Eric Blow Presents at the IEEE Photonics Conference Singapore on November 10th & 13th

Eric C. Blow will present twice at the IEEE Photonics Conference (IPC 2025) in Singapore on November 10 and November 13, 2025.

He will first deliver an invited talk on behalf of Dr. Giovanni Milione on applying machine learning to distributed acoustic sensing for critical infrastructure monitoring, then return later in the week to share new work on neuromorphic photonics for near-field RF sensing.

We are proud to share that Yuxin Wang of Princeton University, who collaborates with Eric Blow, has been named a Best Student Paper Finalist and will present her pioneering work on scalable photonic neurons for high-speed automatic modulation classification, the first experimental photonic implementation of AMC using a fully functional photonic neural network.

These sessions underscore NEC Labs America’s leadership in combining photonics, AI, and sensing for real-world security and monitoring.

The IEEE Photonics Conference (IPC 2025) will take place 9–13 November 2025 in Singapore, is the flagship event of the IEEE Photonics Society. It will feature plenary sessions, invited talks, panels, and special symposia covering cutting-edge research and applications across the full spectrum of photonics.

IPC 2025 Conference
Eric Blow IPC2025 Monday
Eric Blow IPC2025 Thursday

Agenda

Eric C. Blow, a researcher in our Optical Networking and Sensing Group, will give an invited talk on the behalf of Dr. Giovanni Milione, entitled Machine Learning, Distributed Acoustic Sensing, and Critical Infrastructure Monitoring at the IEEE Photonics Conference (IPC2025) in Singapore, on Monday, 10 November 2025 from 8:30am – 10:00am, Session: MF1.1 and in Venue: Aquarius 2. We review recent advances in the applications of novel machine learning methods to distributed acoustic sensing data for the physical monitoring of critical infrastructure, such as facility perimeters. We highlight classification of intrusion detection events—walk, dig, drive—over km-scale, buried optical fiber with ~90% accuracy. Authors from NEC Labs America: Giovanni Milione, Giacomo Borraccini, Eric C. Blow, Yue-Kai Huang, Shaobo Han, Philip Ji and Ting Wang.

Eric C. Blow, a researcher in our Optical Networking and Sensing Group, will present Neuromorphic Photonics-Enabled Near-Field RF Sensing with Residual Signal Recovery and Classification at the IEEE Photonics Conference (IPC2025) in Singapore, on Thursday, 13 November 2025 from 8:30am – 10:00am, Session: ThC1.3 and in Venue: Leo 3. He will present near-field radio-frequency sensing and residual signal recovery accomplished with combination of silicon photonics and FPGA electronics. Frontend sensing is accomplished via microwave photonic cancellers, while backend signal is achieved via photonic recurrent neural networks and FPGA, enabling high-bandwidth and low-latency classification. Eric C. Blow, NEC Laboratories America, Inc.; Lei Xu, Princeton University; Yusuf Jimoh, Princeton University; Professor Paul R. Prucnal, Princeton University; Ting Wang, NEC Laboratories America, Inc.

Yuxin Wang, Princeton University, who collaborates with Eric Blow, has been named a Best Student Paper Finalist and will present her paper for Scalable Photonic Neurons for High-Speed Automatic Modulation Classification at the IEEE Photonics Conference (IPC2025) in Singapore, on Thursday, 13 November 2025 from 8:30am – 10:00am, Session: ThC1.4 Venue: Leo 3. This is the first experimental photonic implementation of Automatic modulation classification (AMC), achieved through a fully functional photonic neural network (PNN) built from novel scalable microring resonators that co-integrate electro-optic modulation and weighting, representing the first system-level deployment of such photonic neurons in PNN. Authors: Yuxin Wang, Princeton University; Weipeng Zhang, Princeton University; Eric C. Blow, NEC Labs America, Princeton University; Joshua C. Lederman, Princeton University; Professor Bhavin J. Shastri, Queen’s University and Professor Paul R. Prucnal, Princeton University.

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Eric Blow of NEC Labs will address how machine-learning methods applied to distributed acoustic-sensing data can monitor facility perimeters and detect intrusion via walk, dig, or drive events over buried optical fibre—for example achieving ~90% classification accuracy. Later in the week he will explore neuromorphic photonic RF sensing combining silicon photonics with FPGA-based recurrent neural networks, and his intern Yuxin Wang will present a finalist paper on scalable photonic neurons for automatic modulation classification.
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