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.

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

Courses

My presentation slides are hosted on github

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

UoA TAP seminar

17-10-2023

NYU Astro seminar

12-09-2023

CZS Summer school 2023

14-08-2023

Amaldi 15

08-08-2023

CMU STAMP seminar

27-10-2022