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 in quantitative trading at a proprietary trading firm, software engineering at a small startup, and quantitative research in Fintech and Consulting. During my free time, I enjoy playing poker and board games with friends, reading textbooks, and watching TV.

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 at if you any questions or inquiries, especially about any of my posts!