Nhan Tran

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 67

Top Topics

Data Compression

Particle Physics

Top Venues

Mach. Learn. Sci. Technol.

Frontiers Big Data

Publications

Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning. CoRR (2024)
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
Reliable edge machine learning hardware for scientific applications. CoRR (2024)
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
Reliable edge machine learning hardware for scientific applications. VTS (2024)
Olivia Weng, Alexander Redding, Nhan Tran, Javier Mauricio Duarte, Ryan Kastner
Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications. CoRR (2024)
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
Corrigendum: Applications and techniques for fast machine learning in science. Frontiers Big Data 6 (2024)
Chenwei Xu, Jerry Yao-Chieh Hu, Aakaash Narayanan, Mattson Thieme, Vladimir Nagaslaev, Mark Austin, Jeremy Arnold, Jose Berlioz, Pierrick Hanlet, Aisha Ibrahim, Dennis Nicklaus, Jovan Mitrevski, Jason Michael St. John, Gauri Pradhan, Andrea Saewert, Kiyomi Seiya, Brian Schupbach, Randy Thurman-Keup, Nhan Tran, Rui Shi, Seda Ogrenci, Alexis Maya-Isabelle Shuping, Kyle J. Hazelwood, Han Liu
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e. CoRR (2023)
Javier Campos, Zhen Dong, Javier M. Duarte, Amir Gholami, Michael W. Mahoney, Jovan Mitrevski, Nhan Tran
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs. CoRR (2023)
Narasinga Rao Miniskar, Pruek Vanna-Iampikul, Aaron R. Young, Sung Kyu Lim, Frank Liu, Jieun Yoo, Corrinne Mills, Nhan Tran, Farah Fahim, Jeffrey S. Vetter
A 3D Implementation of Convolutional Neural Network for Fast Inference. ISCAS (2023)
Nhan Tran, Trevor Grant, Thao Phung, Leanne M. Hirshfield, Christopher D. Wickens, Tom Williams
Now Look Here! Đownarrow Mixed Reality Improves Robot Communication Without Cognitive Overload. HCI (17) (2023)
Shruti R. Kulkarni, Aaron R. Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments. CoRR (2023)
Luke McDermott, Jason Weitz, Dmitri Demler, Daniel Cummings, Nhan Tran, Javier M. Duarte
Neural Architecture Codesign for Fast Bragg Peak Analysis. CoRR (2023)
Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez
Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC. CoRR (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. Comput. Softw. Big Sci. 7 (1) (2023)
Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez
Differentiable Earth mover's distance for data compression at the high-luminosity LHC. Mach. Learn. Sci. Technol. 4 (4) (2023)
Yumou Wei, Ryan F. Forelli, Chris Hansen, Jeffrey P. Levesque, Nhan Tran, Joshua C. Agar, Giuseppe Di Guglielmo, Michael E. Mauel, Gerald A. Navratil
Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak. CoRR (2023)
Landon Brown, Jared Hamilton, Zhao Han, Albert Phan, Thao Phung, Eric Hansen, Nhan Tran, Tom Williams
Best of Both Worlds? Combining Different Forms of Mixed Reality Deictic Gestures. ACM Trans. Hum. Robot Interact. 12 (1) (2023)
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiu Qiang, Pan Li
Structural Re-weighting Improves Graph Domain Adaptation. CoRR (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)
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
Structural Re-weighting Improves Graph Domain Adaptation. ICML (2023)
Shruti R. Kulkarni, Aaron R. Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments. ICONS (2023)
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, Scott Hauck, Javier M. Duarte
QONNX: Representing Arbitrary-Precision Quantized Neural Networks. 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)
Hendrik Borras, Giuseppe Di Guglielmo, Javier M. Duarte, Nicolò Ghielmetti, Benjamin Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. CoRR (2022)
Naif Tarafdar, Giuseppe Di Guglielmo, Philip C. Harris, Jeffrey D. Krupa, Vladimir Loncar, Dylan S. Rankin, Nhan Tran, Zhenbin Wu, Qianfeng Shen, Paul Chow
: An Open Framework for Deploying Machine Learning on Heterogeneous Clusters. ACM Trans. Reconfigurable Technol. Syst. 15 (3) (2022)
David Xu, A. Baris Özgüler, Giuseppe Di Guglielmo, Nhan Tran, Gabriel N. Perdue, Luca P. Carloni, Farah Fahim
Neural network accelerator for quantum control. CoRR (2022)
Javier M. Duarte, Nhan Tran, Benjamin Hawks, Christian Herwig, Jules Muhizi, Shvetank Prakash, Vijay Janapa Reddi
FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning. CoRR (2022)
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
Applications and Techniques for Fast Machine Learning in Science. Frontiers Big Data 5 (2022)
Nhan Tran, Trevor Grant, Thao Phung, Leanne M. Hirshfield, Christopher D. Wickens, Tom Williams
Get This!? Mixed Reality Improves Robot Communication Regardless of Mental Workload. HRI (Companion) (2021)
Colby R. Banbury, Vijay Janapa Reddi, Peter Torelli, Nat Jeffries, Csaba Király, Jeremy Holleman, Pietro Montino, David Kanter, Pete Warden, Danilo Pau, Urmish Thakker, Antonio Torrini, Jay Cordaro, Giuseppe Di Guglielmo, Javier M. Duarte, Honson Tran, Nhan Tran, Wenxu Niu, Xuesong Xu
MLPerf Tiny Benchmark. NeurIPS Datasets and Benchmarks (2021)
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)
Giuseppe Di Guglielmo, Farah Fahim, Christian Herwig, Manuel Blanco Valentin, Javier M. Duarte, Cristian Gingu, Philip C. Harris, James Hirschauer, Martin Kwok, Vladimir Loncar, Yingyi Luo, Llovizna Miranda, Jennifer Ngadiuba, Daniel Noonan, Seda Ogrenci Memik, Maurizio Pierini, Sioni Summers, Nhan Tran
A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC. CoRR (2021)
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, Tomas E. Muller 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 Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng
Applications and Techniques for Fast Machine Learning in Science. CoRR (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)
Colby R. Banbury, Vijay Janapa Reddi, Peter Torelli, Jeremy Holleman, Nat Jeffries, Csaba Király, Pietro Montino, David Kanter, Sebastian Ahmed, Danilo Pau, Urmish Thakker, Antonio Torrini, Pete Warden, Jay Cordaro, Giuseppe Di Guglielmo, Javier M. Duarte, Stephen Gibellini, Videet Parekh, Honson Tran, Nhan Tran, Wenxu Niu, Xuesong Xu
MLPerf Tiny Benchmark. CoRR (2021)
Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference. CoRR (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)
Nhan Tran, Trevor Grant, Thao Phung, Leanne M. Hirshfield, Christopher D. Wickens, Tom Williams
Robot-Generated Mixed Reality Gestures Improve Human-Robot Interaction. ICSR (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)
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, Josiah D. Hester, Yingyi Luo, John Mamish, Seda Orgrenci-Memik, Thea Aarrestad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier M. Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, Zhenbin Wu
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. CoRR (2021)
Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference. Frontiers Artif. Intell. 4 (2021)
Jared Hamilton, Thao Phung, Nhan Tran, Tom Williams
What's The Point?: Tradeoffs Between Effectiveness and Social Perception When Using Mixed Reality to Enhance Gesturally Limited Robots. HRI (2021)
Tom Williams, Leanne M. Hirshfield, Nhan Tran, Trevor Grant, Nicholas Woodward
Using Augmented Reality to Better Study Human-Robot Interaction. HCI (10) (2020)
Sioni Summers, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Duc Hoang, Sergo Jindariani, Edward Kreinar, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Nhan Tran, Zhenbin Wu
Fast inference of Boosted Decision Trees in FPGAs for particle physics. CoRR (2020)
Nhan Tran
Adapting Mixed Reality Robot Communication to Mental Workload. HRI (Companion) (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. 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)
Naif Tarafdar, Giuseppe Di Guglielmo, Philip C. Harris, Jeffrey D. Krupa, Vladimir Loncar, Dylan S. Rankin, Nhan Tran, Zhenbin Wu, Qianfeng Shen, Paul Chow
AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters. FCCM (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)
Aneesh Heintz, Vesal Razavimaleki, Javier M. Duarte, Gage DeZoort, Isobel Ojalvo, Savannah Thais, Markus Atkinson, Mark Neubauer, Lindsey Gray, Sergo Jindariani, Nhan Tran, Philip C. Harris, Dylan S. Rankin, Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Mia Liu, Edward Kreinar, Zhenbin Wu
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs. CoRR (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)
Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Ryan A. Rivera, Sioni Summers, Nhan Tran, Zhenbin Wu
Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. FPGA (2019)
