Eric Huang is a data scientist with nine years of experience applying machine learning and predictive modeling across industrial, clinical, and space science domains. He has translated complex models into practical business value—building nationwide predictive sales models and rain-aware forecasts at CEMEX and automating data pipelines and PyTorch models for NASA’s lunar ice detection effort. At MD Anderson he combined statistical genomics (DESeq2) with clear reporting that informed clinical research on drug resistance. Eric contributes to open-source cancer informatics (cBioPortal), improving patient and study views and integrating specialized heatmap viewers, reflecting his attention to code quality and usability. Based in Greater Houston and trained in statistics at Cornell, he excels at communicating technical solutions to non-technical stakeholders and scaling ML workflows from prototype to production-ready datasets.
9 years of coding experience
2 years of employment as a software developer
Bachelor of Arts - BA Statistics, Bachelor of Arts - BA Statistics at Cornell University
Contributions:8 commits, 6 PRs, 40 comments in 2 months
Contributions summary:Eric contributed to the development of features within the cBioPortal project, specifically focusing on enhancing the patient and study views. Their work involved integrating an MDACC Heatmap viewer, which required modifications to JSP files and the Java code for retrieving and displaying heatmap data. The user also addressed merge conflicts and removed legacy/debug code, indicating a focus on code quality and maintaining the project's functionality.
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.