LabTex Document Generator, 2021 - 2022
A JupyterLab Notebook extension that makes it easier to create scientific documents with LaTeX.
This development project is a working prototype for a biomedical and clinical research company Axle Informatics in which my team and I worked on creating a Jupyter Notebook extension to enhance scientific document generation process for researchers and scientists.
My role —
designer + developer + team member
User design & research
Prototyping
Developer
Timeline —
Part 1: Aug - Dec 2021 (4 months)
Part 2: Jan - May 2022 (4 months)
Click through the slides to view more.
Working with LaTeX is unmanageable.
LaTeX is a typesetting language with a niche and hard coding format, most used by researchers and engineers due to its capable handling of complex formulas and equations.
As a result, LaTeX is often difficult to learn and use, especially for those who are not familiar with coding or programming languages. This can lead to frustration and inefficiency when creating scientific documents.
For part 1 of the project which was spanned from August to December 2021, we conducted observations, surveys, and interviews with stakeholders and users on their experiences with JupyterLab-LaTeX, a JupyterLab Notebook extension that allows users to edit a LaTeX document on the JupyterLab Notebook environment.
44.4% are unsatisfied with standard LaTeX language.
44.4% say using LaTeX affects their work productivity and efficiency.
Writing equations is the most used feature in LaTeX.
Graphing data/graph creating is the most cumbersome feature to implement in LaTeX.
For the remainder of part 1, we created a lo-fi Figma prototype to visualize the user flow and key interactions for the LabTex Document Generator extensions. The key features we focused on are Preview Document, Insert Images, Insert Equations, and Insert Tables.
Please select the full screen button on the top right of frame to fully experience the prototype.
Develop a JupyterLab Notebook LaTeX document generator extension that streamlines the research documentation process.
In part two, we started developing, keeping in mind the insights from our research and prototype analysis during part 1. We started developing the JupyterLab Notebook extension which we called LabTeX Document Generator. Development, testing, and delivery was done in three sprints and happened over the course of 4 months, and during those months, we implemented the planned key features such as Preview Document, Insert Images, Insert Equations, and Insert Tables and more such as Autocomplete, Text-alignment and Spacing, Lists, Typeface Modifier, and more.
Click through the slides to view more.
In this project, I learned that that efficiency is essential in research, and technology is the key to achieving it. By developing a Jupyter Notebook extension to simplify LaTeX, I saw how building with empathy can dramatically improve usability—making complex tools more intuitive and accessible. Technology that breaks down barriers doesn’t just save time; it empowers researchers of all backgrounds to contribute more effectively, fostering collaboration and accelerating scientific progress. Real-world impact isn’t just about innovation—it’s about empathy, listening to users, and designing solutions that fit seamlessly into their lives.
Working on the LabTeX Jupyter Extension over two semesters taught me how critical prototyping is. Our goal was to make LaTeX less intimidating by building a graphical interface in Jupyter Labs. Prototyping let us quickly test designs, spot usability issues, and uncover technical limits before investing too much time. Having two semesters gave us the space to refine those early versions and strike a balance between accessibility for beginners and flexibility for experts. In the end, prototyping was not just about testing functionality but about shaping ideas into solutions that truly met user needs.