Multimode Fiber Encryption
Studying noise-resilient optical encryption pipelines built on multimode fiber speckles, spatial encoding, and physically grounded decoding strategies.
Ruibo Lan
Optical engineering research for intelligent photonic systems.
I am Ruibo Lan, an optical engineering researcher working on multimode fiber photonics, orbital angular momentum based information encoding, diffractive neural networks, and AI-driven modeling for nonlinear optical systems.
- Research interests: OAM, MMF, D2NN, and AI for optics
- Current work spans optical encryption, intelligent decoding, and nonlinear modeling
- Three first-author journal papers published in 2025
Current Research
Physics-aware learning for optical communication and computation
Research
Selected directions
Orbital Angular Momentum
Using OAM beams as high-dimensional carriers for image encoding, information multiplexing, and secure optical transmission.
Diffractive Neural Networks
Building optical inference systems that embed intelligence into propagation itself, with an emphasis on low-latency and all-optical decoding.
Deep learning models for fast prediction of complex nonlinear dynamics in Kerr fiber cavities and related photonic systems.
Hands-on experience with spatial optical systems, phase pattern generation, SLM control, and end-to-end optimization across hardware and software.
Preview
Detailed pages
Curriculum Vitae
An overview of education, research interests, technical skills, awards, and academic experience.
Open CV pagePublications
A selected list of publications with research highlights, first-author role, and direct DOI links.
Open publications pageResearch Vision
What drives my work
My research combines optical physics, computational modeling, and machine learning to build photonic systems that are more secure, interpretable, and robust in realistic environments.