About Me

I'm in my final year of undergrad at the University of Utah, and I'm currently interested in learning more about Ph.D programs in HCI/Computer Science.

My past vis work has involved visualizing educational data with the Sorenson Impact Center, biological data with Genentech, and environmental health data with Miriah Meyer and Pascal Goffin in the Visualization Design Lab.

Throughout my experiences, I've enjoyed conducting, drafting prototypes, and working with D3. I thrive on dense technical projects, but I also love the human side of vis.

In the future, I hope to complete a Ph.D in Computer Science and conduct applied visualization research. If you have openings in your lab, I'd love to connect with you.

Contact Details

Dylan Wootton
(435) 770-0754
me@dylanwootton.com

Education

University of Utah

B.Eng in Bioengineering, Computational Emphasis. Minor in Computer Science
May 2019 3.95 GPA

Relevant Courses:

Machine Learning: Deep Learning, Visualization for Data Science, Data Structures and Algorithms, Discrete Mathematics, Engineering Computing, Linear Algebra and Differential Equations, Object Oriented Programming, and Computational Methods.

Relevant Work

The Visualization Design Lab

Undergraduate Researcher March 2018 - Present

Performed user interviews with members of the AirU project to conceptualize and build web-based tools for exploratory data analysis and pollution detection.

Constructed a webscraper in Python to collect data and processed it using NumPy and Pandas. After cleaning the data, various digital signal processing algorithms were used to classify air quality events (forest fires, inversions, and pollution from commuting) based on the scraped sensor data. Finally, using JavaScript, D3.js, and Leaflet, a visualization tool was built to investigate air quality event data. I presented my research at UDSD 2018. Link to Poster

Genentech

Engineering Intern May 2018 - August 2018

My internship focused on three different projects: purification, oncology, and site-services development.

Planned and executed wetlab experimentation to generate a purification dataset of 17 contaminants, leveraged this dataset to reduce future sample testing. A visualization tool was built using D3.js to explore and communicate the purification data.

Cleaned oncology meta-data for bioinformaticists using R .

Coordinated with site-services to implement a route finding application for their bus pickup locations. Produced a prototype application using leaflet and R shiny which resulted in an investment to construct a full-scale application.

Sorenson Impact Center

Technical Fellow September 2017 - May 2018

Worked with a team of 7 data scientists to provide insights on pay for success projects between state governments and private companies. Primarily used R for data visualization, modeling, cleaning, and analysis. Automated data acquisition tasks saving over 100 billable hours for the Venture Analysis team using Python.