7 papers
Does Latent Context Help? A Controlled Evaluation of Inverse Reinforcement Learning in Arctic Shipping
Vaishnav Vaidheeswaran, Dilith Jayakody, Biruk Ambaw +3
Artificial Intelligence (AI)-assisted navigation can help Arctic shipping adapt to rapidly changing sea-ice conditions, but reliable deployment requires reward models that are inte…
Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling
Parth Doshi, Priyanka Aravindan, Vaishnav Vaidheeswaran +2
Deep learning models for scientific spatio-temporal downscaling often minimize reconstruction error while failing to preserve physically meaningful multi-scale structure. For sea s…
MoCo-AIS: A Contrastive Learning Framework for Similarity Computation of Vessel Trajectories
Ruixin Song, Md Mahbub Alam, Zahra Sadeghi +3
Trajectory similarity is a fundamental task in analyzing mobility patterns, essential for applications such as route pattern extraction, mobility prediction, and anomaly detection.…
Goal-Conditioned Reinforcement Learning for Data-Driven Maritime Navigation
Vaishnav Vaidheeswaran, Dilith Jayakody, Samruddhi Mulay +3
Routing vessels through narrow and dynamic waterways is challenging due to changing environmental conditions and operational constraints. Existing vessel-routing studies typically…
Multi-vessel Interaction-Aware Trajectory Prediction and Collision Risk Assessment
Md Mahbub Alam, Jose F. Rodrigues-Jr, Gabriel Spadon
Accurate vessel trajectory prediction is essential for enhancing situational awareness and preventing collisions. Still, existing data-driven models are constrained mainly to singl…
Modeling Maritime Transportation Behavior Using AIS Trajectories and Markovian Processes in the Gulf of St. Lawrence
Gabriel Spadon, Ruixin Song, Vaishnav Vaidheeswaran +3
Maritime transportation is central to the global economy, and analyzing its large-scale behavioral data is critical for operational planning, environmental stewardship, and governa…