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jmaasch/README.md

J R M A M

I am a PhD student in the Department of Computer Science at Cornell University. I am primarily interested in machine learning and causal inference for clinical research. My major areas are in Artificial Intelligence and Scientific Computing and my minor area is in Applied Probability and Statistics.

🏛️ Affiliations: Cornell Tech | Weill Cornell Medicine Institute of AI for Digital Health | Wang Lab | Kuleshov Group.

📚 Read more about my work @ ResearchGate | Google Scholar | LinkedIn.

Research interests

🖥️ 🔢 Machine learning; causal inference; causal graphical models; probabilistic, generative, and latent variable models; low data regimes; Bayesian methods; scientific computing.

🔬 💊 Computational biomedicine; drug development; health and disease; the microbial ecology of the human body; genetics, genomics, and evolution; the art and science of data visualization.

Pinned

  1. ldp ldp Public

    Local Discovery by Partitioning: Polynomial-Time Causal Discovery around Exposure-Outcome Pairs

    Python

  2. sanzo sanzo Public

    R Color Palettes Based on the Works of Sanzo Wada – A CRAN Package

    HTML 25 2

  3. ashR ashR Public

    Bespoke interpolated color palettes for data visualization in R.

    R 1

  4. pennR pennR Public

    Color palettes for R data visualization based on the official school colors of the University of Pennsylvania.

    R 3 1