, with additional collaborations at Caltech with Adam Wierman and an internship at Nokia Bell Labs. His educational background includes an M.S.E. in Robotics from Johns Hopkins University and a B.E. in Electrical Engineering from Zhejiang University. Dr. Li's research focuses on three interconnected pillars: developing trustworthy online algorithms with strict robustness guarantees, creating sustainable AI systems that minimize environmental impact, and addressing environmental and social inequities through algorithmic solutions. Analysis of his recent publications reveals a strong emphasis on the environmental consequences of AI systems, particularly water consumption ('Making AI Less 'Thirsty'') and geographical distribution of environmental burdens ('Towards Environmentally Equitable AI'). His work bridges theoretical computer science with practical sustainability challenges, often incorporating learning-augmented approaches to traditional online optimization problems. Scientific Recognition: Dissertation Completion Fellowship Award (DCFA) from the Graduate Program in Computer Science (February 2025) 'Making AI Less 'Thirsty'' in Communications of the ACM has received 15 citations and over 17,000 downloads Organizer of the workshop on learning-augmented algorithms at SIGMETRICS 2025 Dr. Li actively seeks to build a research group focused on societal fairness, reliable generative AI, and decision-focused learning. His work has established important connections between theoretical computer science and critical societal challenges, particularly around AI's environmental footprint and equitable resource distribution. Current research directions include developing algorithmic solutions for environmental and social fairness, with applications in water infrastructure, energy systems, and equitable AI deployment.

• Online optimization
• Trustworthy machine learning
• Sustainable AI
• +7 more

Felipe Gohring de Magalhaes is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he has been working since July 2018 and assumed his current position in October 2024. He holds a dual doctorate from PUC-RS (Brazil) and Polytechnique Montréal (2016), with degrees in both computer science and computer engineering. His research spans embedded system architectures, real-time systems, avionics, and cybersecurity for emerging technologies. He is affiliated with the Microelectronics and Microsystems Research Group and the Multidisciplinary Institute for Cybersecurity and Cyber Resilience, reflecting his focus on integrated circuits, microelectronics, and system security. Professor Gohring de Magalhaes has published over 40 articles in international journals and conferences, with recent work focusing on photonic integrated circuits security, optical neural networks, and post-quantum cryptography for avionic systems. His publication trend shows consistent output with increasing focus on security aspects of emerging computing technologies. He has supervised at least one PhD student to completion and teaches courses including Introduction to Programming and Operating System Kernel. His research interests align with NSERC topics in integrated circuits, microelectronics, computer systems organization, and VLSI systems.

• Integrated circuits
• Microelectronics
• Computer systems organization
• +7 more