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Qizhen Zhang is a Professor in the Department of Computer Science at the University of Toronto's Faculty of Arts and Science. Specializing in hyperscale data processing systems, Zhang leads research at the intersection of cloud computing, distributed systems, and data center networking. Recent work focuses on network-centric designs for efficient large-scale data processing, including pioneering contributions to disaggregated data center architectures. Research interests center on hyperscale data processing , network-aware system design , and disaggregated infrastructure . Current projects investigate DPU-accelerated systems (dpBento, DPDPU), memory disaggregation (Cowbird, Redy), and blockchain scalability (FlexChain). Zhang's approach systematically integrates network characteristics into distributed system optimization, addressing challenges in trillion-item workloads through novel shuffle layers (TeShu) and compute pushdown mechanisms (TELEPORT). Zhang advises multiple graduate students working on satellite networking (SaTE), federated learning, and DPU-optimized storage (DDS). Professional service includes program committees for SIGMOD, VLDB, NSDI, and EuroSys (2023-2026), plus journal reviews for ACM TODS and IEEE/ACM Transactions on Networking. Industrial collaborations with Microsoft Research have yielded production-oriented systems like Redy and CompuCache. Key contributions include MimicNet for scalable network simulation (SIGCOMM 2021), GraphRex for network-aware graph processing (SIGMOD 2019), and foundational work on disaggregated data centers (CIDR 2020, VLDB 2020). Teaching responsibilities encompass graduate courses CSC2235 (Cloud-native Data Management) and undergraduate CSCC43 (Databases) at the University of Toronto.

• Hyperscale Data Processing
• Cloud Computing
• Network-Centric System Design
• +4 more

Colin D. Rennie is a Professor and Chair in the Department of Civil Engineering at the University of Ottawa, Faculty of Engineering. He holds a Ph.D. and MASc from the University of British Columbia and a B.Sc. from the University of Guelph, and is a licensed Professional Engineer (P.Eng.). He is an active researcher, educator, and leader in river and environmental hydraulics. His research focuses on river morphodynamics, sediment transport, turbulence, and aquatic habitat, utilizing advanced techniques including acoustic Doppler current profilers (ADCPs), laboratory physical models, and 3D numerical modeling. His work addresses critical issues such as river stability, flood dynamics, hydroelectric development, and ecosystem protection. The recent trends in his publications reflect a strong emphasis on high-resolution numerical modeling of local scour, sediment transport using acoustic methods, and the morphodynamic impacts of river confluences and floods. His work integrates field data with computational fluid dynamics (CFD), particularly using OpenFOAM, to understand complex flow-sediment interactions. He is an Associate Editor of the Journal of Hydraulic Engineering (ASCE) and has served on editorial boards of Journal of Geophysical Research – Earth Surface (AGU). He is a member of professional organizations including ASCE, IAHR, CSCE, and AGU, and has held leadership roles such as Secretary of the River Hydraulics Division at IAHR. Professor Rennie currently supervises multiple graduate students, including Yi Man, Xiatong Cai, Qingcheng Yu, and others, supporting research in sediment dynamics and hydraulic modeling. He has secured research funding for projects related to river flooding, ice processes, and habitat restoration. His teaching includes CVG3116 (Hydraulics), CVG4001 (Introduction to Civil Engineering Design), CVG4907 (Design Project), CVG5162 (River Hydraulics), and CVG5160 (Sediment Transport). His research has been conducted globally, with collaborations in New Zealand, Switzerland, Spain, and China, where he has led field campaigns and trained researchers in spatial mapping of water and sediment fluxes. He has applied his expertise to major flood events, including the 2013 Alberta flood and the 2017–2019 Ottawa River floods.

• River Engineering
• Environmental Hydraulics
• Sediment Transport
• +12 more

Dr. Sihang Liu is an Assistant Professor in the School of Computer Science at the University of Waterloo. Prior to this role, he served as a visiting faculty member at SystemsResearch@Google. He holds a PhD from the University of Virginia, where his research was supported by the Google Fellowship Award. His academic career has been marked by contributions to computer architecture, systems, and persistent memory technologies. Dr. Liu's research interests span computer architecture, systems, and cybersecurity, with a focus on persistent memory systems, energy-efficient computing, and data center optimization. His work bridges hardware-software co-design and explores challenges in scalable computing, fault tolerance, and sustainable AI systems. His recent publications highlight advancements in adaptive memory tiering (HybridTier), carbon intensity forecasting (EnsembleCI), and securing persistent memory (Side-Channel Attacks on Optane). These contributions underscore his commitment to addressing critical issues in modern computing systems' performance, security, and environmental impact. Awards: Google Fellowship Award (PhD), NVMW Memorable Paper Award Finalist (2019), 2019 MICRO Top Picks Honorable Mention Professional Service: Program committees for ISCA, MICRO, ASPLOS; Artifact evaluation roles in leading conferences As an advisor, Dr. Liu mentors a diverse group of students, including current PhD candidates Henry Tian and Desen Sun, and numerous undergraduates. His lab focuses on innovation in sustainable computing and resilient systems design.

• Computer Architecture
• Computer Systems
• Persistent Memory Systems
• +3 more