Skip to Main Content
College Home Page
E C E Home Page

Affiliate Events

Professors & Pizza: Bridging Hardware and Algorithms: Machine Learning for Next-Generation Quantum Sensors


  Add to Google Calendar
Date:  Fri, March 27, 2026
Time:  12:00pm - 1:00pm
Location:  Holmes Hall 244
Speaker:  Dr. Bo-Han Wu, University of Hawaiʻi at Mānoa

Hosted by the University of Hawaiʻi at Mānoa College of Engineering

Please register at: https://forms.gle/zSUBr5CnVCebBEMRA

ECE Graduate Students: This will count towards your seminar credit.

Abstract:

Quantum technologies, including sensing, communication, and computing, are reshaping modern science by exploiting nonclassical resources such as coherence, entanglement, and squeezing. Despite significant progress, their advancement remains limited by the lack of system-level co-optimization that connects physical hardware and algorithmic design. Conventionally, quantum hardware and information processing have been developed independently, which reduces robustness against noise and resource inefficiency.

Machine learning (ML) provides a transformative pathway toward physics-informed co-design, enabling real-time adaptive optimization of complex optical and quantum systems. By embedding the physical principles into learning architectures, ML can enhance signal extraction, suppress noise, and dynamically tune device performance directly at the physical layer. This talk reviews three key directions in quantum photonics: quantum radar, quantum repeaters, and cluster-state generation. I will then present my recent work on the Microring Perceptron (MiRP) and Bidirectional Nonlinear Optical Tomography (BNOT), classical optical systems that leverage machine learning for noise-robust signal processing and unbiased device characterization. Looking ahead, extending these ML-driven frameworks into quantum optical domains will enable the discovery of new design principles, integration strategies, and optimization methods that advance the development of scalable and deployable quantum infrastructures..

Biography:

- Ph.D. in Physics at University of Arizona (2022).

- In 2023, he joined the Massachusetts Institute of Technology (MIT) as a postdoctoral researcher, where he pioneered the Microring Perceptron (MiRP) sensor, a quantum sensor system empowered by machine learning optimization.


Return to Affiliate Events