Name: Fast Machine Learning for Science Workshop 2022
Start: 2022-10-03T09:00:00-05:00
End: 2022-10-06T12:30:00-05:00
Location: Southern Methodist University

Fast Machine Learning for Science Workshop 2022

from Monday, October 3, 2022 (9:00 AM) to Thursday, October 6, 2022 (12:30 PM)

Monday, October 3, 2022
9:00 AM Welcome - Alessio Deiana (CERN) Allison Mccarn Deiana (Southern Methodist University (US))
Welcome
- Alessio Deiana (CERN)
- Allison Mccarn Deiana (Southern Methodist University (US))
9:00 AM - 9:05 AM
9:05 AM Machine Learning for Science - Pan Li (Purdue University)
Machine Learning for Science
- Pan Li (Purdue University)
9:05 AM - 9:45 AM
9:50 AM Efficient Computer Architectures - Sophia Shao (UC Berkeley)
Efficient Computer Architectures
- Sophia Shao (UC Berkeley)
9:50 AM - 10:30 AM
10:30 AM Coffee
Coffee
10:30 AM - 11:00 AM
11:00 AM Applications and Opportunities at the Large Hadron Collider - Maximilian J Swiatlowski (TRIUMF (CA))
Applications and Opportunities at the Large Hadron Collider
- Maximilian J Swiatlowski (TRIUMF (CA))
11:00 AM - 11:40 AM
11:45 AM Application and Opportunities in Nuclear Physics - Jin Huang (Brookhaven National Lab)
Application and Opportunities in Nuclear Physics
- Jin Huang (Brookhaven National Lab)
11:45 AM - 12:25 PM
12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
1:45 PM Contributed Talks
Contributed Talks
1:45 PM - 3:15 PM
Contributions

1:45 PM Designing intelligent DAQ systems for radiation instrumentation with hls4ml - Audrey Corbeil Therrien (Université de Sherbrooke)

2:00 PM Design and first test results of a reconfigurable autoencoder on an ASIC for data compression at the HL-LHC - Danny Noonan (Fermi National Accelerator Lab. (US))

2:05 PM Increasing the LHC Computational Power by integrating GPUs as a service - William Patrick Mccormack (Massachusetts Inst. of Technology (US)) Yongbin Feng (Fermi National Accelerator Lab. (US))

2:10 PM Exa.TrkX inference as-a-service - Yongbin Feng (Fermi National Accelerator Lab. (US))

2:15 PM Quantized ONNX (QONNX) - Jovan Mitrevski (Fermi National Accelerator Lab. (US))

2:30 PM Accelerating JEDI-net for jet tagging on FPGAs - Zhiqiang Que (Imperial College London)

2:45 PM Implementation of a pattern recognition neural network for live reconstruction using AI processors - Patrick Schwaebig

3:00 PM FKeras: A Fault Tolerance Library for DNNs - Olivia Weng
3:15 PM Coffee
Coffee
3:15 PM - 3:45 PM
3:45 PM Contributed Talks
Contributed Talks
3:45 PM - 5:15 PM
Contributions

3:45 PM Neural network accelerator for quantum control - Giuseppe Di Guglielmo (Fermilab)

4:00 PM End-to-End Vertex Finding for the CMS Level-1 Trigger - Benjamin Radburn-Smith (Imperial College (GB)) Christopher Edward Brown (Imperial College (GB))

4:15 PM Resource Efficient and Low Latency GNN-based Particle Tracking on FPGA - Bo-Cheng Lai Shi-Yu Huang

4:30 PM Neural Signal Compression System for a Seizure-Predicting Brain Implant in CMOS 28nm - William Lemaire

4:45 PM Exploring FPGA in-storage computing for Supernova Burst detection in LArTPCs - Benjamin Hawks (Fermi National Accelerator Lab)

5:00 PM Rapid Generation of Kilonova Light Curves Using Conditional Variational Autoencoder - Surojit Saha (Institute of Astronomy, National Tsing Hua University, Taiwan)
6:00 PM

