Summary
Tristan Ballard is a Senior Research Scientist and statistician with nine years of experience building generative and agentic AI for weather, seasonal, and climate forecasting, translating scientific advances into commercial risk products for insurance, finance, and supply chains. His work—published in Science, PNAS, and top ML venues like NeurIPS and ICLR—combines deep learning, probabilistic modeling, and large-scale geospatial processing to produce operational, patented systems that outperform conventional models. He has a track record of productizing research (including an 8x super-resolution wildfire model and a GAN-based climate forecast that beat NASA) and helped scale Sust Global to acquisition before joining Zeus AI to lead multimodal foundation models. Equally at home in Python, PyTorch, and JAX on cloud-scale infrastructure, Tristan brings both rigorous academic training (PhD and MS from Stanford) and hands-on engineering to close the gap between climate science and actionable business insight. An understated but consistent thread in his career is turning complex physical and statistical problems into explainable, deployable solutions that directly reduce real-world risk.
9 years of coding experience
10 years of employment as a software developer
Bachelor of Science (BS) Statistics, Bachelor of Science (BS) Statistics at Duke University
Doctor of Philosophy (Ph.D.) Systems Science, Doctor of Philosophy (Ph.D.) Systems Science at Stanford University