Name: Accelerating Physics with ML@MIT
Start: 2023-01-28T13:00:00-05:00
End: 2023-02-02T18:00:00-05:00
Location: No location set

Accelerating Physics with ML@MIT

from Saturday, 28 January 2023 (13:00) to Thursday, 2 February 2023 (18:00)

Monday, 23 January 2023
Tuesday, 24 January 2023
Wednesday, 25 January 2023
Thursday, 26 January 2023
Friday, 27 January 2023
Saturday, 28 January 2023

13:00 Workshop Hackathon #1

13:00 - 14:30

14:30 Coffee Break
Coffee Break
14:30 - 15:00

15:00 Workshop Hackathon #2

15:00 - 17:00
Sunday, 29 January 2023

09:00 Workshop Hackathon #3

09:00 - 10:30

10:30 Coffee Break
Coffee Break
10:30 - 11:00

11:00 Workshop Hackathon #4

11:00 - 12:30

12:30 Lunch Break
Lunch Break
12:30 - 14:00

14:00 Workshop Hackathon #5

14:00 - 15:30

15:30 Coffee Break
Coffee Break
15:30 - 16:00

16:00 Workshop Hackathon #6

16:00 - 17:30

Monday, 30 January 2023
09:00 Workshop Discussion #1: Introductions and software ecosystems for machine learning
Introductions and software ecosystems for machine learning
09:00 - 10:30
Contributions

09:00 Workshop goals - Philip Coleman Harris (Massachusetts Inst. of Technology (US))

09:30 Inference-as-a-service in high energy physics - William Patrick Mccormack (Massachusetts Inst. of Technology (US))

10:00 Inference-as-a-service in gravitational-wave physics - Alec Gunny Alec Gunny
10:30 Coffee Break
Coffee Break
10:30 - 11:00
11:00 Workshop Discussion #2: Machine learning applications in gravitational-wave searches
Machine learning applications in gravitational-wave searches
11:00 - 12:30
Contributions

11:00 Searches for compact binary coalescences-I - Damon Beveridge Damon Beveridge

11:15 Searches for compact binary coalescences-II - Ethan Marx (MIT) Ethan Marx

11:30 Denoising methods-I - Saleem Muhammed

11:45 Denoising methods-II - Chia-Jui Chou (National Yang Ming Chiao Tung University) Chia-Jui Chou

12:00 Parameter estimation methods - Maximillian Dax
12:30 Lunch Break
Lunch Break
12:30 - 14:00
14:00 Workshop Discussion #3: Machine learning in electromagnetic astronomy
Machine learning in electromagnetic astronomy
14:00 - 15:30
Contributions

14:00 The Challenges of Identification, Classification and Inference for Time-domain Astrophysics with Big Data - Ashley Villar

14:30 Multi-messenger astronomy infrastructure for optical follow-ups - Konstantin Malanchev

15:00 Challenges for identifying and following-up the next kilonova - Niharika Sravan
15:30 Coffee Break
Coffee Break
15:30 - 16:00
16:00 Workshop Discussion #4: Applications in High Energy Physics
Applications in High Energy Physics
16:00 - 17:30
Contributions

16:00 Software Infrastructure Challenges for IaaS with HEP (20'+10') - Kevin Pedro (Fermi National Accelerator Lab. (US))

16:35 SONIC Inference as a Service for Point Clouds - Yongbin Feng (Fermi National Accelerator Lab. (US))

17:00 ML GPU deployments for Neutrino Reconstruction - Tingjun Yang (Fermi National Accelerator Lab. (US))
Tuesday, 31 January 2023
09:00 Workshop Discussion #5: Anomaly Detection applications and challenges
Anomaly Detection applications and challenges
09:00 - 10:30
Contributions

09:00 Anomaly detection for EM - Daniel Muthukrishna (MIT)

09:20 Anomaly detection in GW - Ryan Raikman (Carnegie Mellon University)

09:40 MLY Pipeline - Vasileios Skliris (Cardiff University)

10:00 Anomaly Detection in HEP - Katya Govorkova (Massachusetts Inst. of Technology (US))
10:30 Coffee Break
Coffee Break
10:30 - 11:00
11:00 Workshop Discussion #6: Hardware acceleration
Hardware acceleration
11:00 - 12:30
Contributions

11:00 Point-Voxel CNN - Zhijian Liu

11:30 Sparse GPU implementations - Haotian Tang

12:00 Computing at the Massachusetts Green High Performance Center - Chris Hill
12:30 Lunch Break
Lunch Break
12:30 - 14:00
14:00 Workshop Discussion #7: HPCs
HPCs
14:00 - 15:30
Contributions

14:00 ML Workflows on NSERC - Steven Farrell (Lawrence Berkeley National Laboratory)

14:30 ML Algorithms at SDSC/NRP - Frank Wurthwein (UCSD)

14:50 HPC Discussion
15:30 Coffee Break
Coffee Break
15:30 - 16:00

16:00 Workshop Discussion #8: Break out session and white paper drafting
Break out session and white paper drafting
16:00 - 17:30
Wednesday, 1 February 2023
09:00 Workshop Discussion #9: Multidisciplinary opportunities
Multidisciplinary opportunities
09:00 - 10:45
Contributions

09:00 Machine learning applications in Icecube - Josh Peterson

09:20 Pointing to a Supernova - Kate Scholberg

09:40 Binary neutron star early warning detection using ML - Alistair Mcleod

09:55 Localization and waveform extraction for compact binary coalescences - Chayan Chatterjee

10:10 Unsupervised Learning for TESS Variable Stars - Jeroen Audenaert

10:30 Contextualized machine learning for applied data science - Ben Lengerich
10:45 Coffee Break
Coffee Break
10:45 - 11:30
11:30 Workshop Discussion #10: Summaries and Actions out of the workshop discussions
Summaries and Actions out of the workshop discussions
11:30 - 12:30
Contributions

11:30 HEP - William Patrick Mccormack (Massachusetts Inst. of Technology (US))

11:50 GW - Deep Chatterjee Deep Chatterjee Deep Chatterjee

12:10 EM Astronomy - Daniel Muthukrishna Daniel Muthukrishna (MIT) Daniel Muthukrishna
12:30 Lunch Break
Lunch Break
12:30 - 14:00

14:00 Workshop Hackathon #7

14:00 - 15:30

15:30 Coffee Break
Coffee Break
15:30 - 16:00

16:00 Workshop Hackathon #8

16:00 - 17:30
Thursday, 2 February 2023

09:00 Workshop Hackathon #9

09:00 - 10:30

10:30 Coffee Break
Coffee Break
10:30 - 11:00

11:00 Workshop Hackathon #10

11:00 - 12:30

12:30 Lunch Break
Lunch Break
12:30 - 14:00

14:00 Workshop Hackathon #11

14:00 - 15:30

15:30 Coffee Break
Coffee Break
15:30 - 16:00

16:00 Workshop Hackathon #12

16:00 - 17:30