Alex Sim

About Alex Sim

Alex Sim is a senior computing engineer in Scientific Data division at Lawrence Berkeley National Laboratory. His educational background is in statistics, applied mathematics and computer science. His recent research area includes in-network storage and computing, streaming data analysis methods, dynamic resource management, performance optimization for HPC applications, and statistical modeling and machine learning methods for autonomic scientific data infrastructure. He has been involved in scientific application projects, such as astronomy, climate modeling, combustion modeling, fusion science, genomics, high energy physics, nuclear science, power grids, transportation, and others. He has contributed to 350+ paper publications and technical reports, standard specifications, open source software packages, and multiple patented technologies. He has been leading the system designs, development of algorithms and models, implementation of the systems, and software package releases under open source license. He has led projects from the U.S. Department of Energy (DOE) and National Science Foundation (NSF) as a lead PI or Co-PI. He has involved in technical program committees, steering and advisory committees for conferences, journal editorial boards, review panels, and standardization forums in data, cloud computing, HPC, and networking areas. He is a senior member of info: https://sdm.lbl.gov/asim)

Experience

1. Scholarly Engagements Lead

   Berkeley Lab

   Oct 2025 — Present

Education

• University of California, Berkeley

  MA, Statistics

  1993

• University of California, Berkeley

  BA, Applied Math and Statistics (double major)

  1990

• San Francisco State University

  MS, Computer Science

  1995

Skills

• Data Mining
• Cloud Computing
• Distributed Systems
• Storage Management
• Modeling
• Artificial Intelligence
• Software Engineering
• Networking
• Statistical Data Analysis
• Data Analysis
• Grid Computing
• Machine Leaning
• Mpi
• Parallel Computing
• Mathematical Modeling
• High Performance Computing
• Big Data
• Python