Aditya Sarkar

I’m an ECE graduate with hands-on experience in automotive embedded systems, ML, and end-to-end MLOps. At KPIT Technologies, I optimized the ISO2 charging stack, introduced a new calibration that reduced plug-out timeout errors by 30%, and fixed a critical memory leak to achieve less than 1% runtime variation. I’ve also worked at NARL on RF signal analysis using oscilloscopes and spectrum analyzers. I enjoy building practical AI solutions CNN-based plant disease detection, MediaPipe fitness tracking, LSTM stock prediction, and a full CI-CD-enabled visa prediction system. Strong in C++, Python, Java, DS&A, Docker, AWS, and Linux. Published two IEEE papers and secured AIR 95 in TCS CodeVita Round 2. I’m driven, curious, and passionate about solving real-world problems through smart engineering.