Kris Zhang
University of Waterloo (BMath)
Columbia University (MS in Climate)
I’m Kris Zhang, a recent Bachelor of Mathematics graduate from the University of Waterloo, where I studied Math & Business Administration with a Statistics minor. I’m currently moving into the next stage of my academic work as an incoming master’s student at Columbia Climate School, focusing on quantitative climate risk, climate finance, and data-driven modelling. My work sits at the intersection of statistical modelling, machine learning, time-series forecasting, insurance risk, and climate-informed financial decision-making.
Recently, I’ve worked on projects using mortality data, climate signals, and mathematical models to study long-horizon risk, and I’m now especially interested in AI × climate questions — including the environmental and financial implications of data centers, electricity demand, water use, emissions, and infrastructure growth. I enjoy reading quant-finance and climate-finance papers, writing quick research takeaways, and sharing ideas on X. Outside of research, I’m usually snowboarding, playing tennis or golf, watching NBA and F1, or exploring fashion design, fits, and great visual design.
Research Experience
My research sits at the intersection of statistical forecasting, climate risk, and decision-making under changing conditions. I’m especially interested in building models that stay interpretable and useful when data-generating processes shift—whether in mortality risk under warming trends or in optimization theory verified by formal proof systems.
Projects
My projects focus on turning quantitative ideas into working systems—from optimization models that improve real operations to statistical pipelines that test hypotheses on messy, real-world data. I like building end-to-end solutions (data → modeling → evaluation → interpretation) and prioritizing work that is practical, measurable, and decision-relevant.