# Research

### Bayesian SCM estimation📜

Working on some Bayesian methods to estimate the parameters of canonical Structural Causal Models.
### Bolides 📜 📖

Working on population statistics for space-based bolide detections with Jeffrey Smith at the SETI Institute. Developed a Bayesian Poisson regression model to simultaneously estimate detection bias and the latitudinal distribution of impacts. Work presented at DPS 54. Work also led to a correction of a previous paper by another team.
### 2022 Mathematical Contest in Modeling: Problem A 📜

Developed a cycling kinematics model and, combining it with track data, athlete data, and a novel optimization algorithm, optimized power strategies for cyclists.
### 2022 Columbia Mathematical Modeling Contest📜

Did a data-intensive policy analysis trying to figure out how to best deal with New York City's trash problem. Includes an interesting utility maximization based on government priorities. Currently pushing hard to try and get some of our ideas implemented.
### Phylogenetic tree inference from CRISPR lineage tracing data

Studied different methods for inferring phylogenetic trees from CRISPR lineage tracing data at the Pe'er Lab. Modified Benjamin Wilson's method of learning trees by tuning point configurations in hyperbolic space to give it a mutation model appropriate for CRISPR lineage tracing data.
### Modeling Figgie, a card game[arXiv] 🌐 📜

Did funded research into Figgie, a card game developed by Jane Street. We developed an agent-based model of the game which generalizes to market simulations and studied how different trading strategies interact in the game.
### Filtering genetic variants

Developed software to automatically filter exome data for the most likely and relevant variants based on phenotype, inheritance model, etc.
### 2021 Mathematical Contest in Modeling: Problem A📜

Developed mathematical models and wrote a paper (in 99 hours!) with a team answering some questions about changes in fungal biodiversity due to climate change. My team received an honorable mention.

## Miscellanea

Here are some things that are either too small or too farcical to be “research.”
### A Back-Door Adjustment Formula for Soft Interventions📜

Just a simple and somewhat useful little formula.

### Introduction of 3 Fictional Dragons to a Non-Fictional Planet📜

A paper written in January 2021 to practice for the 2021 MCM by answering Problem A from 2019. An attempt to improve upon the excellent solution of Krinos & Maurais. It's a little (read: very) rough around the edges but it was also the first time any of us tried something like this. I am proud of what we accomplished.

## Work I did in high school

### Can rocket failure be predicted with a statistical model?📜

Answer: Yes, but only somewhat well.

### How has increased competition in the US launch vehicle market affected its efficiency?📜

Answer: It has become more allocatively and productively efficient.

### How much voltage does it take to spark over a given air gap?📜

Answer: The Paschen Curve, as confirmed by experiment, will tell you exactly how much.