2013 - Fellow of the American Mathematical Society
2009 - SIAM Fellow For contributions to discrete mathematics and algorithms.
Prasad Tetali mainly investigates Discrete mathematics, Combinatorics, Algorithm, Spectral gap and Pure mathematics. His work carried out in the field of Discrete mathematics brings together such families of science as Randomized rounding and Graph. His Combinatorics research integrates issues from Upper and lower bounds and Simple.
His studies in Algorithm integrate themes in fields like Logarithm, Markov chain mixing time, Isoperimetric inequality and Markov chain Monte Carlo. His Spectral gap research incorporates elements of Projection, Poincaré conjecture, Symmetric group and Constant. Prasad Tetali combines subjects such as Poincaré inequality, Mathematical analysis, Expander graph and Stationary distribution with his study of Pure mathematics.
Prasad Tetali mainly focuses on Combinatorics, Discrete mathematics, Upper and lower bounds, Random graph and Graph. Prasad Tetali regularly links together related areas like Mixing in his Combinatorics studies. Discrete mathematics and Mathematical proof are commonly linked in his work.
His Upper and lower bounds study combines topics in areas such as Bounded function, Eigenvalues and eigenvectors and Laplace operator. Within one scientific family, Prasad Tetali focuses on topics pertaining to Distributed algorithm under Time complexity, and may sometimes address concerns connected to Spanning tree. The various areas that he examines in his Hypergraph study include Randomized rounding and Vertex cover.
The scientist’s investigation covers issues in Combinatorics, Discrete mathematics, Upper and lower bounds, Graph and Ricci curvature. As part of his studies on Combinatorics, he often connects relevant areas like Eigenvalues and eigenvectors. The Discrete mathematics study combines topics in areas such as Mixing and Metric.
His study in Upper and lower bounds is interdisciplinary in nature, drawing from both Riemannian manifold, Rate of convergence and Wasserstein metric. His Complete bipartite graph study in the realm of Graph interacts with subjects such as Multipartite. He interconnects Martingale, Mathematical analysis and Ising model in the investigation of issues within Pure mathematics.
His primary scientific interests are in Combinatorics, Pure mathematics, Ricci curvature, Symmetric group and Concentration of measure. His Combinatorics research includes elements of Discrete mathematics and Upper and lower bounds. His Discrete mathematics research is multidisciplinary, incorporating perspectives in Lattice path, Sequence and Mixing.
Many of his research projects under Pure mathematics are closely connected to Particle system with Particle system, tying the diverse disciplines of science together. His Symmetric group research incorporates themes from Isoperimetric inequality, Cayley graph, Abelian group and Spectral gap. His studies examine the connections between Concentration of measure and genetics, as well as such issues in Real line, with regards to Applied mathematics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Random walks and the effective resistance of networks
Prasad Tetali.
Journal of Theoretical Probability (1991)
Mathematical Aspects of Mixing Times in Markov Chains
R. Montenegro;P. Tetali.
(2006)
Collisions among random walks on a graph
Don Coppersmith;Prasad Tetali;Peter Winkler.
SIAM Journal on Discrete Mathematics (1993)
Approximating Min Sum Set Cover
Uriel Feige;Prasad Tetali.
Algorithmica (2004)
Simple Markov-chain algorithms for generating bipartite graphs and tournaments
Ravi Kannan;Prasad Tetali;Santosh Vempala.
Random Structures and Algorithms (1999)
Simple deterministic approximation algorithms for counting matchings
Mohsen Bayati;David Gamarnik;Dimitriy Katz;Chandra Nair.
symposium on the theory of computing (2007)
Modified Logarithmic Sobolev Inequalities in Discrete Settings
Sergey G. Bobkov;Prasad Tetali.
Journal of Theoretical Probability (2006)
Analyzing Glauber dynamics by comparison of Markov chains
Dana Randall;Prasad Tetali.
Journal of Mathematical Physics (2000)
Torpid mixing of some Monte Carlo Markov chain algorithms in statistical physics
C. Borgs;J.T. Chayes;A. Frieze;Jeong Han Kim.
foundations of computer science (1999)
Information Inequalities for Joint Distributions, With Interpretations and Applications
Mokshay Madiman;Prasad Tetali.
IEEE Transactions on Information Theory (2010)
Georgia Institute of Technology
Georgia Institute of Technology
Microsoft (United States)
Microsoft (United States)
University of Houston
University of Minnesota
MIT
University of Copenhagen
Weizmann Institute of Science
Princeton University
Profile was last updated on December 6th, 2021.
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