Hesam Sagha is a software engineering manager with 10 years of experience turning machine learning research into production products, currently leading technical development at audEERING in Gilching, Germany. His career blends hands-on ML engineering, product ownership and research—from PhD work in pattern recognition at EPFL to postdoctoral roles in German universities—focused on human activity recognition, anomaly detection and robust multi-stream signal processing. At audEERING he progressed from ML engineer to senior product owner and now manager, demonstrating an ability to bridge research rigor with product delivery and cross-functional leadership. He brings deep expertise in classifier ensembles and noise-robust systems, and a track record of shipping applied ML solutions in audio and sensing domains.
10 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Pattern Recognition Human Activity Recognition Anomaly Detection, Doctor of Philosophy (Ph.D.) Pattern Recognition Human Activity Recognition Anomaly Detection at EPFL
Bachelor of Science (BSc) Computer Software Engineering, Bachelor of Science (BSc) Computer Software Engineering at Ferdowsi University of Mashhad
Master of Science (M.Sc.) Artificial intelligence, Master of Science (M.Sc.) Artificial intelligence at Sharif University of Technology
This module aims to extract emotions from audio. The input argument is either an uploaded audio/video file to the server or a URL. The output is the predicted emotion in terms of Arousal and Valence within the JSON-LD format.
Contributions:21 commits, 19 pushes, 4 comments in 1 year 4 months
A stand-alone OpenSmile plugin for the Cordova framework.
Contributions:6 commits, 1 PR, 4 pushes in 5 months
cordovaopensmile
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