Controls

Towards Online Monitoring and Data-Driven Control: A Study of Segmentation Algorithms for Laser Powder Bed Fusion Processes

An increasing number of laser powder bed fusion machines use off-axis infrared cameras to improve online moni- toring and data-driven control capabilities. However, there is still a severe lack of algorithmic solutions to properly process the …

Robot Control and Mechanism Design Projects

This page contains a collection of projects on robot control and mechanism design that I have worked on throughout my graduate studies at the University of Texas at Austin. The first project is a 3-finger gripper mechanism with centralized actuation …

GAIN Mechanical Engineering Department Award 2021

Awardee of the Mechanical Engineering Department Award for the 2021 Graduate and Industry Networking Event by the University of Texas at Austin for outstanding research.

Predictive Iterative Learning Control

During my Master’s research at the University of Texas at Austin, I focused on enhancing the precision and quality of Selective Laser Sintering (SLS) through advanced data-driven control techniques. My work introduced a Predictive Iterative Learning …

Predictive Iterative Learning Control with Data-Driven Model for Optimal Laser Power in Selective Laser Sintering

Building high quality parts is still a key challenge for Selective Laser Sintering machines today due to a lack of sufficient process control. In order to improve process control, we propose a Predictive Iterative Learning Control (PILC) controller …

Won Sandia National Laboratories Grant

Pitched and secured five-figure funding from Sandia National Labs for a novel laser pre-scan process that enhances part quality in selective laser sintering (3D printing).

Undergraduate Research Scholar

Undergraduate research scholar in Professor Kira Barton's lab at the University of Michigan to study Electrohydrodynamic Jet Printing. Dual-funded by the University of Michigan and RWTH Aachen University.