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Fast Machine Learning for Science Workshop 2023

from Monday, September 25, 2023 (8:30 AM) to Thursday, September 28, 2023 (6:00 PM)
Imperial College London (Blackett Laboratory, Lecture Theatre 1)

        : Sessions
    /     : Talks
        : Breaks
Sep 25, 2023
Sep 26, 2023
Sep 27, 2023
Sep 28, 2023
AM
8:30 AM Registration   (Blackett Laboratory, Lecture Theatre 1)
9:30 AM
Invited Talks (until 10:30 AM) (Blackett Laboratory, Lecture Theatre 1)
9:30 AM Workshop Opening - Alex Tapper (Imperial College London) Sioni Paris Summers (CERN)   (Blackett Laboratory, Lecture Theatre 1)
9:45 AM Fast Machine Learning at the Large Hadron Collider experiments - Thea Aarrestad (ETH Zurich (CH))   (Blackett Laboratory, Lecture Theatre 1)
10:30 AM --- Break ---
11:00 AM
Invited Talks (until 12:30 PM) (Blackett Laboratory, Lecture Theatre 1)
11:00 AM Fast Machine Learning at European XFEL - Steve Aplin (EuXFEL)   (Blackett Laboratory, Lecture Theatre 1)
11:45 AM Bridging AI and biomedicine: Towards AI-driven scientific discoveries - Maria Brbic   (Blackett Laboratory, Lecture Theatre 1)
9:00 AM
Invited Talks (until 10:30 AM) (Blackett Laboratory, Lecture Theatre 1)
9:00 AM Fast Machine Learning for accelerator control - Karin Rathsman (European Spallation Source)   (Blackett Laboratory, Lecture Theatre 1)
9:45 AM Fast Machine Learning for laser wakefield acceleration - Matt Streeter   (Blackett Laboratory, Lecture Theatre 1)
10:30 AM --- Break ---
11:00 AM
Invited Talks (until 12:30 PM) (Blackett Laboratory, Lecture Theatre 1)
11:00 AM Fast ML for fusion simulation, optimization, and control - Jonathan Citrin   (Blackett Laboratory, Lecture Theatre 1)
11:45 AM Machine Learning in Exoplanet Characterisation - Kai Hou Yip Ingo Waldmann (UCL)   (Blackett Laboratory, Lecture Theatre 1)
9:00 AM
Invited Talks (until 10:30 AM) (Blackett Laboratory, Lecture Theatre 1)
9:00 AM Co-Design for Efficient & Adaptive ML - Yaman Umuroglu   (Blackett Laboratory, Lecture Theatre 1)
9:45 AM In network ML: Inference at the Speed of Data - Noa Zilberman   (Blackett Laboratory, Lecture Theatre 1)
10:30 AM --- Group Photo ---
10:45 AM --- Break ---
11:00 AM
Invited Talks (until 12:30 PM) (Blackett Laboratory, Lecture Theatre 1)
11:00 AM Need for Speed: How to harness the power of Large Language Models - Tobias Becker (Maxeler Technologies)   (Blackett Laboratory, Lecture Theatre 1)
11:45 AM Deep Learning for Fast MR Imaging and Analysis - Chen Qin   (Blackett Laboratory, Lecture Theatre 1)
9:00 AM Coprocessors/SONIC Developers Meeting - Kevin Pedro (Fermi National Accelerator Lab. (US)) William Patrick Mccormack (Massachusetts Inst. of Technology (US))   (Blackett Laboratory, Lecture Theatre 3)
9:00 AM QONNX Developers Meeting - Nhan Tran Jovan Mitrevski (Fermi National Accelerator Lab. (US)) Yaman Umuroglu   (Blackett Laboratory, Lecture Theatre 2)
10:00 AM
Tutorial - Javier Campos (until 12:00 PM) (Blackett Laboratory, Lecture Theatre 2)
PM
12:30 PM --- Lunch ---
1:30 PM
Contributed Talks (until 3:00 PM) (Blackett Laboratory, Lecture Theatre 1)
1:30 PM Smart embedded DAQ systems for radiation instrumentation – Testbench and latest results - Prof. Audrey Corbeil Therrien (Université de Sherbrooke)   (Blackett Laboratory, Lecture Theatre 1)
1:45 PM Scalable neural network models and terascale datasets for particle flow reconstruction - Farouk Mokhtar (Univ. of California San Diego (US))   (Blackett Laboratory, Lecture Theatre 1)
2:00 PM Track reconstruction for the ATLAS Phase-II High-Level Trigger using Graph Neural Networks on FPGAs - Santosh Parajuli (Univ. Illinois at Urbana Champaign (US))   (Blackett Laboratory, Lecture Theatre 1)
2:15 PM smartpixels: on-pixel featurization for single layer silicon tracking - Rachel Kovach-Fuentes (University of Chicago)   (Blackett Laboratory, Lecture Theatre 1)
