Name: A3D3 All-hands meeting
Start: 2024-10-14T08:00:00-04:00
End: 2024-10-14T21:35:00-04:00
Location: Convergence Center @ Purdue University

A3D3 All-hands meeting

Monday 14 October 2024 - 08:00
Convergence Center @ Purdue University (Innovation Room)

: Sessions

: Talks

: Breaks

14 Oct 2024

08:00	--- Registration ---
09:00	Morning Plenary (until 10:00)
09:00	Welcome - Seungbin Park Yulei Zhang (University of Washington (US)) A3D3_AllHands_Introduction_2024_SeungbinPark.pdf
09:10	Efficient Multi-modal LLM on the Edge - Dr Song Han (MIT)
09:35	Distribution Shifts in Graph Machine Learning and Graph Domain Adaptation - Pan Li purdue-talk-2024-fall - allhands.pdf purdue-talk-2024-fall - allhands.pptx
10:00	Morning Plenary (until 11:15)
10:00	Trainee-led: Overview of MMA - Will Benoit A3D3 All-Hands MMA Overview.pdf
10:15	Trainee-led: Overview of Neuro - Seungbin Park A3D3_AllHands_Neuro_2024_SeungbinPark.pdf
10:30	Trainee-led: Overview of HEP - Yuan-Tang Chou (University of Washington (US)) Overview of HEP.pdf
10:45	Trainee-led: Overview of HAC - Siqi Miao Overview_of_HAC.pdf
11:00	NSF HDR ML Anomaly Detection Challenge - Advaith Anand (University of Washington (US)) A3D3 All Hands NSF HDR ML Challenge A3D3 All Hands NSF HDR ML Challenge
11:15	--- Coffee ---
11:45	Morning Parallels (until 12:45)
11:45	Dr. Zhijian Liu - Zhijian Liu (Massachusetts Institute of Technology)
11:50	Dr. Julia Gonski - Julia Lynne Gonski (SLAC National Accelerator Laboratory (US)) 1014_jgonski_a3d3intro.pdf
11:55	Dr. Dylan Rankin - Dylan Sheldon Rankin (University of Pennsylvania (US)) a3d3_dsr_faculty_14oct24.pdf
12:00	Panel Discusion - Zhijian Liu (Massachusetts Institute of Technology) Dylan Sheldon Rankin (University of Pennsylvania (US)) Julia Lynne Gonski (SLAC National Accelerator Laboratory (US))

12:45	--- Lunch ---
13:45	Afternoon Plenary (until 14:15) A3D3 All-Hands 2024 Town Hall Notes.pdf A3D3_TraineeSurvey_2024_SeungbinPark.pdf
13:45	Postbac research experience: light from black holes and other multi-messenger astronomy - Kira Nolan KiraNolan_A3D3_101424.pdf
13:55	Attention at Silicon Speed: Towards Efficient Transformers on FPGAs - Rian Flynn (Purdue University (US)) 20241014-A3D3-Postbacc-Talk-Rian-Flynn.pdf Talk slides
14:05	Postbac Research Experience: Multimodal Classification of Astronomical Transients - Alexandra Junell Brown AJBrown-A3D3_Postbac.pptx
14:15	Afternoon Plenary (until 15:10) A3D3 All-Hands 2024 Town Hall Notes.pdf A3D3_TraineeSurvey_2024_SeungbinPark.pdf
14:15	Implementation of `traccc` as-a-service - Miles Cochran-Branson (University of Washington (US)) a3d3_all_hands_traccc_aaS.pdf present_version_traccc_aaS.pdf
14:28	Channel tagging: identifying events with supernova pointing information - Janina Dorin Hakenmueller (Duke University) 20241014_a3d3_channeltagging.pdf
14:41	Combining Neural Networks for IceCube DeepCore Reconstruction and Classification Tasks - Josh Peterson JHPeterson_A3D3_2024_Lightning_Talk.pdf
14:54	Real-time Anomaly Detection at the CMS L1 Trigger - Melissa Quinnan (Univ. of California San Diego (US)) a3d3_hep_talk_quinnan.pdf
15:10	--- Coffee ---
15:30	Afternoon Plenary (until 16:30) A3D3 All-Hands 2024 Town Hall Notes.pdf A3D3_TraineeSurvey_2024_SeungbinPark.pdf
15:30	Neural Architecture Codesign for Fast Physics Applications - Jason Weitz (UCSD) A3D3_NAC.pdf
15:43	ConNAS4ML: Gradient-Based NAS Framework with Hardware Constraints for hls4ml - ChiJui Chen A3D32024_ConNAS4ML_ChiJuiChen.pdf
15:56	Autoencoders for Anomaly Detection and Output Reduction on the Edge (AADORE) - Alexander Yue AADORE_A3D3.pdf
16:09	Closed-loop Brain Stimulation in NHPs using hardware-accelerated Machine Learning - Rajeev Botadra FML2024_AllHandsMeeting_Slides.pdf FML2024_AllHandsMeeting_Slides.pptx
16:30	Afternoon Plenary (until 17:15) A3D3 All-Hands 2024 Town Hall Notes.pdf A3D3_TraineeSurvey_2024_SeungbinPark.pdf
17:15	Poster Session / Reception (until 19:42)
17:15	Decoding multi-limb trajectories of naturalistic running from calcium imaging using deep learning - Seungbin Park
17:20	Noise or Astrophysical: Developing Machine Learning Classifiers for Characterizing Gravitational Wave Events - Seiya Tsukamoto
17:25	Detecting the Invisible: Electron Hit Localization in High-Resolution TEM Images Using Deep Learning on FPGAs - Derrick Appiah Osei
17:30	Estimating the Hubble Constant by combining posteriors from Multi-Messenger Kilonovae Observations - Megan Averill
17:35	Real-time compression of CMS detector data with machine learning - Mariel Peczak
17:40	Multi-messenger Astronomy Observations Via Alert Stream Filtering - Kira Nolan (California Institute of Technology)
17:45	Improving Sensitivity to Neutron Star Gravitational Wave Events using the Qp Transform - Emma de Bruin
17:50	Model Logging for FPGA Deployment - Julian Goddy
17:55	Accelerating Subglacial Bed Topography Prediction in Greenland: A Performance Evaluation of Spark-Optimized Machine Learning Models - Mostafa Cham (iHARP)
18:00	Early-time Classification of Astronomical Transients - Alexandra Junell Brown
18:05	Finding Binary Black Hole Mergers - Steven Henderson (UMN - Twin Cities)
18:10	Online track reconstruction with graph neural networks on FPGAs for the ATLAS experiment - Jared Burleson (University of Illinois at Urbana-Champaign)
18:15	Smart Pixels: A Machine Learning Approach Towards Data Reduction in Next-Generation Particle Detectors - David Jiang (Univ. Illinois at Urbana Champaign (US))
18:28	Foundation Model for Real-Time Model Selection and Fitting - Cymberly Tsai

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