Mulugeta Asres is an AI researcher with a Ph.D. in Artificial Intelligence and eight years of experience applying deep learning and multivariate time-series analytics to large-scale monitoring and Industry 4.0 problems. He has built AI-driven anomaly and data-quality monitoring systems for CERN’s HCAL and developed real-time privacy-preserving anonymization for CCTV at the University of Agder, reflecting a rare mix of high-energy physics instrumentation and applied surveillance ethics. His background spans telecom and manufacturing predictive analytics, NILM research for energy disaggregation, and core network engineering, demonstrating strong cross-domain engineering fluency from embedded systems to cloud-scale R&D. Based in Norway, he emphasizes responsible AI and operationalizing models for continuous monitoring of complex infrastructures—often solving noisy, overlapped-event detection challenges that standard methods miss.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at University of Agder (UiA)
Master of Science (M.Sc.), Computer Engineering, 4.0/4.0, Excellent, Master of Science (M.Sc.), Computer Engineering, 4.0/4.0, Excellent at EiT-M and Thesis at Midori Srl (Italy)
Bachelor of Science (B.Sc.), Electrical and Computer Engineering, Bachelor of Science (B.Sc.), Electrical and Computer Engineering at Ethiopian Institute of Technology-Mekelle, Mekelle University
Contributions:47 pushes, 6 branches in 1 year 7 months
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