Junting Ren
Hey there, I am Junting, Data Scientist/Statistician with a strong background in developing and implementing innovative statistical and machine learning methodologies. Proficient in Python, R, and Linux, with a proven track record of driving strategic analytical initiatives and enhancing decision-making through experimentation design and predictive modeling.
Latest news:
2024-07: Methodology paper published on Communications biology . I built a zero-inflated L-0 penalized regression model in Pytorch using Variational Inference that sped up the Bayesian model inference by over 200%, comparing to MCMC.
2024-05: Methodology paper published on Journal of the Royal Statistical Society . I generalized the estimation of inverse sets to dense and nondense domains with protection against inflated Type I error in exploratory data analysis.
2023-06: Earned my PhD in Biostatistics from University of California San Diego, what a ride, thanks for everything.
2022-03: My paper on flexible novel Semi-parametric zero-inflated Bayesian model for right-skewed data is published in Statistics in Medicine .
要善良，你永远不知道别人在经历什么；要勇敢，只有你知道自己想要什么。如鱼饮水，冷暖自知。
Research interests
- Experimentation Design and Methodology
- Causal Inference
- Prediction Uncertainty Quantification
- Variational Inference for Large Scale Bayesian Models
Programming skills
- PyTorch, Jax, Pyro, Numpyro
- JavaScript, C++
- R, SQL, MATLAB, SAS
More about me
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Junting Ren
Shoot me an email:
junting.ren.stat@gmail.com