Art meets AI algorithms | Colombia News


What was your professional path to become an industrial engineer and professor?

I started as a quantitative analyst on Wall Street instead of doing a postdoc. Years later, I became a hedge fund manager and used pattern recognition and statistical signal processing techniques to spot mispricings and statistical arbitrage. I have always been interested in teaching; I started tutoring when I was 13 and taught until college, in some cases as an extracurricular activity, just because I loved it.

From the beginning of my career, I have loved working with data and I love data mining. My thesis supervisor always said: “let the data do the talking, the models are based on the data”. Throughout my years in industry, before joining Columbia as a full-time professor, I worked on real-world applications of mathematical equations and conducted research with academics in many disciplines. I like to bring industry and academia together and bridge the gap.

Any advice for anyone pursuing a career in engineering?

Always ask questions. Decision-making is data-driven, so work with data and leverage data. If you’re not a programmer, become one!

What is the best part of teaching at Columbia?

Being challenged by smart students, being asked questions I had never thought of, and watching the excitement on students’ faces every time they see and learn something new. I like to teach through visualization as much as possible, and I take that very seriously.

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