Summary
Michael Weisner is a Senior High Performance Computing Specialist with nine years of experience building and operating research computing platforms for top universities, currently supporting HPC clusters and cloud-based research at NYU. He combines deep hands-on expertise in HPC operations, containerized workflows (Singularity), GCP and AWS services, and secure research environments with a strong background in data security, machine learning, and statistical programming in Python and R. At Columbia he helped design and run multiple HPC clusters, a Secure Data Enclave, and JupyterHub deployments, and he now leads SRDE tasks including NIST 800-171 assessments and policy drafting. His MA in Quantitative Methods complements his engineering work, exemplified by a thesis analyzing air pollution, weather, and S&P 500 predictive relationships, highlighting his ability to translate quantitative research into production-ready compute solutions. Notably, he bridges researcher-facing training and technical automation, making complex secure-compute workflows accessible and repeatable across academic projects.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Arts (B.A.), Sociology and Environmental Studies, Bachelor of Arts (B.A.), Sociology and Environmental Studies at New York University
Master's degree, Quantitative Methods in the Social Sciences, Master's degree, Quantitative Methods in the Social Sciences at Columbia University Graduate School of Arts and Sciences
English, German, Japanese