Sanjeev Khanna

Alcatel Lucent (Germany), Mathematical Sciences Research Institute, Oak Ridge National Laboratory

Papers

Total Citations

103

H-Index

About

Sanjeev Khanna is a leading researcher in theoretical computer science, with key contributions spanning algorithms, computational geometry, and robotics. His work is distinguished by deep theoretical insights that address practical challenges, particularly in motion planning and modular systems. Khanna’s foundational paper, "The Angular-Metric Traveling Salesman Problem" (2000, 72 citations), introduced a novel formulation of the TSP that minimizes total direction change—a problem directly motivated by robotics applications—and established its NP-hardness, opening a new avenue for algorithmic study. He has also made significant strides in dynamic graph algorithms, where his work on certificates and lookahead (1995–1998) provided crucial lower bounds explaining why efficient solutions for fundamental directed graph problems like strong connectivity remain elusive. More recently, Khanna has advanced modular robotics through his 2015 paper on embeddability, which introduced a novel graph representation to automatically determine whether one robot design can simulate another. Across his career, Khanna’s research demonstrates a rare ability to bridge abstract theory with tangible, real-world systems, making him a respected figure in both algorithms and robotics communities.