GRADnet Machine learning and AI workshop

chaired by A Bevan (Queen Mary), Marcella Bona (QMUL), A Pourtsidou (Queen Mary), U Blumenschein (Queen Mary)
from to (Europe/London)
at Arts II ( LT )
Queen Mary University of London, Mile End Campus
Description
This is a 2-day workshop that consists of a series of presentations and tutorials, to ensure delegates get the chance to learn about modern methods, and have the opportunity to get some hands on experience.   This workshop will be of interests to PhD students keen to learn about, and start using modern data science and AI in the context of physics and astronomy.
Go to day
  • Wednesday, 15 January 2020
    • 10:30 - 11:00 Break
    • 11:00 - 12:30 Introduction and Orientation Session
      This session will lay down the housekeeping rules and provide some brief data wrangling issues.
      • 11:00 Welcome and housekeeping 10'
        Speaker: Dr. A Bevan (Queen Mary)
        Material: Slides pdf file
      • 11:10 Why is data wrangling important? 20'
        Speaker: Dr. Nick Barlow (Alan Turing Institute)
        Material: Slides pdf file
      • 11:30 Data wrangling exercises 1h0'
        Speaker: Dr. Nick Barlow (Alan Turing Institute)
        Material: Slides linkdown arrow
    • 12:30 - 13:30 Lunch
    • 13:30 - 15:00 Tutorial
      • 13:30 Introduction to Python and TensorFlow (linear regression and neural network examples) 1h30'
        Speakers: Dr. A Bevan (Queen Mary), Dr. Marcella Bona (QMUL), JMM Davies (Queen Mary), TP Charman (Queen Mary)
        Material: Slides link pdf filedown arrow
    • 15:00 - 15:30 Break
    • 15:30 - 17:00 Plenary
      • 15:30 Reinforcement learning 45'
        Speaker: Dr. A Pourtsidou (Queen Mary)
        Material: Slides pdf file
      • 16:15 Sci ML team @ RAL 45'
        Speaker: Dr. Jeyan Thiyagalingam (STFC)
        Material: Slides pdf file
    • 18:00 - 20:00 Dinner
  • Thursday, 16 January 2020
    • 09:00 - 10:30 Tutorial
      • 09:00 Linear regression, neural network model building, and decision trees (tutorial using SciKit Learn and Keras) 1h30'
        Speakers: Dr. A Bevan (Queen Mary), JMM Davies (Queen Mary), Dr. Marcella Bona (QMUL), TP Charman (Queen Mary)
        Material: Slides link pdf filedown arrow
    • 10:30 - 11:00 Break
    • 11:00 - 12:30 Plenary
      • 11:00 NNPDF - using neural networks to compute parton density functions 45'
        Speaker: Dr. Maria Ubiali (DAMPT)
        Material: Slides pdf file
      • 11:45 ABBA - Automatically Building Better Algorithms. 45'
        Speaker: Dr. John Woodward (QMUL)
        Material: Slides powerpoint file pdf file
    • 12:30 - 13:30 Lunch
    • 13:30 - 15:00 Tutorial
      • 13:30 SQL tutorial 45'
        Speaker: Dr. A Pourtsidou (Queen Mary)
        Material: Slides link pdf file
      • 14:15 Data in finance 45'
        Speaker: Dr. Thomas Babbedge (Gresham Investment Management LLC)
    • 15:00 - 15:30 Break
    • 15:30 - 17:15 Plenary
      • 15:30 Challenges of Machine Learning in Physics 45'
        Speaker: Dr. A Bevan (Queen Mary)
        Material: Slides pdf file
      • 16:15 Machine Learning applied to neutrino physics 45'
        Speaker: Dr. Sophie King (Kings College London)
        Material: Slides pdf file