Skip to main content
Chiran Binnu Cherian

Chiran Binnu Cherian

Ph.D. Student in Aerospace Engineering

Iowa State University · Ames, Iowa

cbckbc@iastate.edu

About

Researching estimation, control, and intelligent engineering systems.

I am a Ph.D. student in Aerospace Engineering at Iowa State University. My research spans spacecraft navigation and estimation, nonlinear and higher-order filtering, stochastic optimal control, covariance steering, and machine-learning applications in engineering systems.

My current work explores estimation methods that move beyond conventional linear measurement updates, including quadratic and higher-order polynomial filtering approaches. I also work on risk-sensitive optimal control and covariance steering, while maintaining an interdisciplinary interest in data-driven modeling of engineering materials.

Education

Academic background

01

Ph.D. in Aerospace Engineering

Iowa State University

Ames, Iowa

GPA: 3.52 / 4.00

May 2026 – Present

02

M.S. in Aerospace Engineering, Thesis

Iowa State University

Ames, Iowa

GPA: 3.52 / 4.00

January 2024 – May 2026

03

B.Tech. in Mechanical Engineering

Vellore Institute of Technology

Vellore, India

GPA: 7.94 / 10.00

July 2019 – May 2023

Technical Skills

Methods and tools

Programming & Scientific Computing

Python MATLAB Mathematica

Estimation & Filtering

Kalman Filtering EKF UKF QEKF QUKF Polynomial Filtering Sigma-Point Methods Conjugate Unscented Transformation Monte Carlo Analysis

Optimal Control & Optimization

Stochastic Optimal Control Covariance Steering Nonlinear Optimization Trajectory Optimization

Astrodynamics & Navigation

Clohessy-Wiltshire Dynamics CR3BP Lambert Problem Orbit Determination Spacecraft Relative Navigation

Engineering & Simulation

ABAQUS ANSYS Fluent SolidWorks Autodesk Fusion 360 OpenRocket

Computing Platforms

Google Colab Jetstream2

Looking Ahead

Building across estimation, control, and autonomy

I am interested in developing rigorous computational methods for estimation and control that can operate under nonlinear dynamics, uncertainty, and non-Gaussian environments, with particular interest in aerospace and autonomous systems.