VLSI implementation of an M-array image filter based on shift register array. - Chen-Yi Lee; Jer-Min Tsai; Shih-Chieh Hsu (Integr., 1993)

Collective Regulatory Focus and Control Mechanisms: The Impact of Regulatory Fit on ISD Project Performance. - YuWen Hung; Shih-Chieh Hsu (ECIS, 2015)

Constructing a Travel Risks' Evaluation Model for Tour Freelancers Based on the ANP Approach. - Chin-Tsai Lin; Shih-Chieh Hsu (Adv. Oper. Res., 2016)

A study of the Effects of Information Security Advocacy. - Yan-Ye Lin; Hui-Mei Hsu; Shih-Chieh Hsu (PACIS, 2019)

FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. - Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Sergo Jindariani; Suffian Khan; Benjamin Kreis; Brian Lee; Mia Liu; Vladimir Loncar; Jennifer Ngadiuba; et al. (Comput. Softw. Big Sci., 2019)

FPGAs-as-a-Service Toolkit (FaaST). - Dylan S. Rankin; Jeffrey D. Krupa; Philip C. Harris; Maria Acosta Flechas; Burt Holzman; Thomas Klijnsma; Kevin Pedro; Nhan Tran; Scott Hauck; Shih-Chieh Hsu; Matthew Trahms; Kelvin Lin; et al. (H2RC@SC, 2020)

GPU coprocessors as a service for deep learning inference in high energy physics. - Jeffrey D. Krupa; Kelvin Lin; Maria Acosta Flechas; Jack Dinsmore; Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Thomas Klijnsma; Mia Liu; Kevin Pedro; et al. (CoRR, 2020)

Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networks. - Michael James Fenton; Alexander Shmakov; Ta-Wei Ho; Shih-Chieh Hsu; Daniel Whiteson; Pierre Baldi (CoRR, 2020)

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. - Farah Fahim; Benjamin Hawks; Christian Herwig; James Hirschauer; Sergo Jindariani; Nhan Tran; Luca P. Carloni; Giuseppe Di Guglielmo; Philip C. Harris; Jeffrey D. Krupa; Dylan S. Rankin; Manuel Blanco Valentin; et al. (CoRR, 2021)

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. - Xiangyang Ju; Daniel Murnane; Paolo Calafiura; Nicholas Choma; Sean Conlon; Steven Farrell; Yaoyuan Xu; Maria Spiropulu; Jean-Roch Vlimant; Adam Aurisano; Jeremy Hewes; Giuseppe Cerati; et al. (CoRR, 2021)

SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention. - Alexander Shmakov; Michael James Fenton; Ta-Wei Ho; Shih-Chieh Hsu; Daniel Whiteson; Pierre Baldi (CoRR, 2021)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (CoRR, 2021)

Graph Neural Networks for Charged Particle Tracking on FPGAs. - Abdelrahman Elabd; Vesal Razavimaleki; Shi-Yu Huang; Javier M. Duarte; Markus Atkinson; Gage DeZoort; Peter Elmer; Jin-Xuan Hu; Shih-Chieh Hsu; Bo-Cheng Lai; Mark S. Neubauer; Isobel Ojalvo; et al. (CoRR, 2021)

GPU coprocessors as a service for deep learning inference in high energy physics. - Jeffrey D. Krupa; Kelvin Lin; Maria Acosta Flechas; Jack Dinsmore; Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Thomas Klijnsma; Mia Liu; Kevin Pedro; et al. (Mach. Learn. Sci. Technol., 2021)

Physics Community Needs, Tools, and Resources for Machine Learning. - Philip C. Harris; Erik Katsavounidis; William Patrick McCormack; Dylan S. Rankin; Yongbin Feng; Abhijith Gandrakota; Christian Herwig; Burt Holzman; Kevin Pedro; Nhan Tran; Tingjun Yang; Jennifer Ngadiuba; et al. (CoRR, 2022)

Exploring the Universality of Hadronic Jet Classification. - Kingman Cheung; Yi-Lun Chung; Shih-Chieh Hsu; Benjamin Nachman (CoRR, 2022)

QONNX: Representing Arbitrary-Precision Quantized Neural Networks. - Alessandro Pappalardo; Yaman Umuroglu; Michaela Blott; Jovan Mitrevski; Benjamin Hawks; Nhan Tran; Vladimir Loncar; Sioni Summers; Hendrik Borras; Jules Muhizi; Matthew Trahms; Shih-Chieh Hsu; et al. (CoRR, 2022)

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. - Hendrik Borras; Giuseppe Di Guglielmo; Javier M. Duarte; Nicolò Ghielmetti; Benjamin Hawks; Scott Hauck; Shih-Chieh Hsu; Ryan Kastner; Jason Liang; Andres Meza 001; Jules Muhizi; Tai Nguyen 003; et al. (CoRR, 2022)

Data Science and Machine Learning in Education. - Gabriele Benelli; Thomas Y. Chen; Javier M. Duarte; Matthew Feickert; Matthew J. Graham; Lindsey Gray; Dan Hackett; Philip C. Harris; Shih-Chieh Hsu; Gregor Kasieczka; Elham E Khoda; Matthias Komm; et al. (CoRR, 2022)

