Trinity College in Connecticut is a highly regarded liberal arts college known for its interdisciplinary programs and civic engagement. It emphasizes intellectual exploration and global citizenship. We collaborate with Trinity College on data science, generative modeling, style-based GAN training, as well as disentangled representation learning and scalable AI for education and research applications.

Posts

Toward Intelligent and Efficient Optical Networks: Performance Modeling, Co-existence, and Field Trials

Optical transmission networks require intelligent traffic adaptation and efficient spectrum usage. We present scalable machine learning (ML) methods for network performance modeling, andfield trials of distributed fiber sensing and classic optical network traffic coexistence.

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.

Inline Fiber Type Identification using In-Service Brillouin Optical Time Domain Analysis

We proposed the use of BOTDA as a monitoring tool to identify fiber types present in deployed hybrid-span fiber cables, to assist in network planning, setting optimal launch powers, and selecting correct modulation formats.

Modeling the Input Power Dependency in Transceiver BER-ONSR for QoT Estimation

We propose a method to estimate the input power dependency of the transceiver BER-OSNR characteristic. Experiments using commercial transceivers show that estimation error in Q-factor is less than 0.2 dB.

Multi-Span Optical Power Spectrum Prediction using ML-based EDFA Models and Cascaded Learning

We implement a cascaded learning framework using component-level EDFA models for optical power spectrum prediction in multi-span networks, achieving a mean absolute error of 0.17 dB across 6 spans and 12 EDFAs with only one-shot measurement.