Joshua Agar

According to our database, Joshua Agar authored at least 13 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning.

Khayrul Islam, Ryan F. Forelli, Jianzhong Han, Deven Bhadane, Jian Huang, Joshua C. Agar, Nhan Tran, Seda Ogrenci, Yaling Liu

CoRR, March, 2025

2024

Corrigendum: 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, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Shen Wang, Thomas K. Warburton

Frontiers Big Data, 2024

Making Sense of Metadata Mess: Alignment & Risk Assessment for Diatom Data Use Case.

Kio Polson, Marina Potapova, Uttam Meena, Chad Peiper, Joshua Brown, Joshua Agar, Jane Greenberg

CoRR, 2024

A High Level Synthesis Methodology for Dynamic Monitoring of FPGA ML Accelerators.

Ryan F. Forelli, Rui Shi, Seda Ogrenci, Joshua Agar

Proceedings of the 42nd IEEE VLSI Test Symposium, 2024

Reliable edge machine learning hardware for scientific applications.

Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin

Proceedings of the 42nd IEEE VLSI Test Symposium, 2024

A Wireless Monitoring System to Quantify Indoor-Outdoor Air Pollution in a Building.

John Edrick M. Gador, Lance H. Atienza, John Danielle T. Castor, Nathan Andrei A. Galang, Marc D. Rosales, Percival Magpantay, Julius Rhoan Lustro, Joshua C. Agar, John Jairus D. P. Eslit, Carlo Elpidio Capiral, John Richard E. Hizon

Proceedings of the IEEE Region 10 Conference, 2024

Making Sense of Metadata Mess: Alignment and Risk Assessment for Diatom Data Use Case.

Kio Polson, Marina Potapova, Uttam Meena, Chad Peiper, Joshua Brown, Joshua Agar, Jane Greenberg

Proceedings of the Metadata and Semantic Research - 18th Research Conference, 2024

Data Discovery and Indexing for Semi-Structured Scientific Data.

Kaushik Jagini, Yifan Zhang, Yichen Guo, Julian Goddy, Dale Stansberry, Joshua Agar, Jeff Heflin

Proceedings of the 26th International Conference on Enterprise Information Systems, 2024

2023

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak.

Yumou Wei, Ryan F. Forelli, Chris Hansen, Jeffrey P. Levesque, Nhan Tran, Joshua C. Agar, Giuseppe Di Guglielmo, Michael E. Mauel, Gerald A. Navratil

CoRR, 2023

Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy.

Sergei V. Kalinin, Debangshu Mukherjee, Kevin M. Roccapriore, Ben Blaiszik, Ayana Ghosh, Maxim A. Ziatdinov, Anees Al-Najjar, Christina Doty, Sarah Akers, Nageswara S. V. Rao, Joshua C. Agar, Steven R. Spurgeon

CoRR, 2023

2022

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, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Shen Wang, Thomas K. Warburton

Frontiers Big Data, 2022

2021

Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations.

Shen Wang, Mehdi Nikfar, Joshua C. Agar, Yaling Liu

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, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

CoRR, 2021