About

SwetaSubhra Datta is a highly skilled engineer with a passion for technology and a drive to make a real-world impact. Currently pursuing a Masters in Computer Engineering at North Carolina State University, Raleigh, Sweta is always open to working on challenging projects that can make a difference. With a strong background in software engineering, computer vision, and AI algorithms, Sweta has honed her skills in microprocessor architecture and design. Sweta is currently working as an SDE intern for Autopilot-Camera at Tesla where she has contributed significantly to the in-house validation of car camera calibration. She has interfaced laser systems with Raspberry Pi over tcp/ip, implemented windshield color characterization using spectral sensors interfaced with rp2040 microcontroller over i2c, and developed the core engine of Universal Camera Testing platform on rp2040 (Rpi pico-h) interfaced with RPi. Sweta has also acted as a core contributor to the full-stack web development and deployment of an image validation test web app called Retina. Prior to Tesla, Sweta worked as a Graduate Research Student at North Carolina State University where she worked on the remote-control of BenchBot, a voice-controlled robot. She also contributed to the development of novel algorithms for motion and obstruction detection in Camera FOV for the smart bot Qubo at Hero Electronix. Sweta has optimized neural network models based on FaceNet by converting the Protobuf(.pb) models to Flatbuffers (.tflite) that increased parsing speed by 30% for most models. She has also helped in porting python and Matlab codebase to C++ with CMake build systems and integrating into NDK package on Android. Sweta has a Bachelor of Technology in Biotechnology from VIT. Her tech stack includes Python, Web, test, OpenCV, Computer Vision, AI, Kubernetes, Docker, Research Scientist, FaceNet, Azure, Tensorflow, and Neural Networks. Sweta is actively looking for full-time opportunities starting January 2023 and has 2.10 years of relevant experience.