• Conducted research on Small Language Models to design a Customer Support Chatbot for the company website.
• Leveraged C# and .NET Framework to design and implement scalable, high-performance backend systems,
delivering robust and efficient software solutions.
• Optimized and horizontally scaled a back-end service from start to finish, erasing bottlenecks and achieving
performance improvements of 80% .
• Implemented and optimized SQL queries using non-clustered indexing to streamline Gantt data handling and
improved scroll and loading times by 34%.
• Designed and implemented data caching, asynchronous tasking and parallelization strategies to improve
overall product performance by 37%, and Gantt load times by 70%
• Leveraged GPU acceleration and pioneered the transition from GDI to WPF rendering, significantly
enhancing application performance and visual quality while setting a new standard for the product

• Developed and optimized a Kalman Filter Machine Learning rocket trajectory prediction algorithm, which can
predict the flight path of the rocket in the event of transmission loss by analyzing historical NMEA messages,
exponentially improving the chance of reconnection as well as predicting a landing zone.
• Designed and implemented a GUI to display real-time and predicted trajectory data, streamlining
ground-station operations for enhanced decision-making.
• Engineered a two-axis trajectory tracking radar array, integrating it with ground-station software and the trajectory
prediction algorithm to autonomously adjust it’s orientation and optimize real-time communication with the
rocket during dynamic flight scenarios

• Engineered real-time object detection and optical flow algorithms using Python, OpenCV, YOLO, and
Lucas-Kanade, leveraging domain-specific datasets and model pruning to improve detection accuracy, reduce
computational overhead, and enhance drone object avoidance in dynamic environments.
• Leveraged LiDAR tracking cameras to capture precise telemetry data for detailed flight analysis.
• Key member of the F1Tenth Autonomous Racing Team, leading VESC tuning and LiDAR integration.
• Enhanced proficiency in Python, C, and C++ through hands-on development, algorithm optimization, and
performance tuning, with applications in embedded systems such as drones and autonomous race cars.
• Conducted research and developed a prototype for a crop detection computer vision algorithm designed for
drones, enabling the measurement of crop yields and providing inventory management solutions.
• Refined research skills through rigorous experimentation, data analysis, and algorithm refinement in a
research-driven lab environment

• Developed a facial recognition algorithm using MediaPipe and Python, mapping over 600 facial feature points to
ensure highly secure access control.
• Designed a pose estimation algorithm that predicts face orientation to verify 3D facial presence and prevent
photo-based unauthorized access.
• Developed and 3D-printed a sleek, modern smart door lock prototype with seamless hardware and software integration.
• Presented the project at multiple design competitions, showcasing innovation and technical proficiency.