hi there! i'm

jadeddelta

a software engineer *

a human centric developer 
	with a great passion for
		learning, creating, and upgrading

about me

hello world! i'm a recent graduate from vassar college, with a bachelor's in computer science and a math minor! i've dabbled in plenty of diverse topics, from web dev, to machine learning, to even rudimentary game development! still so early into my career, i am passionate for learning and creating, especially in my current concentration as a research software engineer, directly contributing to scientific research via making developers lives easier with better, well documented and easy to understand tools.
below, you'll find various projects and skills that i've developed since high school. along with that, attached is a more detailed version of my work history, projects and responsibilities that i've taken on in the past few years. i'm always looking for new opportunities to learn and grow, so feel free to reach out if you have any questions or want to chat/collaborate!

expertise

Frontend Development

always focused on the end user, with working knowledge of web technologies such as React and Next.js.

Machine Learning Research

with a deep interest in ethical AI usage, assiting in architecting models for open source camera eye-tracking.

Data Analysis and Engineering

curious and driven about statistics, revelling in the nuances of data manipulation and visualization.

Academic Software Engineering

passionate on building open-source tools for researchers, especially in non-programming fields.

projects

tap on a project to learn more!

professional experience

July 2025 to Present

Research Software Engineer

Immediately after graduation, I began working full-time underneath the same POSE grant as a full-time Research Software Engineer, greatly expanding my responsibilities and scope of work. In this role, I..

  • continue my work as a core maintainer of jsPsych, particularly in a managerial role, as I oversee the work of 4 other part-time students working on the library, but also expanding my own contributions to the codebase and code review processes with our backlog.
  • expand the jsPsych "timelines" functionality, a new paradigm that allows for parameterizable, resuable experiment structures, through extensive review of the student team's work, along with my own contributions.
  • engage in a grant offered by the Center for Open Science to improve interconnectivity between itself and DataPipe, a lightweight service for providing born-open data to Open Science Foundation repositories.
  • architect an OAuth solution to allow for OSF users to log into DataPipe with their existing credentials, supported through the existing Firebase backend, all written in TypeScript. work on this was conducted in lieu with the COS team themselves, allowing me to gain experience on working with their Python backend "GravyValet".
  • present posters at various conferences such as Society for Computation in Psychology (SCiP) and US Research Software Engineer Association (US-RSE), detailing the work done on jsPsych timelines and our findings for open source and open science community building.

September 2024 to May 2025

Assistant Research Software Engineer

After my work in the cognitive science department, I was selected to work under a POSE (Pathways to Enable Open-Source Ecosystems) grant, where I focused my efforts primarily on jsPsych. In this role, I...

  • maintained and developed jsPsych as the most recently promoted core maintainer, engaging in code review, merging pull requests, and spearheading the work on new features.
  • implemented said features into new plugins and core functionality of the library, such as developing a plugin to determine if a user is wearing headphones or not for an experiment.
  • collaborated with the jsPsych community, expanding community outreach and engagement within the repository and on the documentation, emphasizing a contributor-user experience.

October 2023 to June 2024

CogSci Programmer

Employed under Vassar's Cognitive Science department, I advanced forward a diverse array of projects, underneath the same professor that I was with during URSI. While working, I...

  • refocused efforts on eyetracking machine learning research, redocumented data processing pipelines and standardized processing of 5000+ video clips using OpenCV and MediaPipe.
  • explored new research literature, implementing novel solutions in computer vision such as visual transformers and novel loss functions in Tensorflow and Keras.
  • assisted in maintaining jsPsych, writing TypeScript production code, implemented features for plugins that are unit tested, based on GitHub issues and discussions.
  • spearheaded a modernization of Vassar College's turing machine simulator, updating a 7-year-old website to Next.js with modern React and Redux practices.

May 2023 to August 2023

ML Research Assistant

For this summer, I was able to continue my work from the previous summer's URSI, working on the exact same project but on a different team of 2 other students. This time, I...

  • expanded on computer vision machine learning research conducted last summer, implementing various models such as Siamese Networks and Attention Mechanisms.
  • fabricated ETL pipelines to process 1000+ participants' data in a Python package, allowing for modular and scalable data processing of various facial landmark points.
  • utilized services such as wandb for hyperparameter tuning, finalizing a Siamese CNN embedding model with attention and a custom triplet loss function.
  • similarly to last year, presented our final model with a poster to the URSI symposium, with a final model that reported a normalized euclidean distance error of 7.18%.

May 2022 to July 2022

ML Research Assistant

I participated in Vassar College's URSI (Undergraduate Research Summer Institute) where I worked on a project to use Machine Learning to predict the outcome of where a user is looking on a screen given webcam data. In this project, I...

  • devised a research and development plan with my team, which brought forward my first experiences with collaborative programming, Git version control, and GitHub's hosting platform.
  • developed in Python, using packages such as TensorFlow for the ML model, and OpenCV for webcam data; along with using JavaScript with JsPsych for desgining the experiments that would be disseminated over Prolific.
  • architected a CNN embedding network with LSTM processing, along with our own custom ETL pipelines for processing data with google's MediaPipe for facial landmark demarkation.
  • presented our final model to the URSI symposium with a poster detailing our research and findings creating a model with a mean distance error of 18%.