We conduct research on intelligent information processing systems. A major focus is on efficient and robust machine learning. Machine learning systems should efficiently perform their intelligent tasks under resource constraints on computing, storage, communication, and data. Machine learning systems should be robust to physical noise, adversarial examples, and adversarial attackers. We attempt to realize efficient and robust machine learning systems via mathematical tools from coding theory, information theory, and (convex) optimization. We are also researching on coding for memories, energy-efficient computing, and distributed systems.
- Efficient and robust machine learning
- Distributed inference and learning
- Energy-efficient computing and storage
We are looking for graduate students who are interested in machine learning, coding theory, information theory, optimization, and energy-efficient computing. Please contact me with your CV/Resume if you are interested.
Advisor Professor : Kim, Yongjune
Information, Computing, and Intelligence Laboratory Homepage