ProfessorsProfessors of Cornell UniversityMichael Todd

Michael Todd

Cornell University

H-index: 53

North America-United States

About Michael Todd

Michael Todd, With an exceptional h-index of 53 and a recent h-index of 24 (since 2020), a distinguished researcher at Cornell University, specializes in the field of Optimization, convex optimization, semidefinite programming, complexity.

His recent articles reflect a diverse array of research interests and contributions to the field:

An oblivious ellipsoid algorithm for solving a system of (in) feasible linear inequalities

The ellipsoid method redux

A lower bound on the number of iterations of an interior-point algorithm for linear programming

Michael Todd Information

University	Cornell University
Position	Operations Research and Information Engineering
Citations(all)	17061
Citations(since 2020)	3329
Cited By	15922
hIndex(all)	53
hIndex(since 2020)	24
i10Index(all)	131
i10Index(since 2020)	41
Email	Access Email
University Profile Page	Cornell University
Google Scholar	View Google Scholar Profile

Michael Todd Skills & Research Interests

Optimization

convex optimization

semidefinite programming

complexity

Top articles of Michael Todd

Title	Journal	Author(s)	Publication Date
An oblivious ellipsoid algorithm for solving a system of (in) feasible linear inequalities	Mathematics of Operations Research	Jourdain Lamperski Robert M Freund Michael J Todd	2024/2
The ellipsoid method redux	arXiv preprint arXiv:2301.07632	Michael J Todd	2023/1/18
A lower bound on the number of iterations of an interior-point algorithm for linear programming		Michael J Todd	2020/10/7