Purnanand Elango
Research Scientist at Mitsubishi Electric Research Laboratories
Cambridge, Massachusetts, United States
Summary
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Senior🎓
Top SchoolPurnanand Elango is a research scientist specializing in optimization-based trajectory generation, sensing, and feedback control for space vehicles and robotic platforms, with a decade of experience spanning academic and industrial research. He holds a PhD in Aerospace Engineering from the University of Washington and dual degrees (BTech/MTech) from IIT Madras, where he graduated with a standout 9.73/10 GPA. Purnanand has combined deep academic work as a research assistant with hands-on internships and research roles at Mitsubishi Electric Research Laboratories and Amazon, now continuing at MERL in Cambridge. His work bridges theoretical control and practical implementation, often focusing on algorithms that enable reliable autonomous navigation in complex environments. Notably, he transitions smoothly between long-term PhD research and rapid industrial prototyping, making him effective at moving ideas from simulation to real systems.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Aerospace, Aeronautical and Astronautical Engineering, Doctor of Philosophy - PhD, Aerospace, Aeronautical and Astronautical Engineering at University of WashingtonIndian Institute of Technology Madras
Github Skills (11)
convex-optimization9
trajectory-optimization9
trajectory-generation8
constraint-satisfaction8
non-convex7
motion-planning7
algorithm7
numerical-optimization7
robotics7
optimization6
autonomous-driving5
Programming languages (5)
Github contributions (5)
UW-ACL/pipg-demo
Aug 2020 - Jun 2022
Demonstration of the PIPG algorithm for trajectory optimization
Contributions:40 commits, 40 pushes, 1 branch in 1 year 10 months
trajectory-optimizationconvex-optimizationmpc-controlfirst-order-methodsoptimization-algorithms
purnanandelango/trajopt-util
Jan 2023 - Feb 2023
Utilities for Numerical Trajectory Optimization
Contributions:82 commits, 1 PR, 217 pushes in 26 days
trajectory-optimizationconvex-optimizationnumerical-optimization
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