Asif Rahman is a Senior Scientist in New York with 13 years of experience at the intersection of machine learning and signal processing, currently developing clinical analytics at Apple after leading AI research in digital health at Philips. He specializes in physiological time-series, wearable biosignals (ECG, PPG, ABP, PCG), and sequence learning from EHRs, with practical deployments such as the Hemodynamic Stability Index for bedside monitors and top-performing solutions in multiple PhysioNet Challenges. His work blends deep learning (TCNs, RNNs, transformers) with interpretable models—e.g., an Interpretable-RNN and a mixture-of-experts approach that encodes prior medical knowledge—while also building tools like a visual time-series search engine for fast case retrieval. Trained as a bioengineer with a PhD and a strong publication record in biosignal processing and computational neuroscience, he brings both rigorous academic methods and product-focused engineering to improve patient outcomes. An uncommon strength is his track record of translating research prototypes into monitor-integrated algorithms and clinical trial collaborations with industry partners.
13 years of coding experience
11 years of employment as a software developer
Bachelor's Degree, Bioengineering and Biomedical Engineering, Bachelor's Degree, Bioengineering and Biomedical Engineering at City University of New York City College
Contributions:3 commits, 2 pushes, 1 branch in 1 day
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