NEC Laboratories America

Optical Communications & Computing

From forward-looking theoretical studies to cutting-edge experiments to world- and industry-first technology field trials, we deliver globally recognized innovation in optical communications and computing that looks into the future and translates it into present reality.

From the Internet backbone to the data center floor, optics and photonics form the foundation of modern communications and computing infrastructure. As global data demand accelerates, optical communications and computing technologies must evolve together to keep pace. Our department advances the science of high-capacity optical transmission alongside emerging photonic computing architectures, delivering research that spans theoretical modeling, laboratory experimentation, and real-world field trials.

The advent of AI-centric data networking combined with growing demand for globally connected, always-on networks is pushing optical communication systems toward new limits. Our researchers develop coherent optical transmission techniques, agile digital signal processing (DSP) approaches, and software-defined optical networking architectures, including optical line system telemetry, network digital twins, and automation through agentic AI. These innovations expand transmission capacity and extend network reach in traditional fiber links and satellite optical communications, while giving operators the flexibility to support dynamic networking environments such as AI-compute infrastructures and augmented reality (AR)/virtual reality (VR) applications.

Beyond transmission, we explore how photonic and optical computing principles can address the growing energy and latency demands of AI workloads. Our work in high-speed optical signal processing and RF spectral sensing implemented on photonic integrated chips, together with forward-looking research in photonic AI, extends the reach of optical technology from the network core into computing architectures themselves.

Optical communications and computing will play a pivotal role in shaping the future of connectivity, data processing, and AI infrastructure across industries.

Join Us

Are you interested in joining us? We are looking for the next generation of thought leaders in optical communications and computing to join our research team. If you are pursuing a career in this field, visit our careers page to learn more and apply for our available positions.

Summer 2026 Internship Applications are now closed.

Exciting internship opportunities for Summer 2027 will be available on our internship page this fall.  We are looking for students pursuing advanced degrees in Computer Science and Electrical Engineering. Internships are typically 3 months long during the summer. The benefits of working for us include the opportunity to quickly join a project team applying cutting-edge technology to industry-leading concepts.

To apply for a Summer Internship, visit our Internship page.

Learn More

Want to learn more about our optical communications and computing department? Meet our team of experts, check out our blog posts, or read our latest publications.

Featured Optical Communications & Computing Research Projects

Latest Optical Communications & Computing News

High-Sensitivity Forward-Transmission Vibration Sensing for Real-World Event Detection in Urban Fiber Networks

Publication Date: 4/3/2025 Event: OFC 2025 Reference: Th4C.2: 1-3, 2025 Authors: Jian Fang, NEC Laboratories America, Inc.; Ming-Fang Huang, NEC Laboratories America, Inc.; Scott Kotrla, Verizon; Tiejun J. Xia, Verizon; Glenn A. Wellbrock, Verizon; Jeffrey A Mundt, Verizon; Ting Wang, NEC Laboratories

Multi-Event Distributed Forwarding Sensing with Dual-Sensor Adaptive Beamforming

We present adaptive beamforming techniques to forward-transmission multi-event vibration sensing in environments with interference and jamming. Experimental validation over 100km fiber demonstrates significant improvements on signal reconstruction, noise reduction, and interference rejection from other

Multi-span OSNR and GSNR Prediction using Cascaded Learning

We implement a cascaded learning framework leveraging three different EDFA and fiber component models for OSNR and GSNR prediction, achieving MAEs of 0.20 and 0.14 dBover a 5-span network under dynamic channel loading.

Optical Line System Physical Digital Model Calibration using a Differential Algorithm

A differential algorithm is proposed to calibrate the physical digital model of an optical line system from scratch at the commissioning phase, using minimal measurements and maximizing signal and OSNR estimation accuracy.

QoT Digital Twin for Bridging Physical Layer Knowledge Gaps in Multi-Domain Networks

We propose building a spectrally resolved QoT Digital Twin for optical network domains where models and telemetry are unavailable, by probing transmission on a singlespectral slot, using GNPy, and demonstrating accurate experimental results.

Scalable Machine Learning Models for Optical Transmission System Management

Optical transmission systems require accurate modeling and performance estimation for autonomous adaption and reconfiguration. We present efficient and scalable machine learning (ML) methods for modeling optical networks at component- and network-level with minimizeddata collection.