Fast Machine Learning for Science Conference 2024

15 Oct 2024, 08:00 → 18 Oct 2024, 21:00 America/Indiana/Indianapolis

Miaoyuan Liu (Purdue University (US))

We are pleased to announce a four-day event Fast Machine Learning for Science, which will be hosted by Purdue University from October 15-18, 2024. The first three days will be workshop-style with invited and contributed talks. The last day will be dedicated to technical demonstrations and satellite meetings. The event will be hybrid with an in-person, on-site venue and the possibility to join virtually.  For those attending in person, there will be a social reception during the evening of Tuesday, October 15, and a dinner on Thursday, 17th.

As advances in experimental methods create growing datasets and higher resolution and more complex measurements, machine learning (ML) is rapidly becoming the major tool to analyze complex datasets over many different disciplines. Following the rapid rise of ML through deep learning algorithms, the investigation of processing technologies and strategies to accelerate deep learning and inference is well underway. We envision this will enable a revolution in experimental design and data processing as a part of the scientific method to accelerate discovery greatly. This workshop is aimed at current and emerging methods and scientific applications for deep learning and inference acceleration, including novel methods of efficient ML algorithm design, ultrafast on-detector inference and real-time systems, acceleration as-a-service, hardware platforms, coprocessor technologies, distributed learning, and hyper-parameter optimization.

Abstract submission deadline: September 16th, 2024
Registration deadline: October 1st,2024

Organising Committee:
Mia Liu (Chair)
Maria Dadarlat (Co-chair)
Andy Jung
Norbert Neumeister
Wei Xie
Paul Duffel
Haitong Li
Guang Ling
Eugenio Culurciello
Yong Chen
Alexandra Boltasseva
Laimei Nie

Scientific Committee:
Thea Aarrestad (ETH Zurich)
Javier Duarte (UCSD)
Phil Harris (MIT)
Burt Holzman (Fermilab) 
Scott Hauck (U. Washington)
Shih-Chieh Hsu (U. Washington)
Sergo Jindariani (Fermilab)
Mia Liu (Purdue University)
Allison McCarn Deiana (Southern Methodist University)
Mark Neubauer (U. Illinois Urbana-Champaign)
Jennifer Ngadiuba (Fermilab)
Maurizio Pierini (CERN)
Sioni Summers (CERN)
Alex Tapper (Imperial College)
Nhan Tran (Fermilab)

  

Tuesday, 15 October

1 Welcome

Invited talks

invited talks 30 mins + 5 mins Q&A

2 Opening Talk

Speaker: Javier Mauricio Duarte (Univ. of California San Diego (US))

3 Fast ML at the LHC

Speaker: Dylan Sheldon Rankin (University of Pennsylvania (US))

10:55 Coffee

Invited talks

invited talks 30 mins + 5 mins Q&A

4 Industry talk by AMD

Speaker: Abhishek Jain (AMD)

13:05 Lunch

Contributed talks

13 mins + 2 mins Q&A

5 Contributed talk 1

6 Contributed talk 2

7 Contributed talk 3

8 Contributed talk 4

Lighting talks

16:00 Coffee break

Contributed talks

13 mins + 2 mins Q&A

19:00 Reception

Wednesday, 16 October

Invited talks

9 Day 2: Invited talk 1

10 Day 2: Invited talk 2

11 Day 2: Invited talk 3

10:45 Coffee

Invited talks

invited talks 30 mins + 5 mins Q&A

12 Invited talk day 2

13 Invited talk day 2

12:55 Lunch

Contributed talks

13 mins + 2 mins Q&A

Lighting talks

16:00 Coffee

Contributed talks

13 mins + 2 mins Q&A

Thursday, 17 October

Invited talks

invited talks 30 mins + 5 mins Q&A

14 Day 3: Invited talk 1

15 Day 3: Invited talk 2

10:45 Coffee

Invited talks

invited talks 30 mins + 5 mins Q&A

12:00 Lunch

Contributed talks

13 mins + 2 mins Q&A

15:00 Coffee

16 Physics Colloquium [No remote participation]

Speaker: Philip Coleman Harris (Massachusetts Inst. of Technology (US))

17 HLS4ML developer's meeting

18:45 Conference Dinner

Friday, 18 October

HLS4ML tutorial

Next Generation Triggers

SONIC developer's meeting and tutorial

ECE Distinguished Lecture: Prof David Miller (Stanford)

12:00 lunch

Awards and Closeout

Fast ML not-for-profit chat