Research

Imagine yourself glancing at a busy street for a few moments, then trying to sketch the scene you saw from memory. Most people could draw the rough positions of the major objects like cars, people, and crosswalks, but almost no one can draw every detail with pixel-perfect accuracy. The same is true for most modern computer vision algorithms: They are fantastic at capturing high-level details of a scene, but they lose fine-grained details as they process information.

Audio deepfakes have had a recent bout of bad press after an artificial intelligence-generated robocall purporting to be the voice of Joe Biden hit up New Hampshire residents, urging them not to cast ballots. Meanwhile, spear-phishers — phishing campaigns that target a specific person or group, especially using information known to be of interest to the target — go fishing for money, and actors aim to preserve their audio likeness.

MIT professor of electrical engineering and computer science (EECS) and Computer Science and Artificial Intelligence Laboratory (CSAIL) member Vinod Vaikuntanathan was one of four outstanding undergraduate teachers and mentors have been named MacVicar Faculty Fellows. He joins professor of EECS Karl Berggren, professor of political science Andrea Campbell, and associate professor of music Emily Richmond Pollock in receiving the honor.

If a robot traveling to a destination has just two possible paths, it needs only to compare the routes’ travel time and probability of success. But if the robot is traversing a complex environment with many possible paths, choosing the best route amid so much uncertainty can quickly become an intractable problem.