Donny Bertucci
Using compute to solve problems in science.
Previously, Computer Science PhD student at Georgia Tech and Computer Science and Math undergrad at Oregon State University .
I've worked on visualizing neural networks, analyzing protein function, large scale data analytics, machine learning model interpretability, and explainable AI at Georgia Tech , Oregon State , and Carnegie Mellon .
I've been a member of the GT Visual Analytics Lab , OSU Venom Biochemistry & Molecular Biology Lab , CMU Data Interaction Group , and OSU Data Interaction and Visualization Lab .
Education
8.2024 – 11.2024
Ph.D. Computer Science
Georgia Institute of Technology
Machine Learning and Human-Computer Interaction
*degree incomplete: left as of 11.2024
9.2020 – 6.2024
B.S. Computer Science
Oregon State University
Experience
8.2024 – 11.2024
Georgia Institute of Technology
Graduate Research Assistant, GT Visual Analytics Lab
Researched better Machine Learning User Interfaces and Explainable AI [_, _, _, _]. Advised by Dr. Alex Endert
.
9.2023 – 6.2024
Oregon State University
Research Engineer, Venom Biochemistry and Molecular Biology Lab
Designed an interface with protein visualization and implemented computational analysis methods
to discover protein function for venom proteins [_].
Advised by Michael Youkhateh
and Dr. Nathan Mortimer
.
6.2023 – 9.2023
Carnegie Mellon University
Data Visualization Research Intern, CMU Data Interaction Group (DIG)
Researched interactive methods to improve language model prompt generation and transparency
with Dr. Adam Perer
. Developed interactive visualizations of neural network
compression/quantization error [_].
9.2022 – 6.2023
Carnegie Mellon University
Research Assistant, CMU Data Interaction Group (DIG)
Developing human-centered ways to evaluate Machine Learning model behavior within Zeno
[_] with Dr. Alex Cabrera
. Enabling
linked visualizations at scale with FalconVis
[_] with Dr. Dominik Moritz
.
5.2022 – 8.2022
Carnegie Mellon University
Developed user interfaces to interactively discover poor behavior in neural networks [_]. Advised by Dr. Alex Cabrera
and Dr. Adam Perer
.
Hosted by the Data Interaction Group (DIG)
.
8.2021 – 6.2022
Oregon State University
Research Assistant, Data Interaction and Visualization (DIV) Lab
Developed user interfaces to visualize large data and interpret complex machine learning models
[_, _]. Mentored and
advised by Dr. Minsuk Kahng
.
2.2021 – 6.2021
Oregon State University
Developed interactive interfaces to visualize difficult concepts in learned neural networks [_, _]. Advised by Dr. Minsuk Kahng
.
Publications
Conference
[C3]
Zeno: An Interactive Framework for Behavioral Evaluation of Machine Learning
Alex Cabrera
, Erica Fu
, Donald Bertucci
, Kenneth Holstein
, Ameet Talwalkar
, Jason I. Hong
, and Adam Perer
ACM Conference on Human Factors in Computing Systems (CHI). Hamburg, Germany, 2023.
[C2]
DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with Treemaps
Donald Bertucci
, Md Montaser Hamid
, Yashwanthi Anand
, Anita Ruangrotsakun
, Delyar Tabatabai
, Melissa Perez
, and Minsuk Kahng
IEEE Transactions on Visualization and Computer Graphics (IEEE VIS 2022). Oklahoma City, OK
[C1]
Beyond Value: CHECKLIST for Testing Inferences in Planning-Based Reinforcement Learning
Kin-Ho Lam
, Delyar Tabatabai
, Jed Irvine
, Donald Bertucci
, Anita Ruangrotsakun
, Minsuk Kahng
, and Alan Fern
32nd International Conference on Automated Planning and Scheduling (ICAPS 2022).
Workshop
[W4]
Venome: A System to Store and Analyze Venom Protein Function
Donald Bertucci
, Ansen Garvin
, Cora Bailey
, Amanda Sinha
, Michael Youkhateh
, and Nathan Mortimer
2024 Engineering Expo (Computer Science Capstone Project), Oregon State University. Corvallis, OR
[W3]
Mirror: Interactive Discovery of Blindspots in Machine Learning Models
Human-Computer Interaction Institute (HCII) Summer Research Showcase (2022). Pittsburgh, PA
[W2]
Backprop Explainer: Interactive Explanation of Backpropagation in Neural Network Training
Workshop on Visualization for AI Explainability (VISxAI, IEEE VIS 2021).
[W1]
An Interactive Introduction to Autoencoders
Workshop on Visualization for AI Explainability (VISxAI, IEEE VIS 2021).
Open Source
[O9]
VQ-VAE Explainer: Learn the VQ-VAE Implementation with Interactive Visualization
Interact with and visualize a VQ-VAE (Vector-Quantized Variational Autoencoder) directly in the browser.
[O8]
Explore ARC-AGI
Visualize the ARC-AGI dataset with live crossfiltering for compression metrics.
[O7]
VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization
Interact with and visualize a Variational Autoencoder directly in the browser.
[O6]
DS569k Protein Embeddings Dataset
ProteinCLIP embeddings for ~569k proteins from UniprotKB.
[O5]
Random Number Generator with Elementary Cellular Automata in Matlab
Random numbers with Elementary Cellular Automata Rule 30 in Matlab + transform to any other distribution.
Mathematical Software with Torrey Johnson, Oregon State University. Corvallis, OR
[O4]
ProteinScatter: Visualizing Fragments of Structurally Similar Proteins with a Scatterplot
Converted proteins to Foldseek 3Di, then trained an auto-regressive transformer. Embeddings converted into a 2D scatterplot.
Molecular Modeling with Juan Vanegas, Oregon State University (2024). Corvallis, OR
[O3]
Visualizing Neural Network Compression
An interactive article exploring how model compression error affects neural network behavior.
[O2]
FalconVis: A Library to Cross-Filter Billions of Data Entries on the Web
A JavaScript library for visualizing big data on the web with your custom visualizations and scalable data formats.
[O1]
Finding the Distance Function in the Poincaré Disk using Stereographic Projection
A paper that derives the Poicare disk distance function using stereographic projection from Minkowski Space.
Non-Euclidean Geometry with Tevian Dray, Oregon State University (2023). Corvallis, OR
Skills
- Machine Learning Python, NumPy, Keras, Jax/Flax, PyTorch, TensorFlow, TensorflowJS.
- Frontend JavaScript/TypeScript, HTML/CSS, Svelte, React, Vue, Tailwind, Figma.
- Backend Python, Pandas, FastAPI, Flask, NodeJS, Express, MySQL, PostgreSQL, C/C++.
- Data Visualization Svelte, SVG, Canvas, D3, Vega/VL, Mol*, Altair, Matplotlib.
- Math for CS Linear Algebra, Vector Calculus, Discrete Math, Boolean Algebra, Propositional Logic, Statistics, Matlab, Mathematica.
- Other Writing, LaTeX, making research paper figures.
References
Dr. Minsuk Kahng
Senior Research Scientist at Google Deepmind, People + AI Research (PAIR)
Dr. Alex Cabrera
AI + Bio Startup, Founding Member of Technical Staff
Dr. Adam Perer
Professor at Carnegie Mellon University, Data Interaction Group
Dr. Dominik Moritz
Professor at Carnegie Mellon University, Data Interaction Group
Apple ML Research Scientist
Dr. Nathan Mortimer
Professor at Oregon State University, Venom Biochemistry and Molecular Biology Laboratory
Dr. Alex Endert
Professor at Georgia Institute of Technology, Visual Analytics Lab