With over seven years of experience as a quantitative strategist at leading investment banks, including Goldman Sachs, RBC, and Nomura, I have developed and implemented advanced financial models and software tools for trading activities. My expertise lies in the intersection of mathematics, finance, and computer science.
Academic Background I hold a PhD in Complexity Theory, a subfield of Theoretical Computer Science, and two master’s degrees—one in Mathematical Finance and another in Mathematical Logic and Theory of Computation. My academic journey began with a bachelor's degree in Mathematics. I have worked as a researcher and instructor at Yonsei University, one of South Korea's top universities. After returning to Canada, I completed my second master’s degree while teaching at the University of Toronto, one of the world's top institutions. Throughout my research career, I have contributed to the academic community through numerous publications in renowned conferences and journals, which are available on my Google Scholar and DBLP pages.
Teaching & Learning Approach I am passionate about making complex topics accessible through structured, hands-on learning. My courses focus on bridging the gap between theoretical foundations and real-world applications, helping students develop practical skills in finance, artificial intelligence, and quantitative modeling. I strive to simplify complex concepts by breaking them down into smaller components, allowing students to build a strong foundational understanding of the topic.
Beyond Work I love traveling and immersing myself in different cultures. Born in Greece, I’ve lived in Spain for an Erasmus exchange program, pursued my PhD in Canada, and built my academic and professional career across South Korea, Canada, and the UK. These experiences have broadened my worldview and deeply influenced my teaching approach.
