Mere data makes a man —
A and C
and T and G.
The alphabet of you —
I am only two — 1 and
I am on the market for
faculty positions starting Fall 2021.
I am a PhD student in
the Department of Computer Science at Johns Hopkins
Shpitser. The primary focus of my research is methods
development for causal inference. I am also interested in the
application of techniques in causal inference and machine
learning to the analysis of complex genomic datasets to
improve patient outcomes.
Email: First letter of my first name concatenated with
my last name at jhu.edu.
- October 15, 2020: New draft on differentiable causal discovery
in the presence of unmeasured confounders is now up on arXiv
at this link.
- May 1, 2020: Super happy to announce the public
Ananke, a Python software package for causal inference
using graphical models.
- Apr 16, 2020: Razieh
and I gave a joint talk on semiparametric
inference for causal effects in graphical models with
hidden variables at the JHU Biostatistics Causal
- Jan 15, 2020: Razieh and my
introductory course on Causal Inference was
in the Johns Hopkins Hub magazine!
- May 25, 2019: Razieh and I
won the Thomas R. Ten Have award at ACIC,
Montréal. This means that we will be giving a joint
talk at ACIC next year in Austin, Texas.
- May 22, 2019: Presenting a poster
on identification in missing data models represented by
directed acyclic graphs at ACIC, Montréal.
- May 22, 2019: Presenting a poster on causal
inference under interference and network uncertainty at ACIC,