10/16 15:00 Dr. Yuan-Tang Chou (University of Washington) AI-Driven Trigger Innovations for Discoveries at the LHC (P512, 5F, 3rd General Building, Nat'l Tsing Hua Univ.)
******** CTCD/NTHU HEP Seminar ********
Speaker ：Dr. Yuan-Tang Chou (University of Washington)
Title ：AI-Driven Trigger Innovations for Discoveries at the LHC
Time ： 15:00-16:00, Thursday, 2025/10/16
+++++++++++
Place ： P512, 5F, 3rd General Building, Nat'l Tsing Hua Univ.
+++++++++++++++++++++++++++++++
Host ： Prof. Chong-Sun Chu (NTHU)
Abstract:
After a decade of null results from the Large Hadron Collider (LHC), the
particle physics community faces a pressing challenge to rethink our
strategies. These null results underscore the need for innovative
approaches, as all beyond-SM searches and precise SM measurements remain
vital inputs for shaping the next generation of experiments. How can we
harness new tools like artificial intelligence (AI) and machine learning
(ML) to explore beyond the Standard Model (SM)?
In this seminar, I will outline three frontiers to address this
challenge to expand the future discovery potential of the LHC. First, I
will discuss how a new data-taking strategy at the trigger system,
combined with innovative ML algorithms, could unlock unexplored regions
of LHC data for physically significant events. Second, I will discuss
one of the key challenges in charged particle reconstruction as we move
toward the High-Luminosity LHC and demonstrate how modern ML algorithms
offer a promising solution to achieve our physics goals and overcome
computational challenges. Lastly, I will share our recent studies on
Foundation Models, which could provide a potential paradigm shift in how
we leverage vast datasets from the LHC and perform data analysis in
particle physics and beyond.
Speaker ：Dr. Yuan-Tang Chou (University of Washington)
Title ：AI-Driven Trigger Innovations for Discoveries at the LHC
Time ： 15:00-16:00, Thursday, 2025/10/16
+++++++++++
Place ： P512, 5F, 3rd General Building, Nat'l Tsing Hua Univ.
+++++++++++++++++++++++++++++++
Host ： Prof. Chong-Sun Chu (NTHU)
Abstract:
After a decade of null results from the Large Hadron Collider (LHC), the
particle physics community faces a pressing challenge to rethink our
strategies. These null results underscore the need for innovative
approaches, as all beyond-SM searches and precise SM measurements remain
vital inputs for shaping the next generation of experiments. How can we
harness new tools like artificial intelligence (AI) and machine learning
(ML) to explore beyond the Standard Model (SM)?
In this seminar, I will outline three frontiers to address this
challenge to expand the future discovery potential of the LHC. First, I
will discuss how a new data-taking strategy at the trigger system,
combined with innovative ML algorithms, could unlock unexplored regions
of LHC data for physically significant events. Second, I will discuss
one of the key challenges in charged particle reconstruction as we move
toward the High-Luminosity LHC and demonstrate how modern ML algorithms
offer a promising solution to achieve our physics goals and overcome
computational challenges. Lastly, I will share our recent studies on
Foundation Models, which could provide a potential paradigm shift in how
we leverage vast datasets from the LHC and perform data analysis in
particle physics and beyond.