2:30 PM Portable Acceleration of CMS Mini-AOD Production with Coprocessors as a Service - William Patrick Mccormack (Massachusetts Inst. of Technology (US))   (Blackett Laboratory, Lecture Theatre 1)
2:45 PM Accelerating Hadronic Calorimetry with Sparse Point-Voxel Convolutional Neural Networks - Jeffrey Krupa (Massachusetts Institute of Technology)   (Blackett Laboratory, Lecture Theatre 1)
3:00 PM --- Break ---
3:30 PM
Contributed Talks (until 4:45 PM) (Blackett Laboratory, Lecture Theatre 1)
3:30 PM Convolutional Neural Networks for Real-Time Processing of ATLAS Liquid-Argon Calorimeter Signals - Anne-Sophie Berthold (Technische Universitaet Dresden (DE))   (Blackett Laboratory, Lecture Theatre 1)
3:45 PM Fast ML inference in FPGAs for the Level-1 Scouting system at CMS - Thomas Owen James (CERN)   (Blackett Laboratory, Lecture Theatre 1)
4:00 PM Yggdrasil Conifer: Latency and resource-aware decision trees for faster FPGA inference at the LHC - Andrew George Oliver   (Blackett Laboratory, Lecture Theatre 1)
4:15 PM fwXmachina part 1: Classification with boosted decision trees on FPGA for L1 trigger - Tae Min Hong (University of Pittsburgh (US))   (Blackett Laboratory, Lecture Theatre 1)
4:30 PM Realtime Anomaly Detection in the CMS Experiment Global Trigger Test Crate - Chang Sun (ETH Zurich (CH))   (Blackett Laboratory, Lecture Theatre 1)
4:45 PM --- Break ---
5:00 PM
Contributed Talks (until 6:30 PM) (Blackett Laboratory, Lecture Theatre 1)
5:00 PM fwXmachina part 3: Anomaly detection with decision tree autoencoder on FPGA for L1 trigger - Stephen Roche (Saint Louis University)   (Blackett Laboratory, Lecture Theatre 1)
5:05 PM Fast muon identification algorithm on FPGAs for the Phase II level 0 trigger of the ATLAS experiment - Graziella Russo (Sapienza Universita e INFN, Roma I (IT))   (Blackett Laboratory, Lecture Theatre 1)
5:10 PM Neuromorphic Computing for On-Sensor Data Filtering on Smart-Pixels - Shruti R Kulkarni (Oak Ridge National Laboratory)   (Blackett Laboratory, Lecture Theatre 1)
5:15 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))   (Blackett Laboratory, Lecture Theatre 1)
5:20 PM Harnessing charged particle tracks in the Phase-2 CMS Level-1 Trigger with ultrafast Machine Learning - Christopher Edward Brown (Imperial College (GB))   (Blackett Laboratory, Lecture Theatre 1)
5:25 PM B-tagging and Tau reconstruction in the Level-1 Trigger with real-time Machine Learning - Duc Minh Hoang (MIT)   (Blackett Laboratory, Lecture Theatre 1)
5:30 PM Machine Learning based Data Compression on FPGA with HLS4ML - Pratik Jawahar (University of Manchester (UK - ATLAS))   (Blackett Laboratory, Lecture Theatre 1)
5:35 PM Using NVIDIA Triton Server for Inference-as-a-Service at Fermilab - Claire Savard (University of Colorado Boulder (US))   (Blackett Laboratory, Lecture Theatre 1)
5:40 PM Jets as sets or graphs: Fast jet classification on FPGAs for efficient triggering at the HL-LHC - Denis-Patrick Odagiu (ETH Zurich (CH))   (Blackett Laboratory, Lecture Theatre 1)
5:45 PM Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation - Mr Ryan Liu (University of California, Berkeley)   (Blackett Laboratory, Lecture Theatre 1)
5:50 PM Fast b-tagging at the high-level trigger of the ATLAS experiment - Stefano Franchellucci (Universite de Geneve (CH))   (Blackett Laboratory, Lecture Theatre 1)
5:55 PM BDT for tau identification in the ATLAS Level-1 trigger - David Reikher (Tel Aviv University (IL))   (Blackett Laboratory, Lecture Theatre 1)
6:00 PM A Convolutional Neural Network for topological fast selection algorithms in FPGAs for the HL-LHC upgrade of the CMS experiment - Maciej Mikolaj Glowacki (University of Bristol (GB))   (Blackett Laboratory, Lecture Theatre 1)
