Experience

My journey at Applied Materials began as a Software Engineering Intern in summer 2024, where I worked on real-time setpoint generator modules. By optimizing the underlying system architecture and abstractions, I reduced compiled binary sizes significantly while preserving core functionality—improvements deployed across 100+ semiconductor manufacturing tools worldwide.

This experience paved the way for my return as a full-time Software Engineer in July 2025 within the Metal Deposition Products team. Working on Endura PVD chambers and Opta CMP setups, I now focus on high-performance C++ development, real-time control algorithms, RTOS throughput scheduling, and lock-free dynamic resource arbitration for mission-critical semiconductor manufacturing systems.

During my graduate studies at TAMU, I worked in the Autonomous Systems Lab. My research focused on heuristic path planning of autonomous non-holonomic agents in the presence of dynamic obstacles, formulated as a Mixed Integer Linear Programming (MILP) problem.

I created an intuitive interface for the solution using matplotlib animations in Python. It was challenging at first, but correlating mathematical solving methods with geometrical solutions in path-planning definitely helped me grow as a roboticist.

Before arriving for my Master's, I was a Software Engineering Intern at Analog Devices India. ADI was working on a Time-of-Flight sensor, and I built a simulation for my team using ROS Noetic and Gazebo of a 4-wheel skid-steer drive that streamed sensor data via C++ scripts over ROStopics. The package was added to the main codebase, presented at global ADI GTC 2023, and demonstrated live at ROSCON India 2023.

Having my simulation displayed at one of the biggest meetups of ROS enjoyers was a wonderful feeling. Additionally, I helped port the software stack to ROS 2 and optimized image message transmission latency by 67% using C++ and OpenCV.

I was an undergraduate research fellow at Ontario Tech University under Dr. Scott Nokleby in the Mechatronic and Robotic Systems Lab through the MITACS fellowship. The project prompt was to work on an autonomous wheelchair for children with disabilities like cerebral palsy.

I worked with Intel D435i depth cameras for slope detection (implementing a moving-average filter for 98% accuracy), RRT* global path planning, and a Proportional-Derivative local controller tested on a TurtleBot3 Burger prototype.

In my 2nd year of college, I got the opportunity to work at AEREO on path-planning for Unmanned Aerial Vehicles and automated testing procedures. I built a Software-In-Loop (SITL) testbench on top of the ArduPilot flight-stack that integrated with Ground Control Software using TCP/UDP network protocols.

During my undergraduate degree, I led the automation team at Project MANAS for AUVSI SUAS 2022 and a driverless car for the Mahindra Rise Prize Challenge. I got hands-on with sensor modules and protocols like I2C, UART, SPI, and CAN, and worked extensively on the lateral controller using a modified Stanley algorithm with feedforward for lane centering.

I was part of Team Luna, representing India among the top 13 teams internationally as semi-finalists for the Mohamed Bin Zayed International Robotics Challenge. I worked on Forward and Inverse Kinematics for a 6-axis robotic arm mounted on an autonomous surface vessel.