Kevin Pedro

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 28

Top Topics

High Energy Physics

Scientific Data

Top Venues

Mach. Learn. Sci. Technol.

Comput. Softw. Big Sci.

Frontiers Big Data

Publications

Claire Savard, Nicholas Manganelli, Burt Holzman, Lindsey Gray, Alexx Perloff, Kevin Pedro, Kevin Stenson, Keith Ulmer
Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server. Comput. Softw. Big Sci. 8 (1) (2024)
Tejin Cai, Kenneth Herner, Tingjun Yang, Michael Wang, Maria Acosta Flechas, Philip C. Harris, Burt Holzman, Kevin Pedro, Nhan Tran
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing. Comput. Softw. Big Sci. 7 (1) (2023)
Tejin Cai, Kenneth Herner, Tingjun Yang, Michael Wang, Maria Acosta Flechas, Philip C. Harris, Burt Holzman, Kevin Pedro, Nhan Tran
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing. CoRR (2023)
Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection. Mach. Learn. Sci. Technol. 4 (2) (2023)
Andreas Adelmann, Walter Hopkins, Evangelos Kourlitis, Michael Kagan, Gregor Kasieczka, Claudius Krause, David Shih, Vinicius Mikuni, Benjamin Nachman, Kevin Pedro, Daniel Winklehner
New directions for surrogate models and differentiable programming for High Energy Physics detector simulation. CoRR (2022)
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, Michael Coughlin, Scott Hauck, Shih-Chieh Hsu, Elham E Khoda, Deming Chen, Mark S. Neubauer, Javier M. Duarte, Georgia Karagiorgi, Mia Liu
Physics Community Needs, Tools, and Resources for Machine Learning. CoRR (2022)
Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification. Mach. Learn. Sci. Technol. 3 (3) (2022)
Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR (2022)
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, Dylan S. Rankin, Natchanon Suaysom, Matt Trahms, Nhan Tran
GPU coprocessors as a service for deep learning inference in high energy physics. Mach. Learn. Sci. Technol. 2 (3) (2021)
Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang
Fast convolutional neural networks on FPGAs with hls4ml. Mach. Learn. Sci. Technol. 2 (4) (2021)
Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang
Fast convolutional neural networks on FPGAs with hls4ml. CoRR (2021)
Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification. CoRR (2021)
Aleksandra Ciprijanovic, Diana Kafkes, Gabriel N. Perdue, Kevin Pedro, Gregory F. Snyder, F. Javier Sánchez, Sandeep Madireddy, Stefan M. Wild, Brian Nord
Robustness of deep learning algorithms in astronomy - galaxy morphology studies. CoRR (2021)
Guilherme Amadio, A. Ananya, J. Apostolakis, M. Bandieramonte, S. Banerjee, A. Bhattacharyya, Calebe P. Bianchini, G. Bitzes, Philippe Canal, Federico Carminati, O. Chaparro-Amaro, G. Cosmo, J. C. De Fine Licht, V. Drogan, L. Duhem, D. Elvira, J. Fuentes, Andrei Gheata, Mihaela Gheata, Mathieu Gravey, I. Goulas, F. Hariri, S. Y. Jun, Dmitri Konstantinov, H. Kumawat, J. G. Lima, A. Maldonado-Romo, J. Martínez-Castro, Pere Mato, T. Nikitina, S. Novaes, M. Novak, Kevin Pedro, Witold Pokorski, A. Ribon, R. Schmitz, R. Seghal, Oksana Shadura, E. Tcherniaev, Sofia Vallecorsa, S. Wenzel, Y. Zhang
GeantV. Comput. Softw. Big Sci. 5 (1) (2021)
Florencia Canelli, Annapaola de Cosa, Luc Le Pottier, Jeremi Niedziela, Kevin Pedro, Maurizio Pierini
Autoencoders for Semivisible Jet Detection. CoRR (2021)
Jennifer Ngadiuba, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Mia Liu, Kevin Pedro, Nhan Tran, Edward Kreinar, Sheila Sagear, Zhenbin Wu, Duc Hoang
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml. Mach. Learn. Sci. Technol. 2 (1) (2021)
Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip C. Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey D. Krupa, Kevin Pedro, Nhan Tran
GPU-accelerated machine learning inference as a service for computing in neutrino experiments. CoRR (2020)
Nicholas Smith, Lindsey Gray, Matteo Cremonesi, Bo Jayatilaka, Oliver Gutsche, Allison Hall, Kevin Pedro, Maria Acosta Flechas, Andrew Melo, Stefano Belforte, Jim Pivarski
Coffea - Columnar Object Framework For Effective Analysis. CoRR (2020)
Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler, Vladimir Loncar, Maurizio Pierini, Shah Rukh Qasim, Marcel Rieger, Sioni Summers, Gerrit Van Onsem, Kinga Anna Wozniak, Jennifer Ngadiuba, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Mia Liu, Kevin Pedro, Nhan Tran, Edward Kreinar, Zhenbin Wu
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. CoRR (2020)
Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Duc Hoang, Sergo Jindariani, Edward Kreinar, Mia Liu, Vladimir Loncar, Jennifer Ngadiuba, Kevin Pedro, Maurizio Pierini, Dylan S. Rankin, Sheila Sagear, Sioni Summers, Nhan Tran, Zhenbin Wu
Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML. CoRR (2020)
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, Yu Lou, Ta-Wei Ho, Javier M. Duarte, Mia Liu
FPGAs-as-a-Service Toolkit (FaaST). H2RC@SC (2020)
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, Natchanon Suaysom, Matt Trahms, Nhan Tran
GPU coprocessors as a service for deep learning inference in high energy physics. CoRR (2020)
Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip C. Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey D. Krupa, Kevin Pedro, Nhan Tran
GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments. Frontiers Big Data 3 (2020)
Dylan Sheldon 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, Yu Lou, Ta-Wei Ho, Javier M. Duarte, Mia Liu
FPGAs-as-a-Service Toolkit (FaaST). CoRR (2020)
Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler, Vladimir Loncar, Maurizio Pierini, Shah Rukh Qasim, Marcel Rieger, Sioni Summers, Gerrit Van Onsem, Kinga Anna Wozniak, Jennifer Ngadiuba, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Mia Liu, Kevin Pedro, Nhan Tran, Edward Kreinar, Zhenbin Wu
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. Frontiers Big Data 3 (2020)
James Amundson, James Annis, Camille Avestruz, D. Bowring, João Caldeira, Giuseppe Cerati, C. Chang, Scott Dodelson, D. Elvira, A. Farahi, K. Genser, Lindsey Gray, Oliver Gutsche, Philip C. Harris, Jamie Kinney, James B. Kowalkowski, Rob Kutschke, S. Mrenna, Brian Nord, A. Para, Kevin Pedro, Gabriel N. Perdue, A. Scheinker, Panagiotis Spentzouris, J. St. John, Nhan Tran, Shubhendu Trivedi, Laura Trouille, W. L. K. Wu, C. R. Bom
Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan". CoRR (2019)
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, Kevin Pedro, Brandon Perez, Maurizio Pierini, Dylan S. Rankin, Nhan Tran, Matthew Trahms, Aristeidis Tsaris, Colin Versteeg, Ted W. Way, Dustin Werran, Zhenbin Wu
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. Comput. Softw. Big Sci. 3 (1) (2019)
Michael D. Hildreth, Elizabeth Sexton-Kennedy, Kevin Pedro, Matti Kortelainen
Strategies for Modeling Extreme Luminosities in the CMS Simulation. eScience (2018)