I'm currently serving as the Software Team Lead for the Humanoid Robotics Club at Purdue University, where we are embarking on an ambitious four-year project to develop and send a humanoid robot to space. This first year, our focus is on constructing and perfecting the robot's legs, laying the groundwork for its mobility and stability in zero-gravity environments. As we progress, our team will integrate advanced robotics, AI, and systems engineering to achieve our goal of space exploration with humanoid robots. Follow our journey as we push the boundaries of robotics and space technology.

In my role as the Controls, ROS, and Robotics Lead for the Autonomous Boat Project, a competitive initiative for the navy, I had the opportunity to drive the development and integration of advanced control systems for a 14-foot autonomous vessel. Tasked with navigating a series of complex objectives, the boat was equipped with dual RGBD cameras and a sophisticated neural network designed for precise task objective detection. My leadership involved orchestrating the implementation of MAVROS and ArduPilot with ROS2 to manage the boat's controls seamlessly, integrating an electric outboard motor paired with a linear actuator for refined steering and propulsion capabilities. This technical orchestration was pivotal in ensuring the vessel's responsiveness and agility, essential for the dynamic conditions of the competition.The project's ambitious goals included following a pre-determined GPS mission plan, executing a slalom course, conducting a rescue operation for an overboard "person," deploying a LoRaWAN sensor, and safely returning to base. Each objective required meticulous planning, rigorous testing, and continuous optimization to meet the precise standards demanded by the competition's guidelines. My role entailed not only the technical development of the boat's control systems but also ensuring these systems worked in harmony to execute the multifaceted mission objectives efficiently. Through this project, we pushed the boundaries of autonomous maritime technology, showcasing the potential of ROS2 in orchestrating complex, real-world robotic applications and setting a new benchmark for autonomous naval engineering.

As an Undergraduate Teaching Assistant for the ECET 279 course on advanced embedded devices, I had the privilege of deepening my expertise and sharing my knowledge on the intricacies of working with Atmel AVR microcontrollers, specifically in Embedded C. This course covered a comprehensive range of topics, including the setup of timers, PWM, UART communication, and serial communications protocols like SPI and I2C. It also delved into stepper and PID DC motor control, reading analog voltages using an ADC, and managing functions with interrupts. A significant part of the coursework involved storing and retrieving data from EEPROM after power cycles, as well as controlling 7-segment and LCD displays using the Atmel ATmega 2560 chip, all programmed using Atmel's Microchip Studio. My exceptional performance in this class led to my appointment as a Teaching Assistant, where I guided students through the application of these concepts in their lab work. The culmination of the course was a final project that integrated all these techniques to operate a 3D-printed crane, which moved a basket to specific positions based on a password entered through the terminal. This experience not only solidified my technical skills but also honed my ability to mentor and lead others in complex engineering applications.

"Cloud Swarm Robotics" integrates ROS 2 Humble with digital twin technology and Docker to orchestrate a network of mobile robots for environmental mapping and task allocation. Utilizing Lidar and Realsense cameras, the system accurately maps environments and localizes robots using SLAM Toolbox and Apriltags. This facilitates precise task execution and 3D environmental scanning through RTAB-Map, enhancing the creation of a digital twin for simulation and planning.Central to the project is Docker, offering a scalable solution for software deployment across the swarm. Each robot, equipped with sensors and a Raspberry Pi, connects via a wireless network to a central server that manages Docker container deployment. This setup ensures streamlined software management, robustness, and system scalability.Digital twins simulate real-world conditions for advanced task planning and safety assessments. By replicating the physical environment in a digital platform, the project optimizes task distribution and ensures operational safety, using Unity3D for sensor data visualization.This research demonstrates the potential of combining cloud computing, digital twins, and containerization for enhancing swarm robotics, highlighting advancements in autonomous system management, task efficiency, and safety.

Played a pivotal role in facilitating students' understanding of the theoretical and practical aspects of transmitting information wirelessly from one location to another. Assisted in delivering lectures, conducting hands-on lab sessions, and providing guidance on signal analysis, modulation techniques, transmitters, receivers, low noise amplifiers, and RF frequency spectrum filters.

Spearheaded the successful completion of a challenging race, leading a group of motivated students through the entire process. Role honed leadership and organizational skills, efficiently coordinated team members, facilitated building and maintenance of the go-kart, made quick, well-informed decisions under pressure, strategized pit stops, and managed on-the-spot adjustments.