I do science

Summary

Kaze W. K Wong
Assistant research professor
Johns Hopkins University

I am an assistant research professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University. I am also a software engineer with the Data Science and AI Institute. I have very broad interest in many different subjects. In brief, I spend 20-30% of my time thinking about astrophysics, ~40% of my time trying to understand to make neural network robust and how to tune them, and the remaining time building production-grade domain science applications. My work is primarily computational and I care about open source software a lot. See below for some of the topics I am currently working on.

Research Highlight

Here are some topics I am or have been working on. I am big believer in collaborative work instead of racing against each other, so if you find any of the following topics interested you, feel free to reach out to me.

Gravitational wave
Understanding the nature of gravity through ripples in spacetime
Data driven astrophysics
Bridging the gap between all observatories with machine learning
Robustness and Interpretability in machine learning
Ensuring we learn something meaningful from our models
Adaptive Sampling
Optimizing the way we solve inverse problem
Open Source Scientific Software
Open science needs open source software

Course and presentations

Courses

Presentations

My presentation slides are hosted on github

And also, here are some talks I did with recording that are publicly available