Nhan Tran

97 papers A* 3A 3B 1C 3Misc 2Journal 63Unranked 22
YearRankTypeTitle / Venue / Authors
2026 — conf
PrioriFI: More Informed Fault Injection for Edge Neural Networks.
ASPLOS (2)
Olivia Weng, Andres Meza, Nhan Tran, Ryan Kastner
2026 J jnl
Towards a Self-Driving Trigger at the LHC: Adaptive Response in Real Time.
CoRR
Shaghayegh Emami, Cecilia Tosciri, Giovanna Salvi, Zixin Ding, Yuxin Chen, Abhijith Gandrakota, Christian Herwig, David W. Miller, Jennifer Ngadiuba, Nhan Tran
2025 J jnl
AI Benchmark Democratization and Carpentry.
CoRR
Gregor von Laszewski, Wesley Brewer, Jeyan Thiyagalingam, Juri Papay, Armstrong Foundjem, Piotr Luszczek, Murali Emani, Shirley V. Moore, Vijay Janapa Reddi, Matthew D. Sinclair, Sebastian Lobentanzer, Sujata S. Goswami, Benjamin Hawks, Marco Colombo, Nhan Tran, Christine R. Kirkpatrick, Abdulkareem Alsudais, Gregg Barrett, Tianhao Li, Kirsten N. Morehouse, Shivaram Venkataraman, Rutwik Jain, Kartik Mathur, Victor Lu, Tejinder Singh, Khojasteh Z. Mirza, Kongtao Chen, Sasidhar Kunapuli, Gavin Farrell, Renato Umeton, Geoffrey C. Fox
2025 J jnl
An MLCommons Scientific Benchmarks Ontology.
CoRR
Benjamin Hawks, Gregor von Laszewski, Matthew D. Sinclair, Marco Colombo, Shivaram Venkataraman, Rutwik Jain, Yiwei Jiang, Nhan Tran, Geoffrey C. Fox
2025 J jnl
End-to-end workflow for machine learning-based qubit readout with QICK and hls4ml.
CoRR
Giuseppe Di Guglielmo, Botao Du, Javier Campos, Alexandra Boltasseva, Akash V. Dixit, Farah Fahim, Zhaxylyk Kudyshev, Santiago Lopez, Ruichao Ma, Gabriel N. Perdue, Nhan Tran, Omer Yesilyurt, Daniel Bowring
2025 A conf
Greater than the Sum of its LUTs: Scaling Up LUT-based Neural Networks with AmigoLUT.
FPGA
Olivia Weng, Marta Andronic, Danial Zuberi, Jiaqing Chen, Caleb Geniesse, George A. Constantinides, Nhan Tran, Nicholas J. Fraser, Javier Mauricio Duarte, Ryan Kastner
2025 J jnl
Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing.
CoRR
Tommaso Baldi, Javier Campos, Olivia Weng, Caleb Geniesse, Nhan Tran, Ryan Kastner, Alessandro Biondi
2025 J jnl
Neural Architecture Codesign for Fast Physics Applications.
CoRR
Jason Weitz, Dmitri Demler, Luke McDermott, Nhan Tran, Javier M. Duarte
2025 J jnl
Neural architecture codesign for fast physics applications.
Mach. Learn. Sci. Technol.
Jason Weitz, Dmitri Demler, Luke McDermott, Nhan Tran, Javier M. Duarte
2025 — conf
Onboarding Process from Power-Up to Motion Detection Using ESP32-EYE: A Quick and Comprehensive Approach.
IUKM (1)
Tho Nguyen, Long Le, Binh Nguyen, Trung Nguyen, Nhan Tran, Thien Pham, Tho Quan
2025 J jnl
Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning.
CoRR
Khayrul Islam, Ryan F. Forelli, Jianzhong Han, Deven Bhadane, Jian Huang, Joshua C. Agar, Nhan Tran, Seda Ogrenci, Yaling Liu
2025 — conf
Real-Time Monitoring and Anomaly Detection in Server Lab Environments Using ESP32 DevKit and VAE-Bi-LSTM Hybrid Model: A Case Study at HUFLIT University, Ho Chi Minh City.
