ATTN: Neal Young, 202WVH
360 Huntington Avenue
Boston, MA 02115
- Lagrangian-relaxation algorithms for large-scale linear programming
- Online algorithms for caching and data management
- Approximation algorithms for NP-hard problems.
- PhD in Computer Science, Princeton University
- BA in Computer Science and Mathematics, Cornell University
Neal Young is a teaching professor in the Khoury College of Computer Sciences at Northeastern University. Outside of Boston, Young teaches computer science at The University of California, Riverside, where he’s been a faculty member since 2004. From 1999 to 2004, he worked at Akamai Technologies for five years, where he designed, coded, and helped deploy a Lagrangian-relaxation-based algorithm to dynamically assign end-users to servers to; respect capacity constraints, maximize end-user experience, and reduce bandwidth costs by millions of dollars. Between 1995 and 1999, Young was an assistant professor at Dartmouth College and was a postdoctoral fellow at AT&T Bell Labs (Mathematical Foundations of Computing), Cornell ORIE, and the University of Maryland (UMIACS).
Where is your hometown?
West Lafayette, Indiana
What is your research focus?
My research focuses on approximation algorithms for combinatorial optimization, including Lagrangian-relaxation algorithms for large-scale linear programming, online algorithms for caching and data management, and approximation algorithms for NP-hard problems.