Chris Kennedy ck37

Psychiatric AI; biostatistics PhD. {Targeted, deep, machine} learning, NLP, IRT, computer vision, EHRs.

Achievements

ck37 /README.md

I am an instructor in psychiatry at Massachusetts General Hospital / Harvard Medical School, with a PhD in biostatistics from UC Berkeley. I work in Jordan Smoller's Center for Precision Psychiatry.

🌱 Projects from my postdoc include:
1. Measuring consumption of opiods following surgery, and reducing overprescribing through prescription guidelines and provider interventions.
2. Deep learning for surgical videos and operative notes to evaluate surgical skill and risk of complications.
3. Measuring COVID-19 severity in hospitalized patients using item response theory + EHRs.
✨ My three dissertation projects are:
⚡ Additional long-term projects include:
1. Multi-modal deep learning to track social media marketing of e-cigarettes (vaping) to teenagers - initial study
2. Causally motivated, nonparametric variable importance - varimpact software

hands-on-precision-psychiatry-ai hands-on-precision-psychiatry-ai Public

CPP Training 2025

JavaScript 4 1
ecpolley/SuperLearner ecpolley/SuperLearner Public

Current version of the SuperLearner R package

R 286 76
dlab-berkeley/Machine-Learning-in-R dlab-berkeley/Machine-Learning-in-R Public archive

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

CSS 194 72
coral-ordinal coral-ordinal Public

Tensorflow Keras implementation of ordinal regression using consistent rank logits (CORAL) by Cao et al. (2019)

Python 83 23
varimpact varimpact Public

Variable importance through targeted causal inference, with Alan Hubbard

R 59 12
dlab-berkeley/Unsupervised-Learning-in-R dlab-berkeley/Unsupervised-Learning-in-R Public

Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).

R 47 12