6:00 PM - 8:00 PM
Tuesday, October 4, 2022
9:00 AM Applications and Opportunities for Machine Controls - Verena Kain (CERN)
Applications and Opportunities for Machine Controls
- Verena Kain (CERN)
9:00 AM - 9:40 AM
9:45 AM Applications and Opportunities in Fusion Systems - Chris Hansen (University of Washington)
Applications and Opportunities in Fusion Systems
- Chris Hansen (University of Washington)
9:45 AM - 10:25 AM
10:30 AM Coffee
Coffee
10:30 AM - 11:00 AM
11:00 AM Autonomous experiments in scanning probe microscopy: opportunities for rapid inference and decision making - Rama Vasudevan (ORNL)
Autonomous experiments in scanning probe microscopy: opportunities for rapid inference and decision making
- Rama Vasudevan (ORNL)
11:00 AM - 11:30 AM
11:30 AM Toward Real Time Decision-Making in Material Science Experiments - Mitra Taheri (JHU)
Toward Real Time Decision-Making in Material Science Experiments
- Mitra Taheri (JHU)
11:30 AM - 12:00 PM
12:00 PM Some current challenges in materials measurements: an industrial perspective - Roger Proksch (Oxford Instruments)
Some current challenges in materials measurements: an industrial perspective
- Roger Proksch (Oxford Instruments)
12:00 PM - 12:30 PM
12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
1:30 PM
1:30 PM - 3:15 PM
Contributions

1:30 PM Demonstration of Machine Learning-assisted real-time noise regression in LIGO - Muhammed Saleem Cholayil (University of Minnesota)

1:45 PM Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks - Alibek Kaliyev (Lehigh University)

2:00 PM Data Driven Weather Forecasting with Rudimentary Observables - Luke Fairbanks (ucsd)

2:05 PM Low-latency Noise Subtraction of Gravitational Wave Data by DeepClean - Chia-Jui Chou (National Yang Ming Chiao Tung University)

2:10 PM Harnessing ultrafast ML for new algorithms at the CMS L1 trigger - Daniel Diaz (Univ. of California San Diego (US))

2:15 PM Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors - Micol Rigatti (Fermi National Accelerator Lab. (US))

2:30 PM Application of deep learning to instability tracking using high-speed video cameras in magnetic confinement fusion - Yumou Wei (Columbia University)

2:45 PM Fast recurrent neural networks on FPGAs with hls4ml - Elham E Khoda (University of Washington (US))

3:00 PM Deep Neural Network Algorithms in the CMS Level-1 Trigger - Anthony Vizcaino Aportela (Univ. of California San Diego (US))
3:15 PM Coffee
Coffee
3:15 PM - 3:45 PM
3:45 PM
3:45 PM - 5:15 PM
Contributions

3:45 PM Extremely Noisy 4D-TEM Strain Mapping Using Cycle Consistent Spatial Transforming Autoencoders - Shuyu Qin

4:00 PM Quantized Distilled Autoencoder Model on FPGA for Real-Time Crystal Structure Detection in 4D Scanning Transmission Electron Microscopy - Ryan Forelli (Lehigh University)

4:15 PM Deployment of ML in changing environments - Benjamin Radburn-Smith (Imperial College (GB)) Christopher Edward Brown (Imperial College (GB)) Marco Barbone

4:30 PM Low-latency Calorimetry Clustering at the LHC with SPVCNN - Alexander Joseph Schuy (University of Washington (US))

4:45 PM CryoAI – Prototyping cryogenic chips for machine learning at 22nm - Manuel Valentin (Northwestern University)

5:00 PM Next Generation Coprocessors as a service - Dylan Sheldon Rankin (Massachusetts Inst. of Technology (US))
6:00 PM

