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

Template Matching Method with Distributed Acoustic Sensing Data and Simulation Data

We propose a new method to detect acoustic signals by matching distributed acoustic sensing data with simulation. In the simulation of the dynamic strain on an optical fiber, the optical fiber layouts and the gauge length are properly incorporated. We apply the proposed method to the acoustic-source

Distributed Fiber Optic Sensors Placement for Infrastructure-as-a-Sensor

Recently, the distributed fiber optic sensing (DFOS) techniques have advanced rapidly. There emerges various types of DFOS sensors that can monitor physical parameters such as temperature, strain, and vibration. With these DFOS sensors deployed, the telecom networks are capable of offering additional

Time Series Prediction and Classification using Silicon Photonic Neuron with Self-Connection

We experimentally demonstrated the real-time operation of a photonic neuron with a self-connection, a prerequisite for integrated recurrent neural networks (RNNs). After studying two applications, we propose a photonics-assisted platform for time series prediction and classification.

Learning Transferable Reward for Query Object Localization with Policy Adaptation

We propose a reinforcement learning-based approach to query object localization, for which an agent is trained to localize objects of interest specified by a small exemplary set. We learn a transferable reward signal formulated using the exemplary set by ordinal metric learning. Our proposed method enables

Provable Adaptation Across Multiway Domains via Representation Learning

This paper studies zero-shot domain adaptation where each domain is indexed on a multi-dimensional array, and we only have data from a small subset of domains. Our goal is to produce predictors that perform well on unseen domains. We propose a model which consists of a domain-invariant latent representation

Codebook Design for Composite Beamforming in Next-generation mmWave Systems

In pursuance of the unused spectrum in higher frequencies, millimeter wave (mmWave) bands have a pivotal role. However, the high path-loss and poor scattering associated with mmWave communications highlight the necessity of employing effective beamforming techniques. In order to efficiently search for