Muhammad Saleem is a PhD-trained Data Scientist with eight years of experience turning high-dimensional sensor and vision data into production-ready AI, specializing in multimodal sensor fusion and edge intelligence for UAVs and autonomous systems. He bridges foundational research—Computer Vision, Transformers, and time-series forecasting—with hands-on MLOps, deploying models on AWS SageMaker and optimized edge platforms to reduce latency and maximize real-world ROI. His work spans document AI/OCR, object detection, and automated demand-forecasting MVPs, reflecting a rare combination of algorithm design and systems architecture. Notably, his research projects captured expert inspector behavior via eye-tracking and developed ultra-low-power event-driven sensors, showing a practical focus on accessibility and long-term structural monitoring. Based in Fort Lauderdale, he thrives at the intersection of high-performance computing and field-deployable solutions, able to own models end-to-end from prototype to scalable production.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Penn State University
Master's degree, Master's degree at Chung-Ang University
Bachelor’s Degree Electrical and Electronics Engineering, Bachelor’s Degree Electrical and Electronics Engineering at Bahria University
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