IUKM (1)
Trong Le, Long Le, Nhan Tran, Tho Nguyen, Binh Nguyen, Trung Nguyen, Thien Pham, Tho Quan
2025 J jnl
Surrogate Neural Architecture Codesign Package (SNAC-Pack).
CoRR
Jason Weitz, Dmitri Demler, Benjamin Hawks, Nhan Tran, Javier M. Duarte
2025 J jnl
Track reconstruction as a service for collider physics.
CoRR
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, Kevin Pedro, Nhan Tran
2025 J jnl
hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware.
CoRR
Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun, Jovan Mitrevski, Nicolò Ghielmetti, Enrico Lupi, Dimitrios Danopoulos, Vladimir Loncar, Javier M. Duarte, David Burnette, Lauri Laatu, Stylianos Tzelepis, Konstantinos Axiotis, Quentin Berthet, Haoyan Wang, Paul White, Suleyman Demirsoy, Marco Colombo, Thea Aarrestad, Sioni Summers, Maurizio Pierini, Giuseppe Di Guglielmo, Jennifer Ngadiuba, Javier Campos, Benjamin Hawks, Abhijith Gandrakota, Farah Fahim, Nhan Tran, George A. Constantinides, Zhiqiang Que, Wayne Luk, Alexander D. Tapper, Duc Hoang, Noah Paladino, Philip C. Harris, Bo-Cheng Lai, Manuel Blanco Valentin, Ryan F. Forelli, Seda Ogrenci, Lino Gerlach, Rian Flynn, Mia Liu, Daniel Diaz, Elham E Khoda, Melissa Quinnan, Russell Solares, Santosh Parajuli, Mark S. Neubauer, Christian Herwig, Ho Fung Tsoi, Dylan S. Rankin, Shih-Chieh Hsu, Scott Hauck
2025 A conf
wa-hls4ml and lui-gnn: A Benchmark and GNN based Surrogate Model for hls4ml Resource and Latency Estimation.
FPGA
Benjamin Hawks, Dennis Plotnikov, Nhan Tran, Karla Tame-Narvaez, Mohammad Mehdi Rahimifar, Hamza Ezzaoui Rahali, Audrey C. Therrien, Giuseppe Di Guglielmo, Javier Duarte, Vladimir Loncar
2025 J jnl
wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation.
CoRR
Benjamin Hawks, Jason Weitz, Dmitri Demler, Karla Tame-Narvaez, Dennis Plotnikov, Mohammad Mehdi Rahimifar, Hamza Ezzaoui Rahali, Audrey C. Therrien, Donovan Sproule, Elham E Khoda, Keegan A. Smith, Russell Marroquin, Giuseppe Di Guglielmo, Nhan Tran, Javier M. Duarte, Vladimir Loncar
2024 J jnl
Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications.
CoRR
Olivia Weng, Alexander Redding, Nhan Tran, Javier Mauricio Duarte, Ryan Kastner
2024 J jnl
Corrigendum: Applications and techniques for fast machine learning in science.
Frontiers Big Data
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
2024 J jnl
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs.
ACM Trans. Reconfigurable Technol. Syst.
Javier Campos, Jovan Mitrevski, Nhan Tran, Zhen Dong, Amir Gholaminejad, Michael W. Mahoney, Javier M. Duarte
2024 Misc conf
Reliable edge machine learning hardware for scientific applications.
VTS
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
2024 J jnl
Reliable edge machine learning hardware for scientific applications.
CoRR
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
2024 J jnl
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning.
CoRR
Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
2024 J jnl
Robust anomaly detection for particle physics using multi-background representation learning.
Mach. Learn. Sci. Technol.
Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
2024 J jnl
Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning.
Mach. Learn. Sci. Technol.
Jieun Yoo, Jennet Dickinson, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Douglas Berry, Manuel Blanco Valentin, Karri DiPetrillo, Farah Fahim, Lindsey Gray, James Hirschauer, Shruti R. Kulkarni, Ron Lipton, Petar Maksimovic, Corrinne Mills, Mark S. Neubauer, Benjamin Parpillon, Gauri Pradhan, Chinar Syal, Nhan Tran, Dahai Wen, Aaron Young
2023 C conf
A 3D Implementation of Convolutional Neural Network for Fast Inference.
