Donny Bertucci
I want to use compute to advance 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 done research as a part 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. (incomplete) Computer Science
Georgia Institute of Technology
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
9.2023 – 6.2024
Oregon State University
Research Engineer, Venom Biochemistry and Molecular Biology Lab
6.2023 – 9.2023
Carnegie Mellon University
Data Visualization Research Intern, CMU Data Interaction Group (DIG)
9.2022 – 6.2023
Carnegie Mellon University
Research Assistant, CMU Data Interaction Group (DIG)
5.2022 – 8.2022
Carnegie Mellon University
8.2021 – 6.2022
Oregon State University
Research Assistant, Data Interaction and Visualization (DIV) Lab
2.2021 – 6.2021
Oregon State University
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
[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
[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
Workshop
[W2]
Backprop Explainer: Interactive Explanation of Backpropagation in Neural Network Training
[W1]
An Interactive Introduction to Autoencoders
Open Source
[O11]
VQ-VAE Explainer: Learn the VQ-VAE Implementation with Interactive Visualization
[O10]
Explore ARC-AGI
[O9]
VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization
[O8]
DS569k Protein Embeddings Dataset
[O7]
Venome: A System to Store and Analyze Venom Protein Function
Donald Bertucci
, Ansen Garvin
, Cora Bailey
, Amanda Sinha
, Michael Youkhateh
, and Nathan Mortimer
[O6]
Random Number Generator with Elementary Cellular Automata in Matlab
[O5]
ProteinScatter: Visualizing Fragments of Structurally Similar Proteins with a Scatterplot
[O4]
Visualizing Neural Network Compression
[O3]
FalconVis: A Library to Cross-Filter Billions of Data Entries on the Web
[O2]
Finding the Distance Function in the Poincaré Disk using Stereographic Projection
[O1]