Hillol Sarker is a Senior AIML Scientist with a decade of experience applying machine learning and deep learning to real-world healthcare and mobile sensing problems. He combines a strong software engineering background (Python, C++, Java, Matlab, PHP) with research-grade expertise in CNNs, LSTMs, autoencoders, imputation, and time-series sensor analytics. His work spans end-to-end systems from smartphone and smartwatch data collection platforms to cloud-based pipelines, yielding measurable gains such as boosting activity-detection F1 from 0.856 to 0.955 and improving EHR imputation over prior art. At Sanofi and formerly IBM Research and MD2K, he translated sensor and ICU data into actionable models for monitoring stress, smoking, and adverse events, demonstrating both product and scientific impact. He is comfortable leading cross-disciplinary teams and building production-ready components (Android, Horovod, TensorFlow/Keras) while retaining a keen eye for statistical rigor in hypothesis testing and distributional modeling. Based in Belmont, MA, he blends deep academic credentials (PhD) with hands-on engineering—often bridging gaps between prototype research and scalable clinical applications.
10 years of coding experience
19 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at The University of Memphis
Bachelor of Science (B.Sc.), Computer Science and Engineering, 3.57, Bachelor of Science (B.Sc.), Computer Science and Engineering, 3.57 at Bangladesh University of Engineering and Technology
Contributions:4 PRs, 20 pushes, 3 branches in 13 days
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