Summary
Alex Sim is a seasoned scientific computing leader based in Berkeley with 14+ years driving R&D in data-intensive HPC, distributed systems, and machine learning at Lawrence Berkeley National Laboratory. Trained in applied math, statistics, and computer science, he designs and implements in-network storage/computing, streaming analytics, and dynamic resource management for domains from astronomy to genomics. He has led DOE and NSF projects as PI/Co-PI, contributed to 350+ publications, standards, open-source releases and patents, and has shepherded systems from algorithm design through open-source deployment. Known for blending statistical rigor with systems engineering, he focuses on online anomaly detection and performance prediction for autonomic scientific data infrastructures. As a senior IEEE member who has served on editorial and program committees, he quietly shapes both research directions and operational best practices across data, cloud, HPC, and networking communities.
14 years of coding experience
19 years of employment as a software developer
BA Applied Math and Statistics (double major), BA Applied Math and Statistics (double major) at University of California, Berkeley
MS Computer Science, MS Computer Science at San Francisco State University