Ishaan Mehta

Indian Institute of Technology Delhi, Toronto Metropolitan University

Papers

Total Citations

H-Index

About

Ishaan Mehta is a researcher whose work spans robotics programming, optimization, and intelligent systems. His contributions bridge the gap between human-robot interaction and computational problem-solving, making him a notable voice in applied robotics research. Among his most recognized work is his 2016 paper on a teach pendant interface for controlling virtual robots within the Roboanalyzer platform, which has garnered 13 citations. This contribution advanced the accessibility of robot programming by enabling intuitive, interactive trajectory teaching through handheld control units — a development with meaningful implications for industrial automation education and practice. More recently, Mehta turned his attention to multi-objective optimization, publishing a 2022 paper introducing the Pareto Frontier Approximation Network (PA-Net), a novel approach to solving bi-objective instances of the Travelling Salesperson Problem. With 5 citations in a short time, this work demonstrates his growing influence in the intersection of robotics planning, scheduling, and machine learning-driven optimization. Collectively, Mehta's research reflects a consistent commitment to making robotic systems more programmable, efficient, and intelligently optimized — contributions that hold practical relevance for students and professionals working at the frontier of robotics and autonomous systems.