Balcan Receives ACM Grace Murray Hopper Award
Maria Florina "Nina" Balcan, an associate professor in the School of Computer Science's Machine Learning and Computer Science Departments, has received the 2019 Association for Computing Machinery (ACM) Grace Murray Hopper Award for her significant innovations in machine learning and minimally supervised learning. This award is given to the outstanding young computer professional of the year and includes a $35,000 prize.
Balcan's research interests include learning theory, machine learning, artificial intelligence, theory of computing, algorithmic economics and algorithmic game theory, and optimization.
The ACM is the world's largest educational and scientific computing society. Its president, Cherri M. Pancake, lauded Balcan for accomplishing so much before age 35. "Although she is still in the early stages of her career, she has already established herself as the world leader in the theory of how AI systems can learn with limited supervision," Pancake said. "More broadly, her work has realigned the foundations of machine learning, and consequently ushered in many new applications that have brought about leapfrog advances in this exciting area of artificial intelligence."
Balcan introduced the first theoretical framework for semi-supervised learning — a technique used to increase training data in machine learning and improve predictive accuracy. Her work advanced the tool and enabled the subsequent work of many other researchers. Balcan has also made significant contributions in the techniques of active learning and clustering.
Balcan received bachelor's and master's degrees from the University of Bucharest in 2000 and 2002, respectively, and earned a Ph.D. in computer science from Carnegie Mellon in 2008. She was honored with a National Science Foundation CAREER Award in 2009, a Microsoft Faculty Fellowship in 2011 and a Sloan Research Fellowship in 2014. She has served as the program committee co-chair for all three of the major machine learning conferences: the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Conference on Learning Theory (COLT).