AI in Science
Description
People from around campus talk about how they use AI. Two 20 minute talks. The audience is mostly physics, math, CS.  This week features Manuel Franco Sevilla (Physics) and Maria Cameron (Math)
Speaker:Â Manuel Franco Sevilla
From particle detection to AI Agents: the evolution of ML and AI at LHCb
With the prospect of an unprecedented influx of data from the future Large Hadron Collider (LHC), in 1989 Tim Berners-Lee proposed the World Wide Web at CERN to help researchers share and navigate scientific information. Today, the enormous volumes of data produced by the LHC demand increasingly sophisticated tools to turn collisions into discoveries.
This talk explores how the LHCb experiment uses machine learning and AI to identify particles, select interesting events, and simulate detector responses. It then looks at emerging applications of large language models and AI agents to help particle physicists access knowledge, develop software, and support experiment operations, highlighting both their potential and the challenges of using them reliably in scientific research.
Speaker:Â Maria Cameron
Reshaping math courses in the age of AI
The advancement and availability of AI have had a major impact on mathematics research and education. I will share my thoughts on how we can reshape upper-division undergraduate and graduate applied math classes to take advantage of AI. I am thinking of courses that involve lecture and practice lab classes, a project-oriented agenda, mathematical, numerical, and applied components, and oral pass/not pass assessments and written exams.Â
Speaker:Â Manuel Franco Sevilla
From particle detection to AI Agents: the evolution of ML and AI at LHCb
With the prospect of an unprecedented influx of data from the future Large Hadron Collider (LHC), in 1989 Tim Berners-Lee proposed the World Wide Web at CERN to help researchers share and navigate scientific information. Today, the enormous volumes of data produced by the LHC demand increasingly sophisticated tools to turn collisions into discoveries.
This talk explores how the LHCb experiment uses machine learning and AI to identify particles, select interesting events, and simulate detector responses. It then looks at emerging applications of large language models and AI agents to help particle physicists access knowledge, develop software, and support experiment operations, highlighting both their potential and the challenges of using them reliably in scientific research.
Speaker:Â Maria Cameron
Reshaping math courses in the age of AI
The advancement and availability of AI have had a major impact on mathematics research and education. I will share my thoughts on how we can reshape upper-division undergraduate and graduate applied math classes to take advantage of AI. I am thinking of courses that involve lecture and practice lab classes, a project-oriented agenda, mathematical, numerical, and applied components, and oral pass/not pass assessments and written exams.Â