Aaron C. Bell
株式会社Ridge-i / AI Solutions Engineer
Bunkyo-ku, Tokyo, Japan
Aaron C. Bell
株式会社Ridge-i / AI Solutions Engineer
Bunkyo-ku, Tokyo, Japan
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Aaron C. Bell
株式会社Ridge-i / AI Solutions Engineer
Trained as an astro-datascientist. Dreaming of accelerating research-for-public-impact through cloud computing and machine learning.
For my PhD I used statistics, machine learning, and massive astronomical image data to explore what our galaxy is made of.
NASA Frontier Development Lab
In the future
In the future
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.
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Aug 2018
Researcher
June 2018 - Aug 2018
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 le
東京大学理学系研究科(Graduate School, The University of Tokyo)
博士号/天文学系(Ph.D., Astrophysics)
Mar 2018
Kentucky Ambassador
Oct 2007
Oct 2007
Chambliss Astronomy Award for Science Communication
Oct 2012
Oct 2012
Searching for the Culprit of Anomalous Microwave Emission: An AKARI PAHrange Analysis of Probable Electric Dipole Emitting Regions
Oct 2016
Oct 2016
Blind Component Decomposition of the Milky Way
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.
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.
東京大学理学系研究科(Graduate School of Science, The University of Tokyo)
修士号/天文学系(M.Sc., Astrophysics)
Mar 2015
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July 2012
Summer Research Intern
June 2012 - July 2012
The Honors College at Western Kentucky University
生物学と物理学 (B.S. Biology and Physics double-major)
May 2012
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
The Carol Martin Gatton Academy of Mathematics and Science in Kentucky
2009
エンジニア 博士(天文学) ベルアーロンPresent
NVIDIA GPU Grant Recipient
Aug 2018
Aug 2018
NASA Frontier Development Lab 2018: Astrobiology Team 1 Abstract for NeurIPS 2018 @ Montreal
Skills and qualities
jupyter
Communication Skill
Research
Python
Git
Publications
NASA Frontier Development Lab
July 2018
Searching for the Culprit of Anomalous Microwave Emission: An AKARI PAHrange Analysis of Probable Electric Dipole Emitting Regions
Oct 2016
Accomplishments/Portfolio
NASA Frontier Development Lab 2018: Astrobiology Team 1 Abstract for NeurIPS 2018 @ Montreal
Blind Component Decomposition of the Milky Way
Awards and Certifications
NVIDIA GPU Grant Recipient
Aug 2018
Coursera-Stanford: Machine Learning Course
Apr 2017
Udemy "Intro to Data Science" Course
Jan 2017
JLPT N3 (日本語能力試験３級）
Jan 2017
JLPT N5 (日本語能力試験５級）
July 2015
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Languages
English - Native, Japanese - Conversational