About

Hi. I’m Ryan Tolsma. I love technical challenges and problem solving, and am particularly interested in pure mathematics and its applications in physics and machine learning. I enjoy applying the powerful tools of theory towards modelling and solving real world problems. At Stanford, I performed research in Stanford’s Iliad Lab focusing on developing better algorithms for multi-agent reinforcement learning and dealing with non-stationary environments. In my past, I’ve worked as a quant researcher for HFT, founded and sold a small B2B SaaS compliance startup, performed research in fintech and health consulting, and worked on post-training at a consumer AI startup. During my free time, I enjoy playing poker and board games with friends, reading and learning about how the world works, climbing, sailing, and anime. My party fun facts are that I don’t have a high school diploma and used to play competitive Pokemon.

I have a passion for teaching and decomposing complex concepts into intuitive digestible components. My personal beliefs are that strong foundations in theory have compounded returns over time and vastly accelerate and simplify the process of learning new subjects. My current goals primarily center on intensive learning and establishing expertise across a variety of technical fields.

Please feel free to reach out to me via email if you any questions or inquiries, especially about any of my posts!