About Marco Canini Marco Canini Professor, Computer Science machine learning artificial intelligence distributed systems large-scale computing cloud computing programmable networks Professor Canini’s research seeks to improve networked-system design, implementation and operation concerning vital properties such as reliability, performance, security and energy efficiency. Events Presented Events Mar 1 - Mar 7, 2026 From Prompts to Production: The Systems Agenda for Agentic AI Marco Canini, Professor, Computer Science Mar 2, 12:00 - 13:00 B9 L2 R2325 AI observability reproducibility Computer Information Systems In this talk, I will discuss our recent work on benchmarking, evaluation, and deployment of multi-agent LLM systems, and use it to outline a broader research agenda for agentic AI as a systems discipline - where progress depends not only on better models, but on principled infrastructure for observability, reproducibility, safe experimentation, and scalable execution. Nov 24 - Nov 30, 2024 Why ML Works: It’s Not Magic, It’s Networked Systems Wizardry! Marco Canini, Professor, Computer Science Nov 27, 10:00 - 11:30 B9, L2, R2322 machine learning computing system Today’s machine learning (ML) solutions are achieving extraordinary success across diverse fields, thanks to their ability to learn complex models and deliver impressively accurate results. While the availability of big data is often credited as a driving force, the unsung hero behind ML’s rise is the rapid innovation in computing and software systems that make these breakthroughs possible and accessible. Apr 16 - Apr 22, 2023 Serverless Computing: With Great Freedom Comes Great Opportunity! Marco Canini, Professor, Computer Science Apr 17, 12:00 - 13:00 B9 L2 H2 H2 serverless computing This talk introduces serverless computing, a programming model that has flourished in the last few years, mainly because it allows developers to concentrate on the application logic and not worry about scalability and resource management. Current serverless offerings give users limited flexibility for configuring the resources allocated to their function invocations. We take a principled approach to the problem of resource allocation for serverless functions, analyzing the effects of automating this choice in a way that leads to the best combination of performance and cost. Aug 28 - Sep 3, 2022 Which came first: the paper or the peer-review? Marco Canini, Professor, Computer Science Aug 29, 12:00 - 13:00 B9 L2 R2322 H1 This talk presents some perspectives on doing research in computer science and publishing through the peer review process.
From Prompts to Production: The Systems Agenda for Agentic AI Marco Canini, Professor, Computer Science Mar 2, 12:00 - 13:00 B9 L2 R2325 AI observability reproducibility Computer Information Systems In this talk, I will discuss our recent work on benchmarking, evaluation, and deployment of multi-agent LLM systems, and use it to outline a broader research agenda for agentic AI as a systems discipline - where progress depends not only on better models, but on principled infrastructure for observability, reproducibility, safe experimentation, and scalable execution.
Why ML Works: It’s Not Magic, It’s Networked Systems Wizardry! Marco Canini, Professor, Computer Science Nov 27, 10:00 - 11:30 B9, L2, R2322 machine learning computing system Today’s machine learning (ML) solutions are achieving extraordinary success across diverse fields, thanks to their ability to learn complex models and deliver impressively accurate results. While the availability of big data is often credited as a driving force, the unsung hero behind ML’s rise is the rapid innovation in computing and software systems that make these breakthroughs possible and accessible.
Serverless Computing: With Great Freedom Comes Great Opportunity! Marco Canini, Professor, Computer Science Apr 17, 12:00 - 13:00 B9 L2 H2 H2 serverless computing This talk introduces serverless computing, a programming model that has flourished in the last few years, mainly because it allows developers to concentrate on the application logic and not worry about scalability and resource management. Current serverless offerings give users limited flexibility for configuring the resources allocated to their function invocations. We take a principled approach to the problem of resource allocation for serverless functions, analyzing the effects of automating this choice in a way that leads to the best combination of performance and cost.
Which came first: the paper or the peer-review? Marco Canini, Professor, Computer Science Aug 29, 12:00 - 13:00 B9 L2 R2322 H1 This talk presents some perspectives on doing research in computer science and publishing through the peer review process.
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