Talk title: What’s there to monitor? Performance perceived across communities
Bettina Kemme is a Professor of the School of Computer Science at McGill University where she leads the Distributed Information Systems lab. Her general research interests lie in large-scale data management and distributed computing. Her recent projects involved compiler-based approaches for advanced data analytics, platform support for machine learning on structured data as well as the use of machine learning to support distributed application monitoring. Bettina holds a PhD degree in Computer Science from ETH Zurich, and an undergraduate degree from the Friedrich-Alexander-Universität Erlangen, Germany. She has published well over 100 publications in major journals and conferences in the areas of database systems and distributed systems. In 2010, she won the VLDB 10-year test-of-time award. She has served on the editorial board of the VLDB Journal and Information Systems and has been on the program committee or area chair of major database and distributed systems conferences such as SIGMOD, VLDB, ICDE, ICDCS, Middleware, SRDS and many more. She was the PC Co-Chair of Middleware 2017, DEBS 2023 and EDBT 2025, and is a senior IEEE Member. She was also General Chair of two conferences and co-created the Workshop series on Data Systems meet Data Science (DSDS). She was the Director of the School of Computer Science at McGill University from 2016-2021 and is currently serving as Vice-President of the CS-CAN/INFO-CAN Canadian Association of Computer Science.
Talk title: How the cloud made performance on board agenda!
Manzoor, a cloud veteran with over 25 years of experience, co-founded Capacitas and serves as its Chief Innovation Officer. He has a proven track record of delivering millions in annual cloud spend reductions and optimising the performance of complex systems and has helped companies achieve their financial goals through strategic cloud management.
Manzoor recognised the transformative power of cloud computing early on, understanding how it strengthens the link between performance and cost. This realisation led him to create Capacitas' unique methodology, which has empowered numerous clients, including easyJet, Skype, JAGGAER, Ancestry, Cegid, and BMC Software, to achieve significant cost reductions and performance improvements.
Manzoor is a trusted advisor and thought leader in the cloud computing space, passionate about helping businesses leverage the cloud to achieve their full potential.
Talk title: What does performance mean for large language models?
Jane Hillston is Professor of Quantitative Modelling in the School of Informatics and Dean of Research Culture in the College of Science and Engineering at the University of Edinburgh. Her research is concerned with formal approaches to modelling dynamic behaviour of discrete event systems. This includes everything from cloud computing, to biological processes, to transport systems in smart cities. Her research has been recognised by a number of awards including the RSE Lord Kelvin Medal, the BCS Lovelace Award and Fellowship of the Royal Society. She was Head of School in School of Informatics from 2018—2023 and Deputy Vice Principal Research 2020—2022. Professor Hillston was awarded an MBE in the Kings Birthday Honours List in 2023 in recognition of her contribution to computer science and women in science.
Talk title: Optimizing Edge AI: Performance Engineering in Resource-Constrained Environments
Recent years have witnessed the growth of Edge AI, a transformative paradigm that integrates neural networks with edge computing, bringing computational intelligence closer to end users. However, this innovation is not without its challenges, especially in environments with limited computing, network, and memory constraints, where resource-hungry AI models often need to be partitioned for distributed execution. This issue becomes even more acute in scenarios where post-deployment updates are infeasible or costly, posing a need to accurately reason about the interplay between resource constraints and Quality-of-Service (QoS) in Edge AI systems, so as to optimally design and operate them.
In this keynote talk, I will focus on these challenges, discussing QoS management and deployment problems arising in Edge AI systems. I will review mechanisms such as early exits and DNN partitioning that are distinctive of this problem space, explaining how they could be accounted for and leveraged in system performance and reliability tuning. I will then illustrate how design decisions and the definition of novel runtime control algorithms can be guided by approaches based on both traditional analytical models and emerging data-driven methods based on machine learning models.
Giuliano Casale is a Reader in the Department of Computing at Imperial College London. He does research in Quality-of-Service engineering and cloud computing, topics on which he has published more than 150 refereed papers. He has served as program co-chair for several conferences in the area of performance and reliability engineering, such as ACM SIGMETRICS/Performance and IEEE/IFIP DSN. His research work has received best paper awards at ACM SIGMETRICS, IEEE/IFIP DSN and IEEE INFOCOM. During 2019-2023, he has served as ACM SIGMETRICS chair. He serves on the editorial board of ACM TOMPECS and as the Editor-in-Chief of Elsevier Performance Evaluation.