Fast Machine Learning for Science Workshop 2023

Session

Invited Talks

25 Sept 2023, 09:30

Blackett Laboratory, Lecture Theatre 1 (Imperial College London)

65. Workshop Opening

Alex Tapper (Imperial College London), Sioni Paris Summers (CERN)

25/09/2023, 09:30

66. Fast Machine Learning at the Large Hadron Collider experiments

Thea Aarrestad (ETH Zurich (CH))

25/09/2023, 09:45

Invited Talks

67. Fast Machine Learning at European XFEL

Steve Aplin (EuXFEL)

25/09/2023, 11:00

Invited Talks

75. Bridging AI and biomedicine: Towards AI-driven scientific discoveries

Maria Brbic

25/09/2023, 11:45

Invited Talks

Biomedical data poses multiple hard challenges that break conventional machine learning assumptions. In this talk, I will highlight the need to transcend our prevalent machine learning paradigm and methods to enable them to become the driving force of new scientific discoveries. I will present machine learning methods that have the ability to bridge heterogeneity of individual biological...

38. Fast Machine Learning for accelerator control

Karin Rathsman (European Spallation Source)

26/09/2023, 09:00

Invited Talks

Standard Talk

The European Spallation Source (ESS) is multi-disciplinary research facility based on neutron scattering under construction in Lund. The facility includes a superconducting linear proton accelerator, a rotating tungsten target wheel where neutrons are spalled off by the high energy protons and a suit of instruments for neutron scattering experiments.

ESS is a user facility designed and...

68. Fast Machine Learning for laser wakefield acceleration

Matt Streeter

26/09/2023, 09:45

Invited Talks

69. Fast ML for fusion simulation, optimization, and control

Jonathan Citrin

26/09/2023, 11:00

Invited Talks

Magnetic confinement fusion research is at a threshold where the next generation of experiments are designed to deliver burning fusion plasmas with net energy gain for the first time. ML holds great promise in reducing the costs and risks of fusion reactor development, by enabling efficient workflows for scenario optimization, reactor design, and controller design. This talk reviews various...

70. Machine Learning in Exoplanet Characterisation

Ingo Waldmann (UCL), Kai Hou Yip

26/09/2023, 11:45

Invited Talks

The exploration of extrasolar planets, which are planets orbiting stars other than our own, holds great potential for unravelling long-standing mysteries surrounding planet formation, habitability, and the emergence of life in our galaxy. By studying the atmospheres of these exoplanets, we gain valuable insights into their climates, chemical compositions, formation processes, and past...

71. Co-Design for Efficient & Adaptive ML

Yaman Umuroglu

27/09/2023, 09:00

Invited Talks

Beyond the well-known highlights in computer vision and natural language, AI is steadily expanding into new application domains. This Pervasive AI trend requires supporting diverse and fast-moving application requirements, ranging from specialized I/O to fault tolerance and limited resources, all the while retaining high performance and low latency. Adaptive compute architectures such as AMD...

72. In network ML: Inference at the Speed of Data

Noa Zilberman

27/09/2023, 09:45

Invited Talks

How fast should your machine learning be? ideally, as fast as you can stream data to it.
In this presentation I will discuss the role of computing infrastructure in machine learning, and argue that to face the growing volume of data and support latency constraints, the best place for inference is within the network. I will introduce in-network machine learning, the offloading of machine...

73. Need for Speed: How to harness the power of Large Language Models

Tobias Becker (Maxeler Technologies)

27/09/2023, 11:00

Invited Talks

Large Language Models (LLMs) will completely transform the way we interact with computers, but in order to be successful they need to be fast and highly responsive. This represents a significant challenge due to the extremely high computational requirements of running LLMs. In this talk, we look at the technology behind LLMs, its challenges, and why Groq's AI accelerator chip holds a...

74. Deep Learning for Fast MR Imaging and Analysis

Chen Qin

27/09/2023, 11:45

Invited Talks

Deep learning has shown great potential in improving and accelerating the entire medical imaging workflow, from image acquisition to interpretation. This talk will focus on the recent advances of deep learning in medical imaging, from the reconstruction of accelerated signals to automatic quantification of clinically useful information. The talk will describe how model-based deep learning can...

64. Registration