Art and algorithms at Sotheby's: MIT alumna builds AI to predict auction prices
MIT alumna Kelly Shen '17 uses algorithms at Sotheby's to forecast art prices and manage real-time bidding systems, blending her computer science training with a lifelong passion for drawing.
Shen works in the growing field of art intelligence, building algorithms to predict prices using factors such as buying trends and artists’ popularity. She has also worked on cataloguing and ensuring that real-time systems can handle thousands of potential bidders visiting the auction house’s website.
Outside her work, she serves MIT as a class officer, vice president of the Association of MIT Alumnae, and a volunteer for the MIT Club of New York. A double major in computer science and math, Shen credits lessons from MIT—along with a lifelong passion for drawing—with shaping her career.
Her favorite class was Project Laboratory in Mathematics, where students present creative answers to intricate math puzzles. “The class helped me talk about what I do with different audiences,” she says. Though she appreciates elegant algorithms, she understands when they’re impractical: “You can build a super-sophisticated algorithm, but if it doesn’t bring more audience engagement, it doesn’t really matter.”