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For my PhD I used statistics, machine learning, and massive astronomical image data to explore what our galaxy is made of.
Looking now towards our own planet and society, I want to use machine learning to help build more sustainable, efficient industries and communities.
My passion is connecting knowledge between natural sciences, engineering, and machine learning, and blurring the lines between industry and academia.
Curiosity led me to double-major in biology and physics. Finally, I ended up diving into astronomical data science during grad school, studying the molecules floating around in space that can eventually become planets, and even living things.
Because astronomy grad school didn’t teach enough of the latest machine-learning techniques, I did an internship at Grid, Inc. during the last year of my Ph.D. program. This introduced me to the world of machine learning.
Now, my curiosity leans towards the human experience- infrastructure, healthcare, social and environmental stability- I want to use a combination data science, AI, and compassion to improve peoples lives, and the life of our planet at the same time.
Now at the NASA Frontier Development lab I'm finding I have a strong passion for science acceleration using machine learning, in general. I love working on a diverse range of scientific computing challenges, from infrastructure to astrobiology.
Working in an extremely diverse team to leverage AI, the Google Cloud Platform, and scientific guidance to probe the edge astronomy and biology. My role in the team, as an astronomy PhD with experience machine learning, is as a conduit between the scientists and Ai engineers. My technical input during the program was valuable in developing a pipeline from varied extreme-life datasets to potential effects on exoplanetary atmosphere stability, leveraging cutting-edge machine learning techniques. The questions we hoped to answer were challenging but were poised to create a firm stepping stone in the 8-week intense science accelerator program that future researchers can pick up and run with. Alas 8-weeks was not enough to solve all the possibilities for life in the universe, but my team and our mentors continue working together remotely as Volunteer Fellows.
This project is in collaboration with GRID, Inc. We are applying a variety of machine learning techniques to massive, all-sky astrophysical data sets. Our goal is to facilitate breakthroughs in big-astrophysical-data. This field suffers from two major limitations that we think machine learning can help with: 1) Heavy reliance on conventional models (which make very strong assumptions) 2) Too much data! We have more information coming in from satellites and telescopes than we are able to efficiently and thoroughly analyze.
2017-3 - 2017-5
NASA Frontier Development Lab 2018: Astrobiology Team 1 Abstract for NeurIPS 2018 @ Montreal
I double-majored in biology and physics to build a broad platform of knowledge about natural sciences. For example, I took elective classes in ecology and neuroscience due to their interdisciplinary nature. My major interest was in studying connections between biology, chemistry, physics, and astronomy. In my last year and a half, I started to focus on astrophysics. I did small research projects in biology and materials science, and an in-depth project in astrophysics. At the same time, I studied Japanese language and culture and grew a strong interest in exploring Japan and the world, leading to my choice of UTokyo for graduate school.
What it Means to be a Scientist in the 21st Century
This was a one-time seminar, which I led and organized. It took the format of an open discussion, between senior faculty members, junior professors, and students. A led the 2-hour long discussion about what the role of a researcher would look like in the next 100 years. It was a lively conversation between experienced researchers and students just entering the field. More than that, it was a lot of fun for my, as just an undergrad, to be able to stimulate such a discussion.
2011-10 - 2011-10
Coursera-Stanford: Machine Learning Course
JLPT N3 (日本語能力試験３級）
Udemy "Intro to Data Science" Course
JLPT N5 (日本語能力試験５級）
Chambliss Astronomy Award for Science Communication