6:05 PM Low Energy LArTPC Signal Detection using Anomaly Detection - Jovan Mitrevski (Fermi National Accelerator Lab. (US))   (Blackett Laboratory, Lecture Theatre 1)
6:10 PM Graph Neural Networks on FPGAs with HLS4ML - Jan-Frederik Schulte (Purdue University (US))   (Blackett Laboratory, Lecture Theatre 1)
6:15 PM Optimizing Sparse Neural Architectures for Low-Latency Anomaly Detection - Luke McDermott (UC San Diego & Modern Intelligence)   (Blackett Laboratory, Lecture Theatre 1)
6:20 PM Accomodating Transformer in the FastML era of HEP-EX - Sitian Qian (Peking University (CN))   (Blackett Laboratory, Lecture Theatre 1)
7:00 PM
Social event (until 9:00 PM) (Blackett Laboratory, Lecture Theatre 1)
12:30 PM --- Lunch ---
1:30 PM
Contributed Talks (until 3:30 PM) (Blackett Laboratory, Lecture Theatre 1)
1:30 PM Deep Spectral Networks: Enhancing Orbit Propagation and Determination in Astrodynamics - Sabin Anton (Imperial College London, Department of Aeronautics, Postgraduate Student)   (Blackett Laboratory, Lecture Theatre 1)
1:45 PM Machine Learning Explorations in GRB Studies: From Classification to Extended Emission Identification - Keneth Stiven Garcia Cifuentes (Universidad Nacional Autónoma de México)   (Blackett Laboratory, Lecture Theatre 1)
2:00 PM GWAK: Gravitational-Wave Anomalous Knowledge with Recurrent Autoencoders - Katya Govorkova (Massachusetts Inst. of Technology (US))   (Blackett Laboratory, Lecture Theatre 1)
2:15 PM Tools and Results for Real-Time Deep Learning in Gravitational-Wave Physics - Eric Anton Moreno (Massachusetts Institute of Technology (US))   (Blackett Laboratory, Lecture Theatre 1)
2:30 PM Real Time End to End Supernova Pointing - Maira Khan   (Blackett Laboratory, Lecture Theatre 1)
2:45 PM Edge AI for accelerator controls: beam loss deblending - Jovan Mitrevski (Fermi National Accelerator Lab. (US))   (Blackett Laboratory, Lecture Theatre 1)
3:00 PM Adaptive Machine Learning for Quench Prediction - Maira Khan   (Blackett Laboratory, Lecture Theatre 1)
3:15 PM Real-Time Instability Tracking with Deep Learning on FPGAs in Magnetic Confinement Fusion Devices - Ryan Forelli (Lehigh University)   (Blackett Laboratory, Lecture Theatre 1)
3:30 PM --- Break ---
4:00 PM
Contributed Talks (until 5:40 PM) (Blackett Laboratory, Lecture Theatre 1)
4:00 PM SAMBA: A Trainable Segmentation Web-App with Deep-Learning Powered Labelling - Ronan Docherty (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
4:15 PM Real-time Fitting and Materials Characterization in Band- Excitation Piezoresponse Force Microscopy - Veronica Obute (Drexel)   (Blackett Laboratory, Lecture Theatre 1)
4:30 PM Real-Time Machine Learning in Materials Microscopy and Spectroscopy - Prof. Joshua Agar (Drexel)   (Blackett Laboratory, Lecture Theatre 1)
4:45 PM A hybrid data-driven and data assimilation operational model for long term spatiotemporal forecasting: Global and regional PM2.5 forecasting - Dr Fangxin Fang (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
5:00 PM Towards lightweight transformer-based models with multimodal data for low-latency surgical applications - Miguel Xochicale (University College London)   (Blackett Laboratory, Lecture Theatre 1)
5:15 PM Approximating Many-Electron Wave Functions using Neural Networks - Matthew Foulkes (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
5:30 PM Crystallization Learning with Delaunay Triangulation - Guosheng Yin (Department of Mathematics Imperial College London) Prof. Guosheng Yin (Department of Mathematics Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
5:35 PM Genomic Interpreter: A Hierarchical Genomic Deep Neural Network with 1D Shifted Window Transformer - Zehui Li   (Blackett Laboratory, Lecture Theatre 1)
7:00 PM Public lecture: Algorithms and Flow: Lupe Fiasco’s Creative Use of LLMs - Lupe Fiasco   (Blackett Lab. Lecture Theatre 1)