Graph Neural Networks for Charged Particle Tracking on FPGAs. - Abdelrahman Elabd; Vesal Razavimaleki; Shi-Yu Huang; Javier M. Duarte; Markus Atkinson; Gage DeZoort; Peter Elmer; Scott Hauck; Jin-Xuan Hu; Shih-Chieh Hsu; Bo-Cheng Lai; Mark S. Neubauer; et al. (Frontiers Big Data, 2022)

Quantum Machine Learning with SQUID. - Alessandro Roggero; Jakub Filipek; Shih-Chieh Hsu; Nathan Wiebe (Quantum, 2022)

Low Latency Edge Classification GNN for Particle Trajectory Tracking on FPGAs. - Shi-Yu Huang; Yun-Chen Yang; Yu-Ru Su; Bo-Cheng Lai; Javier M. Duarte; Scott Hauck; Shih-Chieh Hsu; Jin-Xuan Hu; Mark S. Neubauer (FPL, 2023)

Extended Symmetry Preserving Attention Networks for LHC Analysis. - Michael James Fenton; Alexander Shmakov; Hideki Okawa; Yuji Li; Ko-Yang Hsiao; Shih-Chieh Hsu; Daniel Whiteson; Pierre Baldi (CoRR, 2023)

Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. - Elham E Khoda; Dylan S. Rankin; Rafael Teixeira de Lima; Philip C. Harris; Scott Hauck; Shih-Chieh Hsu; Michael Kagan; Vladimir Loncar; Chaitanya Paikara; Richa Rao; Sioni Summers; Caterina Vernieri; et al. (Mach. Learn. Sci. Technol., 2023)

Deep-Learning Based Classification of Clinical Significance for Prostate Cancer. - Jia-Hao Chen; Shih-Chieh Hsu; Chih-Yu Shen; Gia-Shing Shieh; Chun-Hung Yang; Yung-Ming Kuo (ICCE-Taiwan, 2024)

Ultra Fast Transformers on FPGAs for Particle Physics Experiments. - Zhixing Jiang; Dennis Yin; Elham E Khoda; Vladimir Loncar; Ekaterina Govorkova; Eric A. Moreno; Philip C. Harris; Scott Hauck; Shih-Chieh Hsu (CoRR, 2024)

FPGA Deployment of LFADS for Real-time Neuroscience Experiments. - Xiaohan Liu; Chi-Jui Chen; YanLun Huang; LingChi Yang; Elham E Khoda; Yihui Chen; Scott Hauck; Shih-Chieh Hsu; Bo-Cheng Lai (CoRR, 2024)

Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation. - Qibin Liu; Chase Shimmin; Xiulong Liu; Eli Shlizerman; Shu Li; Shih-Chieh Hsu (CoRR, 2024)

Low Latency Transformer Inference on FPGAs for Physics Applications with hls4ml. - Zhixing Jiang; Dennis Yin; Yihui Chen; Elham E Khoda; Scott Hauck; Shih-Chieh Hsu; Ekaterina Govorkova; Philip C. Harris; Vladimir Loncar; Eric A. Moreno (CoRR, 2024)

FAIR Universe HiggsML Uncertainty Challenge Competition. - Wahid Bhimji; Paolo Calafiura; Ragansu Chakkappai; Yuan-Tang Chou; Sascha Diefenbacher; Jordan Dudley; Steven Farrell; Aishik Ghosh; Isabelle Guyon; Chris Harris; Shih-Chieh Hsu; Elham E Khoda; et al. (CoRR, 2024)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - Claudius Krause; Michele Faucci Giannelli; Gregor Kasieczka; Benjamin Nachman; Dalila Salamani; David Shih; Anna Zaborowska; Oz Amram; Kerstin Borras; Matthew R. Buckley; Erik Buhmann; Thorsten Buss; et al. (CoRR, 2024)

BAQET: BRAM-aware Quantization for Efficient Transformer Inference via Stream-based Architecture on an FPGA. - LingChi Yang; Chi-Jui Chen; Trung Le 002; Bo-Cheng Lai; Scott Hauck; Shih-Chieh Hsu (FPGA, 2025)

HiGTR: High-Performance FPGA Implementation of Complete GNN-based Trajectory Reconstruction for HEP. - Yun-Chen Yang; Hsuan-Wei Yu; Bo-Cheng Lai; Shih-Chieh Hsu; Mark S. Neubauer; Santosh Parajuli (FPGA, 2025)

MErBAG: Mesh Error Based Adaptive Grid Generation in System-Level Thermal Analysis. - Yu-Min Lee; Shih-Chieh Hsu; Bo-Yi Tsai; Zong-Lin Lu (ISQED, 2025)

Track reconstruction as a service for collider physics. - Haoran Zhao; Yuan-Tang Chou; Yao Yao; Xiangyang Ju; Yongbin Feng; William Patrick McCormack; Miles Cochran-Branson; Jan-Frederik Schulte; Miaoyuan Liu; Javier M. Duarte; Philip Harris; Shih-Chieh Hsu; et al. (CoRR, 2025)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)

SuperSONIC: Cloud-Native Infrastructure for ML Inferencing. - Dmitry Kondratyev; Benedikt Riedel; Yuan-Tang Chou; Miles Cochran-Branson; Noah Paladino; David Schultz; Mia Liu; Javier Duarte; Philip Harris; Shih-Chieh Hsu (CoRR, 2025)