6:00 PM - 9:00 PM
Wednesday, October 5, 2022
9:00 AM Beyond CMOS - Jennifer Hasler (Georgia Tech)
Beyond CMOS
- Jennifer Hasler (Georgia Tech)
9:00 AM - 9:40 AM
9:45 AM Applications and Opportunities in Neutrino and DM experiments - Jonathan Asaadi (University of Texas at Arlington) Jonathan Asaadi (University of Texas at Arlington (US))
Applications and Opportunities in Neutrino and DM experiments
- Jonathan Asaadi (University of Texas at Arlington)
- Jonathan Asaadi (University of Texas at Arlington (US))
9:45 AM - 10:25 AM
10:30 AM Coffee
Coffee
10:30 AM - 11:00 AM
11:00 AM Benchmarking Fast ML systems - Vijay Reddi (Harvard University)
Benchmarking Fast ML systems
- Vijay Reddi (Harvard University)
11:00 AM - 11:40 AM
11:45 AM The need for low latency with billion-year old signals - Matthew Graham (California Institute of Technology) Matthew Graham (Caltech)
The need for low latency with billion-year old signals
- Matthew Graham (California Institute of Technology)
- Matthew Graham (Caltech)
11:45 AM - 12:25 PM
12:30 PM Lunch
Lunch
12:30 PM - 1:30 PM
1:30 PM
1:30 PM - 3:15 PM
Contributions

1:30 PM A Deep Learning Approach to Particle Identification for the AMS Electromagnetic Calorimeter - Raheem Hashmani (Middle East Technical University (TR))

1:45 PM A Normalized Autoencoder for LHC triggers - Luigi Favaro

2:00 PM Interaction Network Autoencoder in the Level-1 Trigger - Sukanya Krishna (Univ. of California San Diego (US))

2:05 PM Large CNN for HLS4ML and Deepcalo - ChiJui Chen Lin-Chi Yang Yan-Lun Huang

2:10 PM End-to-end acceleration of machine learning in gravitational wave physics - Alec Gunny (Massachusetts Institute of Technology)

2:15 PM FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning - Jules Muhizi (Fermilab/Harvard University)

2:30 PM Robust anomaly detection using NuRD - Abhijith Gandrakota (Fermi National Accelerator Lab. (US))

2:45 PM Quantized Neural Networks on FPGAs using HAWQ-V3 and hl4ml - Javier Ignacio Campos (Fermi National Accelerator Lab. (US))

3:00 PM Implementing Deep Neural Network Algorithms inside the CMS Level-1 Trigger - Duc Hoang (MIT)
3:15 PM Coffee
Coffee
3:15 PM - 3:45 PM
3:45 PM
3:45 PM - 5:15 PM
Contributions

3:45 PM Real-time image processing for high-resolution imaging detectors - Georgia Karagiorgi

4:00 PM Semi-supervised Graph Neural Networks for Pileup Noise Removal - Shikun Liu

4:05 PM A Machine Learning Software Infrastructure for Gravitational Wave Signal Discovery - Ethan Marx (MIT)

4:10 PM Online-compatible Unsupervised Non-resonant Anomaly Detection - Vinicius Massami Mikuni (Lawrence Berkeley National Lab. (US))

4:15 PM In-System Parameter Update and I/O Capture for Machine Learning IP Cores - Brett McMillian (Crossfield Technology LLC)

4:30 PM Detection for Core-collapse Supernova and Fast Data Preprocessing - Andy Chen (National Yang Ming Chiao Tung University (NYCU))

4:35 PM EMD Neural Network Loss for ECON-T ASIC Autoencoder - Rohan Shenoy (Univ. of California San Diego (US))

4:40 PM A novel ML-based method of primary vertex reconstruction in high pile-up condition - Haoran Zhao (University of Washington (US))

4:45 PM In-Pixel AI: From Algorithm to Accelerator - Priyanka Dilip (Stanford University / Fermilab)

5:00 PM Autonomous real-time science-driven follow-up of survey transients - Niharika Sravan
Thursday, October 6, 2022
9:00 AM hls4ml tutorial - Sioni Paris Summers (CERN) Elham E Khoda (University of Washington (US))
hls4ml tutorial
- Sioni Paris Summers (CERN)
- Elham E Khoda (University of Washington (US))
9:00 AM - 11:00 AM
11:00 AM hls4ml community session
hls4ml community session
11:00 AM - 12:30 PM

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