Summary
Yingcong Tan is a researcher and operations-research engineer with nine years of experience bridging machine learning and optimization, currently based in Canada. He holds a PhD in Industrial Engineering from Concordia University and has pursued postdoctoral work at Concordia and the University of Toronto on inverse optimization, Bayesian optimization, QUBO modeling, and complex vehicle routing. From 2023–2025 he applied these research strengths in industry as a Senior Product Developer at IBS Software and is now a researcher at China Three Gorges Corporation. Yingcong’s work blends theoretical algorithm development with applied transportation and logistics problems—examples include last-mile routing prediction, pickup-and-delivery with transfer scheduling, and airplane service design for remote northern communities. He has published and developed novel gradient and bi-level optimization methods, and his projects often combine active learning with inverse optimization to learn decision models from (near-)optimal solutions. Colleagues describe him as someone who consistently turns rigorous academic ideas into practical tools for real-world decision-making.
9 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Industrial Engineering, 4.08/4.3, Doctor of Philosophy - PhD, Industrial Engineering, 4.08/4.3 at Concordia University
Bachelor of Applied Science - BASc, Engineering Science, Bachelor of Applied Science - BASc, Engineering Science at University of Toronto
French, English, Chinese