Engineering Projects
Design Projects
About Me
Resume
Contact
Illustration Gallery
Research Publications
Hi,
I'm Hwei-Shin (sounds like 'way sheen')
I am a first-year PhD student in software engineering at Carnegie Mellon University, advised by Josh Sunshine and Dominik Moritz.
My experience is primarily in full stack engineering, data analysis
and data visualization. I am passionate about improving STEM
education, particularly by improving visual communication in
learning materials (check out my work on
Edgeworth). I am always
looking for interesting ways that technology and design
intersect, and I care about working on impactful projects that
have the power to make the world a better place.
Check out my resume for
more detailed descriptions of my professional experience and
qualifications, and my
project gallery to learn more about
some of the projects I have worked on.
Experience:
-
Student Researcher at Carnegie Mellon University,
2023-present
-
Fullstack Software Engineer at Tableau,
2022-2023
-
Research Intern at
Penrose (Carnegie
Mellon University),
2021
-
Vehicle Software Engineering Intern at Tesla Motors,
2020
-
Fullstack Engineering Intern at Tableau,
2019, 2020
Education:
-
Carnegie Mellon University, School of Computer Science,
PhD Student
-
Olin College of Engineering, B.S Engineering,
2022
-
Parsons School of Design (visiting student),
2020
Awards:
-
NSF Graduate Research Fellowship Program Recipient,
2023
-
ARCS Scholarship Recipient,
2023
-
Grand Finalist, ACM Student Research Competition
2021
-
1st Place Undergraduate Division, ACM SPLASH Student Research Competition
2021
-
Semi-Finalist, Disney Imagineering
2020
-
50% Tuition Olin Merit Scholarship
2017-2022
Outside of Engineering:
-
Professional ballerina, guests around U.S
-
Digital Illustrator, owner of Arken Designs
- Peet's Coffee Certified Barista
- Collegiate Overwatch player for Carnegie Mellon University
Software Projects
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-
Swiss Modernism Poster Generator
Web Development
Spring, 2020
-
LDA Research Buddy
Machine Learning
Fall, 2019
-
All About MNIST & Convolutional Neural Nets
Machine Learning
Fall, 2018
-
Robolympics: PID Control Loop
Firmware, Controls
Fall, 2018
-
Robotic Vaccuum Obstacle Course: RANSAC, Gradient Descent
Mapping, Perception
Fall, 2018
-
Eigenface & Bayesian Facial Recognition
Computer Vision
Spring, 2018
-
Paletteful: Image-Based Color Palette Generator
Image Processing
Spring, 2018
Design Projects
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-
Life Cycle of Stars
Data Visualization
Spring, 2020
-
YAGP Ballet Competition Winners: Where Do They Come From?
Data Visualization
Spring, 2020
-
Neri Oxman: Material Ecology MoMA Exhibit Rebranding
Illustrator, InDesign
Spring, 2020
-
Disney Imaginations Design Competition: Semi-Finalist
Research, User Experience
Fall, 2019
-
Ballet: Data Visualization
Illustrator
Fall, 2019
Other Projects
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-
Illustration Gallery
2017-2020
-
"hey, spaceman" Poster
Fall, 2019