Sancar Adali is a computational biologist and data scientist with 12 years of experience applying statistical learning and machine learning to biomedical and multimodal data, currently contributing at GSK and freelancing on research projects. He combines deep learning expertise (TensorFlow, Keras, Caffe) with classical methods in survival analysis, signal/image processing, and genomic sequence analysis to develop reproducible, production-minded solutions for biomarker discovery and risk prediction. His background spans government and academic research—DARPA/IARPA programs, Raytheon BBN, FDA ORISE work, and Johns Hopkins—where he built algorithms for video analytics, genomic engineering detection, and graph/matching problems. Comfortable coding across R, Python, C/C++, Java and MATLAB, he brings both software engineering rigor and statistical depth, having implemented optimization algorithms like FAQ and worked with mass spectrometry, connectomes, and time-to-event clinical data. A permanent U.S. resident based in Rockville, MD, he uniquely bridges hands-on algorithm development with practical translational science aimed at real-world clinical and defense challenges.
12 years of coding experience
13 years of employment as a software developer
M.Sc, Electrical Sciences & Computer Engin., M.Sc, Electrical Sciences & Computer Engin. at Brown University
Johns Hopkins University
Robert College
B.Sc., Electrical and Electronics Engineering, B.Sc., Electrical and Electronics Engineering at Boğaziçi University
Contributions:32 pushes, 1 branch in 3 years 8 months
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