Tom Williams, Matthew Bussing, Sebastian Cabrol, Ian Lau, Elizabeth Boyle, Nhan Tran
Investigating the Potential Effectiveness of Allocentric Mixed Reality Deictic Gesture. HCI (10) (2019)
Tom Williams, Matthew Bussing, Sebastian Cabrol, Elizabeth Boyle, Nhan Tran
Mixed Reality Deictic Gesture for Multi-Modal Robot Communication. HRI (2019)
Brian Nord, Andrew J. Connolly, Jamie Kinney, Jeremy Kubica, Gautaum Narayan, Joshua E. G. Peek, Chad Schafer, Erik J. Tollerud, Camille Avestruz, Gutti Jogesh Babu, Simon Birrer, Douglas Burke, João Caldeira, Douglas A. Caldwell, Joleen K. Carlberg, Yen-Chi Chen, Chuanfei Dong, Eric D. Feigelson, V. Zach Golkhou, Vinay Kashyap, T. S. Li, Thomas Loredo, Luisa Lucie-Smith, Kaisey S. Mandel, J. R. Martínez-Galarza, Adam A. Miller, Priyamvada Natarajan, Michelle Ntampaka, Andy Ptak, David Rapetti, Lior Shamir, Aneta Siemiginowska, Brigitta M. Sipocz, Arfon M. Smith, Nhan Tran, Ricardo Vilalta, Lucianne M. Walkowicz, John ZuHone
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era. CoRR (2019)
Duc Nguyen, Nhan Tran, Hung Le
Improving Long Handwritten Text Line Recognition with Convolutional Multi-way Associative Memory. CoRR (2019)
Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Jennifer Ngadiuba, Maurizio Pierini, Ryan A. Rivera, Nhan Tran, Zhenbin Wu
Fast inference of deep neural networks in FPGAs for particle physics. CoRR (2018)
Tom Williams, Nhan Tran, Josh Rands, Neil T. Dantam
Augmented, Mixed, and Virtual Reality Enabling of Robot Deixis. HCI (9) (2018)
Oliver Gutsche, Matteo Cremonesi, Peter Elmer, Bo Jayatilaka, Jim Kowalkowski, Jim Pivarski, Saba Sehrish, Cristina Mantilla Surez, Alexey Svyatkovskiy, Nhan Tran
Big Data in HEP: A comprehensive use case study. CoRR (2017)
Nhan Tran
Applications of potential theoretic mother bodies in Electrostatics. CoRR (2017)
Nhan Tran, Muthana Zouri, Alexander Ferworn
Computational Public Safety: The Evolution to Public Safety Research. NBiS (2017)
Siddhartha Joshi, Dawei Li, Seda Ogrenci Memik, Grzegorz Deptuch, James Hoff, Sergo Jindariani, Tiehui Liu, Jamieson Olsen, Nhan Tran
A content addressable memory with multi-Vdd scheme for low power tunable operation. MWSCAS (2017)
Dawei Li, Siddhartha Joshi, Seda Ogrenci Memik, James Hoff, Sergo Jindariani, Tiehui Liu, Jamieson Olsen, Nhan Tran
A methodology for power characterization of associative memories. ICCD (2015)
Nhan Tran, Shun Bai, Jiawei Yang, Hosung Chun, Omid Kavehei, Yuanyuan Yang, Vijay Muktamath, David C. Ng, Hamish Meffin, Mark E. Halpern, Efstratios Skafidas
A Complete 256-Electrode Retinal Prosthesis Chip. IEEE J. Solid State Circuits 49 (3) (2014)
Jiawei Yang, Shun Bai, Nhan Tran, Hosung Chun, Omid Kavehei, Yuanyuan Yang, Efstratios Skafidas, Mark E. Halpern, David C. Ng, Vijay Muktamath
A charge-balanced 4-wire interface for the interconnections of biomedical implants. BioCAS (2013)
Hosung Chun, Omid Kavehei, Nhan Tran, Stan Skafidas
A flexible biphasic pulse generating and accurate charge balancing stimulator with a 1μW neural recording amplifier. ISCAS (2013)
Nhan Tran, Mark E. Halpern, Shun Bai, Efstratios Skafidas
Crosstalk current measurements using multi-electrode arrays in saline. EMBC (2012)
Hosung Chun, Nhan Tran, Yuanyuan Yang, Omid Kavehei, Shun Bai, Stan Skafidas
A precise charge balancing and compliance voltage monitoring stimulator front-end for 1024-electrodes retinal prosthesis. EMBC (2012)
Nhan Tran, Efstratios Skafidas, Jiawei Yang, Shun Bai, Meng Fu, David C. Ng, Mark E. Halpern, Iven M. Y. Mareels
A prototype 64-electrode stimulator in 65 nm CMOS process towards a high density epi-retinal prosthesis. EMBC (2011)
Nhan Tran, Vijay Somers
Modeling privacy compromise: visibility of individuals via DRM and RFID in ubiquitous computing. SpringSim (2008)
Alexander Ferworn, Nhan Tran, James Tran, Gerry Zarnett, Farrokh Janabi-Sharifi
WiFi repeater deployment for improved communication in confined-space urban disaster search. SoSE (2007)
Chitta Baral, Karen Chancellor, Tran Hoai Nam, Nhan Tran, Anna M. Joy, Michael E. Berens
A knowledge based approach for representing and reasoning about signaling networks. ISMB/ECCB (Supplement of Bioinformatics) (2004)
Chitta Baral, Karen Chancellor, Tran Hoai Nam, Nhan Tran
Representing and reasoning about signal networks: an illustration using NF\kappaB dependent signaling pathways. CSB (2003)