ISCAS
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
2023 J jnl
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing.
CoRR
Tejin Cai, Kenneth Herner, Tingjun Yang, Michael Wang, Maria Acosta Flechas, Philip C. Harris, Burt Holzman, Kevin Pedro, Nhan Tran
2023 J jnl
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing.
Comput. Softw. Big Sci.
Tejin Cai, Kenneth Herner, Tingjun Yang, Michael Wang, Maria Acosta Flechas, Philip C. Harris, Burt Holzman, Kevin Pedro, Nhan Tran
2023 J jnl
Best of Both Worlds? Combining Different Forms of Mixed Reality Deictic Gestures.
ACM Trans. Hum. Robot Interact.
Landon Brown, Jared Hamilton, Zhao Han, Albert Phan, Thao Phung, Eric Hansen, Nhan Tran, Tom Williams
2023 J jnl
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e.
CoRR
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
2023 J jnl
Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC.
CoRR
Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez
2023 J jnl
Differentiable Earth mover's distance for data compression at the high-luminosity LHC.
Mach. Learn. Sci. Technol.
Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez
2023 J jnl
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs and ASICs.
CoRR
Javier Campos, Zhen Dong, Javier M. Duarte, Amir Gholami, Michael W. Mahoney, Jovan Mitrevski, Nhan Tran
2023 J jnl
Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak.
CoRR
Yumou Wei, Ryan F. Forelli, Chris Hansen, Jeffrey P. Levesque, Nhan Tran, Joshua C. Agar, Giuseppe Di Guglielmo, Michael E. Mauel, Gerald A. Navratil
2023 J jnl
Neural Architecture Codesign for Fast Bragg Peak Analysis.
CoRR
Luke McDermott, Jason Weitz, Dmitri Demler, Daniel Cummings, Nhan Tran, Javier M. Duarte
2023 — conf
Now Look Here! Đownarrow Mixed Reality Improves Robot Communication Without Cognitive Overload.
HCI (17)
Nhan Tran, Trevor Grant, Thao Phung, Leanne M. Hirshfield, Christopher D. Wickens, Tom Williams
2023 — conf
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments.
ICONS
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
2023 J jnl
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments.
CoRR
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
2023 A* conf
Structural Re-weighting Improves Graph Domain Adaptation.
ICML
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
2023 J jnl
Structural Re-weighting Improves Graph Domain Adaptation.
CoRR
Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
2022 J jnl
Applications and Techniques for Fast Machine Learning in Science.
Frontiers Big Data
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
2022 J jnl
FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning.
CoRR
Javier M. Duarte, Nhan Tran, Benjamin Hawks, Christian Herwig, Jules Muhizi, Shvetank Prakash, Vijay Janapa Reddi
2022 J jnl
Neural network accelerator for quantum control.
CoRR
David Xu, A. Baris Özgüler, Giuseppe Di Guglielmo, Nhan Tran, Gabriel N. Perdue, Luca P. Carloni, Farah Fahim
2022 J jnl
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark.
CoRR
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
2022 J jnl
Physics Community Needs, Tools, and Resources for Machine Learning.
CoRR
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
2022 J jnl
QONNX: Representing Arbitrary-Precision Quantized Neural Networks.
CoRR
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
2021 J jnl
A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC.
CoRR
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
2021 J jnl
Applications and Techniques for Fast Machine Learning in Science.
CoRR
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
2021 J jnl
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml.
Mach. Learn. Sci. Technol.
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
2021 J jnl
Fast convolutional neural networks on FPGAs with hls4ml.
CoRR
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
2021 J jnl
Fast convolutional neural networks on FPGAs with hls4ml.
Mach. Learn. Sci. Technol.
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
2021 J jnl
GPU coprocessors as a service for deep learning inference in high energy physics.
Mach. Learn. Sci. Technol.
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
2021 — conf
Get This!? Mixed Reality Improves Robot Communication Regardless of Mental Workload.
