TLDR: I’m working on my PhD in astrophysics. I like machine learning. I develop software to apply machine learning algorithms to some of the largest astronomical datasets ever collected in near real-time. Check out my research and software portfolios here and connect with me on LinkedIn if you’d like to know more!
What I Do
I am a PhD candidate in the Physics Department at the University of Wisconsin-Madison studying astrophysics and computer science. I am passionate about developing new ways to approach problems in modern astronomy. Optical astronomy is undergoing what I would call a “Big Data Revolution” where astronomers are faced with larger and more complex datasets than ever before, and these datasets are only expected to increase in size over the next couple decades.
My work finds new ways to both handle and leverage these datasets, enabling myself and others to squeeze as many answers about the nature of the Universe out of the data as possible. The main technique I use is machine learning, in which I develop ways to organize and characterize astronomical data such that a computer is able to detect patterns in the dataset. Then by analyzing these computer-identified patterns, I am able to help move the field forward with new findings about the Universe.
The most exciting part of what I do is working in real-time, where I am trying to identify the most interesting astronomical objects in large datasets seconds after the data are collected, and competing with other research teams to do just that. For this purpose, the machine learning approaches I utilize need to be robust and ready-to-go at all times, and to make that possible I spend a lot of my time on software engineering solutions.
On this website you can find information on my current research, contributed software, and media in which my work has been featured. Thanks for visiting!