Ruixin Song
AI Product Engineer & Co-Founder of GradientX Technology · Vancouver, BC
I work on representation learning, graph learning, and physics-informed AI.
I am currently an AI product engineer and co-founder of GradientX Technology, building FinTorch, an AI financial copilot centred on retrieval-augmented, multi-agent pipelines for personal financial decision support and simulation.
Before that I spent two years as a research assistant with the AISViz and MAPS labs at Dalhousie University, working on spatiotemporal trajectory representation learning and on the data infrastructure behind fifteen years of maritime shipping records. I hold an M.Sc. in Computer Science from Memorial University of Newfoundland, where my thesis used gravity-informed deep learning to forecast marine traffic for invasive-species risk assessment.
My research has appeared in Scientific Reports, Biological Invasions, and IEEE BigData. You can find the full list on the publications page, or download my CV.
news
| Jul 29, 2026 | Our startup GradientX Technology has been accepted into the Innovation UBC incubator and the Venture Founder Program, Cohort 52. |
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selected publications
- arXiv preprintMoCo-AIS: A Contrastive Learning Framework for Similarity Computation of Vessel TrajectoryIn , 2026Under review
- Sci. Rep.Enhancing Global Maritime Traffic Network Forecasting with Gravity-Inspired Deep Learning ModelsScientific Reports, 2024R. Song and G. Spadon contributed equally