- Ph.D., Carnegie Mellon University
- S.M., Massachusetts Institute of Technology
- S.B., Massachusetts Institute of Technology
James Aspnes' research emphasizes the use of randomization to solve difficult core problems in the theory of distributed algorithms. His recent work has concentrated on tools for managing large-scale loosely structured systems as found in peer-to-peer networks and wireless sensor networks. These tools include novel distributed data structures supporting efficient range queries over large data sets scattered across many machines, new models of distributed computation that capture the limited resources of individual nodes in sensor systems, and mechanisms for providing security and fault-tolerance in large-scale systems with no restrictions on the arrival of new and possibly malevolent participants. His interests also include related problems in biology, economics, and learning theory.
Professor Aspnes is a member of the editorial board for Algorithmica, has served as program committee chair for the PODC 2005 and DCOSS 2007 conferences, and has served on numerous conference program committees. He is a recipient of the Dylan Hixon Prize for Teaching Excellence in the Natural Sciences.
- Learning a circuit by injecting values, with Dana Angluin, Jiang Chen, and Yinghua Wu. Thirty-Eighth Annual ACM Symposium on Theory of Computing , May 2006, pp. 584-593.
- Computation in networks of passively mobile finite-state sensors, with Dana Angluin, Zoë Diamadi, Michael J. Fischer, and René Peralta. Distributed Computing 18(4):235-253, March 2006. (PODC 2004 special issue).
- Skip graphs, with Gauri Shah. Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, January 2003, pp. 384–393.