Sayan Mandal is a Senior Software Development Engineer and PhD candidate blending eight years of experience in machine learning, computer vision, and time-series analysis to build production-grade LLM and detection systems. At AMD he focuses on hybrid SFT LLMs and efficient runtime architectures for automated code review and compliance, while his academic work at Duke centers on CNN-LSTM models and weak supervision for disease progression from medical imaging. His background spans applied industry wins—improving Alexa FireTV search with a BART-Large pipeline—and research prototypes like real-time drone detection using audio processing on edge hardware. Trained originally in aerospace at IIT Kharagpur and a KVPY fellow, he pairs strong control-systems and signal-processing instincts with fluency in Python and hands-on experience deploying scalable ML solutions. Notably, he combines deep research rigor with practical system-building, from Raspberry Pi detectors to production LLM deployments.
8 years of coding experience
3 years of employment as a software developer
Higher Secondary High School/Secondary Certificate Programs, Higher Secondary High School/Secondary Certificate Programs at Atomic Energy Central School-1, Jaduguda
Doctor of Philosophy - PhD Electrical and Computer Engineering, Doctor of Philosophy - PhD Electrical and Computer Engineering at Duke University
Bachelor of Technology (B.Tech.) Aerospace Aeronautical and Astronautical Engineering, Bachelor of Technology (B.Tech.) Aerospace Aeronautical and Astronautical Engineering at Indian Institute of Technology, Kharagpur
Secondary General, Secondary General at Atomic Energy Central School, Turamdih
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Sayan Mandal - Senior Software Development Engineer at AMD