Eric Allender

Personal Information

Identity
First Name: Eric
Middle Name:
Last Name: Allender
Title: Professor

Contact Information
Email: ALLENDER@CS.RUTGERS.EDU
Phone: 445-2001 ext 3629
Office Hours: http://www.cs.rutgers.edu/~allender/hours/
Office Location: Hill 442, Busch Campus
Website: http://www.cs.rutgers.edu/~allender/



Biography

Eric Allender is a well-known researcher in the field of computational complexity, and has given numerous plenary addresses internationally at symposia on theoretical computer science.  He received a B.A. from the University of Iowa in 1979, majoring in Computer Science and Theatre, and a Ph.D. from Georgia Tech in 1985.  He has been at Rutgers University since then, serving as department chair from 2006 to 2009.  He is a Fellow of the ACM, and serves on the editorial boards of ACM Transactions on Computation Theory, Computational Complexity, and The Chicago Journal of Theoretical Computer Science.  He has chaired the Conference Committee for the annual IEEE Conference on Computational Complexity, and he serves on the Scientific Board for the Electronic Colloquium on Computational Complexity (ECCC).

 


Institutional Affilation

Departmental Name
SAS - Computer Science
SAS - Mathematics

Allender's appointment is in the Computer Science Department, but he is also a member of the graduate faculty of Mathematics.

Research Interests

Heading
Applied Mathematics
Computer Science and Engineering
Informatics
Mathematics

Computational Complexity Theory is the branch of mathematics that endeavors to show that certain problems are so hard to compute that they are essentially intractable. The study of encryption (encoding information in a secure way, to ensure privacy or to enable electronic commerce) is closely tied up with computational complexity. Allender's research touches on many aspects of complexity theory.

Documents

Curriculum Vitae

Other Documents
No other documents are associated with this profile

Past Projects

(Aresty Summer Science) Research Problems in Computational Complexity Theory Learn more