HRI (Companion)
Nhan Tran, Trevor Grant, Thao Phung, Leanne M. Hirshfield, Christopher D. Wickens, Tom Williams
2021 — conf
MLPerf Tiny Benchmark.
NeurIPS Datasets and Benchmarks
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
2021 J jnl
MLPerf Tiny Benchmark.
CoRR
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
2021 J jnl
Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference.
Frontiers Artif. Intell.
Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
2021 J jnl
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference.
CoRR
Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
2021 B conf
Robot-Generated Mixed Reality Gestures Improve Human-Robot Interaction.
ICSR
Nhan Tran, Trevor Grant, Thao Phung, Leanne M. Hirshfield, Christopher D. Wickens, Tom Williams
2021 A* conf
What's The Point?: Tradeoffs Between Effectiveness and Social Perception When Using Mixed Reality to Enhance Gesturally Limited Robots.
HRI
Jared Hamilton, Thao Phung, Nhan Tran, Tom Williams
2021 J jnl
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices.
CoRR
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 Ogrenci 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
2020 Misc conf
AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters.
FCCM
Naif Tarafdar, Giuseppe Di Guglielmo, Philip C. Harris, Jeffrey D. Krupa, Vladimir Loncar, Dylan S. Rankin, Nhan Tran, Zhenbin Wu, Qianfeng Shen, Paul Chow
2020 J jnl
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs.
CoRR
Aneesh Heintz, Vesal Razavimaleki, Javier M. Duarte, Gage DeZoort, Isobel Ojalvo, Savannah Thais, Markus Atkinson, Mark S. 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
2020 — conf
Adapting Mixed Reality Robot Communication to Mental Workload.
HRI (Companion)
Nhan Tran
2020 J jnl
Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML.
CoRR
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
2020 J jnl
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics.
CoRR
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
2020 J jnl
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics.
Frontiers Big Data
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
2020 — conf
FPGAs-as-a-Service Toolkit (FaaST).
H2RC@SC
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
2020 J jnl
FPGAs-as-a-Service Toolkit (FaaST).
CoRR
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
2020 J jnl
Fast inference of Boosted Decision Trees in FPGAs for particle physics.
CoRR
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
2020 J jnl
GPU coprocessors as a service for deep learning inference in high energy physics.
CoRR
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
2020 J jnl
GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments.
Frontiers Big Data
Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip C. Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey D. Krupa, Kevin Pedro, Nhan Tran
2020 J jnl
GPU-accelerated machine learning inference as a service for computing in neutrino experiments.
CoRR
Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip C. Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey D. Krupa, Kevin Pedro, Nhan Tran
2020 — conf
Using Augmented Reality to Better Study Human-Robot Interaction.
HCI (10)
Tom Williams, Leanne M. Hirshfield, Nhan Tran, Trevor Grant, Nicholas Woodward
2019 J jnl
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era.
CoRR
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 L. 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
2019 J jnl
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing.
Comput. Softw. Big Sci.
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
2019 A conf
Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications.
FPGA
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
2019 J jnl
Improving Long Handwritten Text Line Recognition with Convolutional Multi-way Associative Memory.
CoRR
Duc Nguyen, Nhan Tran, Hung Le
2019 — conf
Investigating the Potential Effectiveness of Allocentric Mixed Reality Deictic Gesture.
HCI (10)
Tom Williams, Matthew Bussing, Sebastian Cabrol, Ian Lau, Elizabeth Boyle, Nhan Tran
2019 A* conf
Mixed Reality Deictic Gesture for Multi-Modal Robot Communication.
HRI
Tom Williams, Matthew Bussing, Sebastian Cabrol, Elizabeth Boyle, Nhan Tran
2019 J jnl
Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan".
CoRR
James F. Amundson, James Annis, Camille Avestruz, D. Bowring, João Caldeira, Giuseppe Cerati, Chihway L. Chang, Scott Dodelson, D. Elvira, A. Farahi, Krzysztof L. 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, Alexander Scheinker, Panagiotis Spentzouris, J. St. John, Nhan Tran, Shubhendu Trivedi, Laura Trouille, W. L. K. Wu, C. R. Bom
2018 — conf
Augmented, Mixed, and Virtual Reality Enabling of Robot Deixis.
