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Sonia Buckley (Fed)

My research at NIST has spanned from integrated and quantum photonics to neuromorphic computing and hardware for AI. I am interested in the development of next generation computing and networking technologies, which will involve heterogeneous and application-specific hardware. In particular, I am developing some of the measurement and benchmarking techniques and services needed for these technologies become commercially viable. On the quantum side, I work on the quantum radiometry project, developing a single photon detector calibration service at NIST. We are also working to develop the next generation of single photon detector measurement tools, applicable to waveguide-coupled single photon detectors on photonic integrated circuits. On the AI side, I am working on general techniques for training emergent hardware for AI. As part of this project, I am involved in a community-driven effort to benchmark next-generation neuromorphic technologies.


  • National Research Council Research Associateship Program (RAP) Award - 2015
  • Ross N. Tucker Memorial Scholarship of the Electronics Materials Symposium - 2013
  • National Science Foundation Graduate Fellowship - 2009
  • Stanford Graduate Fellowship - 2009


NeuroBench: advancing neuromorphic computing through collaborative, fair and representative benchmarking

Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sonia Buckley, Sander Bohte, Younes Bouhadjar, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Daram, Mike Davies, Yigit Demirag, Jason K. Eshraghian, Jeremy Forest, Steve Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddarth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos Michmizos, Dylan Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayca Ozcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Sun Pao-Sheng, Melika Payvand, Christian-Gernot Pehle, Mihai Alexandru Petrovici, Cristoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens Schaefer, Andre van Schaik, Johannes Schemmel, Catherine Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Terrence Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig Vineyard, Bernard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddy
The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles

Photonic Online Learning: A Perspective

Sonia Buckley, Alexander Tait, Adam McCaughan, Bhavin Shastri
Neuromorphic systems promise to solve certain problems faster and with higher energy efficiency than traditional computing, by using the physics of the devices

Single Photon Detectors and Metrology

Sonia Buckley, Michelle Stephens, John H. Lehman
For quantum applications, it is important to generate quantum states of light and detect them with extremely high efficiency. For future applications, it also

Demonstration of Superconducting Optoelectronic Single-Photon Synapses

Saeed Khan, Bryce Primavera, Jeff Chiles, Adam McCaughan, Sonia Buckley, Alexander Tait, Adriana Lita, John Biesecker, Anna Fox, David Olaya, Richard Mirin, Sae Woo Nam, Jeff Shainline
Superconducting optoelectronic hardware is being explored as a path towards artificial spiking neural networks with unprecedented scales of complexity and

Patents (2018-Present)

System And Mathod For Parameter Multiplexed Gradient Descent

NIST Inventors
Adam McCaughan , Sonia Buckley and Andrew Dienstfrey
Embodiments of the present invention relate to systems and model-free methods for perturbing neural network hardware parameters and measure the neural network response that are implemented natively within the neural network hardware and without requiring a knowledge of the internal structure of the

Neuromimetic Circuit

NIST Inventors
Jeff Shainline and Sonia Buckley
Optoelectronic neural networks comprise a system of interconnected processing units (neurons) interconnected by integrated photonic waveguides. The processing units receive photonic signals from other units. Each unit sums the received signals on a waveguide-integrated photon detector, and when the
Line drawing of the thermal impedance amplifier

Thermal Impedance Amplifier

NIST Inventors
Adam McCaughan , Varun Verma and Sonia Buckley
A thermal impedance amplifier includes: a resistive layer including: a resistance member; a first electrode in electrical communication with the resistance member; and a second electrode in electrical communication with the resistance member; a switch layer opposing the resistive layer and including
Created June 1, 2019, Updated June 20, 2023