12:30 PM --- Lunch ---
1:30 PM
Contributed Talks (until 3:30 PM) (Blackett Laboratory, Lecture Theatre 1)
1:30 PM Hardware-aware pruning of real-time neural networks with hls4ml Optimization API - Benjamin Ramhorst (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
1:45 PM Efficient Quantization of Deep Learning Models for Hardware Acceleration - Cheng ZHANG (Imperial College London) Mr Jianyi Cheng (University of Cambridge)   (Blackett Laboratory, Lecture Theatre 1)
2:00 PM High Granularity Quantization​ for Ultra-Fast ML Applications on FPGAs​ - Chang Sun (ETH Zurich (CH))   (Blackett Laboratory, Lecture Theatre 1)
2:15 PM EventDetector: A Python Package for Time Series Event Detection - Dr Menouar Azib (Akkodis)   (Blackett Laboratory, Lecture Theatre 1)
2:30 PM FKeras: A Sensitivity Analysis Tool for Edge Neural Networks - Olivia Weng   (Blackett Laboratory, Lecture Theatre 1)
2:45 PM Reconfigurable Fused and Branched CNN Accelerator - Dr Marko Andjelkovic (IHP - Leibniz-Institut für innovative Mikroelektronik) Dr Markus Ulbricht (IHP - Leibniz-Institut für innovative Mikroelektronik) Mr Rizwan Tariq Syed (IHP - Leibniz-Institut für innovative Mikroelektronik) Prof. Milos Krstic (IHP - Leibniz-Institut für innovative Mikroelektronik)   (Blackett Laboratory, Lecture Theatre 1)
3:00 PM PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based Inference - Marta Andronic (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
3:15 PM Exploring medical applications of fast ML with a novel FPGA firmware framework - Freddie Renyard (University of Bristol)   (Blackett Laboratory, Lecture Theatre 1)
3:30 PM --- Break ---
4:00 PM
Contributed Talks (until 5:30 PM) (Blackett Laboratory, Lecture Theatre 1)
4:00 PM Running Converged HPC & AI Workloads on the Groq AI Inference Accelerator - Dr Tobias Becker (Maxeler Technologies)   (Blackett Laboratory, Lecture Theatre 1)
4:15 PM Optimizing for Imperfections in Analog Neural Computations on BrainScaleS-2 - Hendrik Borras (Heidelberg University) Eric Kern (Heidelberg University)   (Blackett Laboratory, Lecture Theatre 1)
4:30 PM Implementing Machine Learning Methods on QICK Hardware for Qubit Readout - Javier Campos   (Blackett Laboratory, Lecture Theatre 1)
4:45 PM Post-training ReLU Sparsification for Faster CNN Inference on FPGA Streaming Accelerators - Mr Zhewen Yu (Imperial College London) Mr Krish Agrawal (Imperial College London) Mr Alexander Montgomerie-Corcoran (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
5:00 PM ATHEENA: A Toolflow for Hardware Early-Exit Network Automation - Benjamin Biggs   (Blackett Laboratory, Lecture Theatre 1)
5:15 PM Simplifying Time-Series Recognition: Automated Feature Extraction and Modern Classification - Jan Zavadil (Department of Mathematics, FNSPE, Czech Technical University in Prague.)   (Blackett Laboratory, Lecture Theatre 1)
5:20 PM Universal approximation theorem and error bounds for quantum neural networks and quantum reservoirs - Dr Lukas Gonon (Imperial College London)   (Blackett Laboratory, Lecture Theatre 1)
5:25 PM AI Upscaling with Super Resolution CNNs on FPGAs and ASICs - Ryan Forelli (Lehigh University)   (Blackett Laboratory, Lecture Theatre 1)
5:30 PM Workshop Summary - Philip Coleman Harris (Massachusetts Inst. of Technology (US))   (Blackett Laboratory, Lecture Theatre 1)
7:00 PM
Social event (until 11:00 PM) ()
12:00 PM --- Lunch ---
1:00 PM Intel® FPGA AI Suite and AI Tensor Blocks: Empowering Real-time, Low-Latency, and Low-Power Deep Learning Inference with Intel FPGAs - Jahanzeb Ahmad Suleyman Demirsoy   (Blackett Laboratory, Lecture Theatre 2)
3:00 PM AI for Simulation: Transforming Traditional HPC with Graphcore IPUs - Alexander Titterton (Graphcore)   (Blackett Laboratory, Lecture Theatre 2)
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