• Designed an electrical system and software interface and spec electrical components to ensure their earth-space environmental compatibility for the AEGIS, inflatable lunar landing pad, project as a part of the NASA 2024 Big Idea Challenge• Developed a Flutter desktop application in Steam Deck Controller to interface bodycam live capture and control two dimensional gymbals• Integrated WiFi connectivity between Steam Deck and the Live Camera using NetworkManager linux daemon along with UI feedback in the Flutter app, and reduced RTSP stream latency from 5s down to 1s by utilizing Flutter GStreamer plugin• Developed interactive 3D visualization websites using NextJS, Tailwind CSS, ThreeJS, CesiumJS to visualize periodic orbits and spacecrafts trajectory in the Earth-Moon orbit, and establish lunar rights and resources on the Moon surface• Wrote Python scripts to scrape tabular data consisting of computed positions and velocities of an orbiting spacecraft at a specific time of over 200 space missions and 10 periodic orbits within cis-lunar orbit using JPL API• Processed JPL tabular data using Python with Pandas and OpenAI libraries to collect a spacecraft’s trajectory, origin and a summary of its mission, and converted raw string data into JSON format data for ease of use• Hosted websites using AWS Platform, Cloudflare and NGINX, and utilized S3 to store big JSON and image files• Built a planetary marker for the purpose of interacting and labeling/highlighting surfaces on the Moon using CesiumJS• Built a sidebar using TailwindCSS to allow users to create their lunar sites for future lunar mission simulation• Implemented an orientation menu to change 3D orientation view of the cis-lunar orbital environment and the Moon planet• Wrote several GET and POST API routes using TypeScript and ExpressJS to get CRUD operations to MongoDB database

Leading the team that provides electronic instruments and software applications for use in High-Powered Rocketry and Rocket Propulsion. Current active projects involve the development of low-level drivers for some modules such as Global Positioning System, RF Module, and Servo Driver for the custom flight computer, as well as allowing Liquid Propulsion Hot-fire Sequencing by interfacing our custom liquid engine controller with command-line interface and graphical user interface software. This team not only assists avionics needs for SDR organization but also promises to bring more major diversity, especially Electrical Engineering and Computer Systems Engineering, into the Rocketry and Aerospace industry.

Developing Flight Computer Firmware to support the SDR organization's electronics and software for both high-power rockets and research purposes. The projects involve the implementation in of many electronic modules such as Inertia Measurement Unit, Global Positioning System, external memory devices like Flash and SDCard. These units are developed mainly in C/C++, Makefiles, ARM Cortex Microprocessors and controlled through the organization's interface built in Python.

Researching on leveraging Transformers Encoder-Decoder and Large Language Model architectures to create a multimodal text to music generative AI model. Specifically, we are examining our concept performance when text-based AI encoder is merged with music-based AI decoder. This project currently involves the use of many research Python libraries such as Fairseq, FastTransformer, and PyTorch, and will be trained on a dataset with more than 100,000 samples.

• Investigated and predicted air quality for Uganda in the Layer.ai contest• Processed the tabular dataset by filling in missing values, scaling data, converting categorical values, dropping overfitting features, which helped reduce Mean Absolute Error score from 20 to 17• Trained and tuned the neural network to fit the dataset, which improved our score from 17 to 16.69

An Autonomous car that follows traffic rules using PID and ESP32. (Robotraffic Careful Driving Winner 3rd Place 2022)∗ Team leader of our school’s team, where I guided, gave solutions and reviewed team’s codes∗ Developed a self-driving car using a line sensor, a PID control, and the ESP32 microprocessor∗ Used the built-in WIFI module in the ESP32 to send data to Firebase database∗ Developed a web app using JavaScript to control the motor and PID configuration∗ Created a traffic light system that communicates to the self-driving car

This project was made for RMIT Tech Genius Contest 2021Maple is a mobile application that helps students perform better when self-studying.Maple works as a virtual assistant. At first, it is required to enter the user’s current study progress. Once entered, it will tell a user whether he/she performs well or not. If not, it will suggest some practice videos related to certain subjects that the user needs to improve. Furthermore, users can chat with Maple if they need advice or better recommendations, or simply chat to get to know each other more.