HCI (9)
Tom Williams, Nhan Tran, Josh Rands, Neil T. Dantam
2018 J jnl
Fast inference of deep neural networks in FPGAs for particle physics.
CoRR
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
2017 — conf
A content addressable memory with multi-Vdd scheme for low power tunable operation.
MWSCAS
Siddhartha Joshi, Dawei Li, Seda Ogrenci Memik, Grzegorz Deptuch, James Hoff, Sergo Jindariani, Tiehui Liu, Jamieson Olsen, Nhan Tran
2017 J jnl
Applications of potential theoretic mother bodies in Electrostatics.
CoRR
Nhan Tran
2017 J jnl
Big Data in HEP: A comprehensive use case study.
CoRR
Oliver Gutsche, Matteo Cremonesi, Peter Elmer, Bo Jayatilaka, Jim Kowalkowski, Jim Pivarski, Saba Sehrish, Cristina Mantilla Suarez, Alexey Svyatkovskiy, Nhan Tran
2017 — conf
Computational Public Safety: The Evolution to Public Safety Research.
NBiS
Nhan Tran, Muthana Zouri, Alexander Ferworn
2015 C conf
A methodology for power characterization of associative memories.
ICCD
Dawei Li, Siddhartha Joshi, Seda Ogrenci Memik, James Hoff, Sergo Jindariani, Tiehui Liu, Jamieson Olsen, Nhan Tran
2014 J jnl
A Complete 256-Electrode Retinal Prosthesis Chip.
IEEE J. Solid State Circuits
Nhan Tran, Shun Bai, Jiawei Yang, Hosung Chun, Omid Kavehei, Yuanyuan Yang, Vijay Muktamath, David C. Ng, Hamish Meffin, Mark E. Halpern, Efstratios Skafidas
2013 — conf
A charge-balanced 4-wire interface for the interconnections of biomedical implants.
BioCAS
Jiawei Yang, Shun Bai, Nhan Tran, Hosung Chun, Omid Kavehei, Yuanyuan Yang, Efstratios Skafidas, Mark E. Halpern, David C. Ng, Vijay Muktamath
2013 C conf
A flexible biphasic pulse generating and accurate charge balancing stimulator with a 1μW neural recording amplifier.
ISCAS
Hosung Chun, Omid Kavehei, Nhan Tran, Stan Skafidas
2012 — conf
A precise charge balancing and compliance voltage monitoring stimulator front-end for 1024-electrodes retinal prosthesis.
EMBC
Hosung Chun, Nhan Tran, Yuanyuan Yang, Omid Kavehei, Shun Bai, Stan Skafidas
2012 — conf
Crosstalk current measurements using multi-electrode arrays in saline.
EMBC
Nhan Tran, Mark E. Halpern, Shun Bai, Efstratios Skafidas
2011 — conf
A prototype 64-electrode stimulator in 65 nm CMOS process towards a high density epi-retinal prosthesis.
EMBC
Nhan Tran, Efstratios Skafidas, Jiawei Yang, Shun Bai, Meng Fu, David C. Ng, Mark E. Halpern, Iven M. Y. Mareels
2008 — conf
Modeling privacy compromise: visibility of individuals via DRM and RFID in ubiquitous computing.
SpringSim
Nhan Tran, Vijay Somers
2007 — conf
WiFi repeater deployment for improved communication in confined-space urban disaster search.
SoSE
Alexander Ferworn, Nhan Tran, James Tran, Gerry Zarnett, Farrokh Janabi-Sharifi
2004 — conf
A knowledge based approach for representing and reasoning about signaling networks.
ISMB/ECCB (Supplement of Bioinformatics)
Chitta Baral, Karen Chancellor, Tran Hoai Nam, Nhan Tran, Anna M. Joy, Michael E. Berens
2003 — conf
Representing and reasoning about signal networks: an illustration using NF\kappaB dependent signaling pathways.
CSB
Chitta Baral, Karen Chancellor, Tran Hoai Nam, Nhan Tran