Using AI in experimental physics

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SUMMARY

The forum discussion centers around a presentation from a graduate school regarding the application of AI in experimental physics, specifically in analyzing high-energy scattering data. Participants expressed interest in the outcomes of the talk and sought summaries or recordings due to missed attendance. The discussion highlights the growing intersection of artificial intelligence and fundamental physics research, emphasizing the need for accessible resources from such presentations.

PREREQUISITES
  • Understanding of high-energy physics concepts
  • Familiarity with AI applications in scientific research
  • Knowledge of data analysis techniques
  • Experience with Zoom for virtual presentations
NEXT STEPS
  • Research AI methodologies in high-energy physics
  • Explore data analysis tools used in experimental physics
  • Investigate recent advancements in AI for scientific data interpretation
  • Look for recordings of similar academic presentations on AI applications
USEFUL FOR

Researchers in experimental physics, data scientists interested in AI applications, and graduate students seeking insights into the integration of technology in scientific analysis.

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Here's an upcoming presentation from the grad school I attended about applying AI to fundamental physics, namely, analyzing high-energy scattering data:
Duarte talk.webp

(https://universitydevelopment.cmail20.com/t/d-e-gamhk-hliyjihltk-u/)
 
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How was the talk?

How did they do this and what did they learn?
 
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jedishrfu said:
How was the talk?
Alas, I missed it due to a scheduling conflict. Did anyone else hop on the Zoom meeting?
 
Bummer.

Did they post any summaries of the talks?

Or a recording of the talk?
 
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