Software Engineer with experience in computer vision, embedded systems, and full-stack application development. Has worked with Python, OpenCV, Flask, Socket.IO, Flutter, Dart, Node.js, MongoDB, C, FreeRTOS, and I2C acro…
Software Engineer with experience in computer vision, embedded systems, and full-stack application development. Has worked with Python, OpenCV, Flask, Socket.IO, Flutter, Dart, Node.js, MongoDB, C, FreeRTOS, and I2C across automotive, financial literacy, and firmware projects.
<p>Developed an end-to-end multi-camera computer vision system for international automotive deployments, integrating real-time weld validation and PLC signaling to prevent welding outside approved regions on rotating subframes.<br>
Built a parallel Python inference pipeline using multiprocessing and shared memory for 4 synchronized camera streams, increasing throughput and reducing frame-processing latency by 40%.<br>
Engineered segmentation-based validation logic with temporal and spatial consistency checks to reduce false detections by 85% and improve robustness under operator and rotating-part occlusions.<br>
Engineered custom algorithms using Python and OpenCV for weld-region validation, pixel-connectivity, motion tracking, and adaptive exposure switching, improving detection reliability under active welding.<br>
Annotated and analyzed 10,000+ production images for a YOLO pose-estimation model, reducing false positives by 30% through dataset refinement, label validation, and augmentation for varying lighting and welding conditions.<br>
Built a real-time Flask and Socket.IO operator interface to visualize camera feeds, system state, and weld-validation results for production monitoring and debugging.</p>
<p>Developed a financial literacy app using Flutter and Dart, implementing login, registration, email verification, password recovery, and responsive UI across multiple devices.<br>
Built and integrated a backend system using Node.js and MongoDB, handling user registration, authentication, and data storage.<br>
Debugged and optimized app performance using Flutter DevTools, identifying and resolving bugs and rendering issues to enhance overall app responsiveness.</p>
<p>Developed a C-based driver for the LM75BD sensor, utilizing I2C protocols and bit-banging to ensure accurate satellite telemetry.<br>
Integrated the driver into FreeRTOS, using task prioritization and mutex mechanisms to optimize real-time sensor data processing.<br>
Applied unit testing and profiling to streamline the driver’s execution, reducing latency by 20%.</p>
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