Donny Bertucci

Table of Contents

I've published machine learning research [_, _, _, _], applied machine learning to biology [_, _, _], explored the internals of machine learning architectures [_, _, _, _, _, _], and developed libraries to process large-scale data [_, _, _].

Fortunate to have been a member of the Carnegie Mellon Data Interaction Group (DIG), Oregon State Venom Biochemistry & Molecular Biology Lab, Oregon State Data Interaction and Visualization Lab, and Georgia Tech Visualization Lab.

donnybertucci.com drbertucci@hotmail.com

GitHub Google Scholar LinkedIn

Education

9.2020 – 6.2024

B.S. Computer Science

Oregon State University

Degree Focus: Artificial Intelligence, Minor: Mathematics

Experience

8.2024 – 11.2024

Georgia Institute of Technology

Research Assistant, GT Visualization Lab

Built interactive visualizations to interpret machine learning model architectures (such as VAE and VQ-VAEs) [_, _, _, _] with Dr. Alex Endert.

9.2023 – 6.2024

Oregon State University

Research Assistant, Venom Biochemistry and Molecular Biology Lab

Built a system to store, visualize, and search for similar venom protein structures using computational methods [_]. Advised by Michael Youkhateh and Dr. Nathan Mortimer.

Summer 2023

Carnegie Mellon University

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 Falcon [_] with Dr. Dominik Moritz.

Summer 2022

Carnegie Mellon University

HCII Summer Undergraduate Research Program

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

URSA Engage Research Program

Developed interactive interfaces to visualize difficult concepts in learned neural networks [_, _]. Advised by Dr. Minsuk Kahng.

Publications

Conference

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.

Paper Demo Code

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

Paper Demo Code

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).

Paper

Workshop

Venome: A Computational Analysis Tool for Protein Function

Donald Bertucci, Ansen Garvin, Cora Bailey, Amanda Sinha, Michael Youkhateh, and Nathan Mortimer

2024 Engineering Expo, Oregon State University. Corvallis, OR

Paper Demo Code

Mirror: Interactive Discovery of Blindspots in Machine Learning Models

Donald Bertucci, Alex Cabrera, Nari Johnson, Gregory Plumb, Erica Fu, and Adam Perer

Human-Computer Interaction Institute (HCII) Summer Research Showcase (2022). Pittsburgh, PA

Paper

Backprop Explainer: Interactive Explanation of Backpropagation in Neural Network Training

Donald Bertucci and Minsuk Kahng

Workshop on Visualization for AI Explainability (VISxAI, IEEE VIS 2021).

Demo Code

An Interactive Introduction to Autoencoders

Donald Bertucci

Workshop on Visualization for AI Explainability (VISxAI, IEEE VIS 2021).

Demo Code

Miscellaneous

VQ-VAE Explainer: Learn the VQ-VAE Implementation with Interactive Visualization

Donald Bertucci and Polo Chau

Interact with and visualize a VQ-VAE (Vector-Quantized Variational Autoencoder) directly in the browser.

Paper Demo Code

Explore ARC-AGI

Donald Bertucci

Visualize the ARC-AGI dataset with live crossfiltering for compression metrics.

Demo Code

VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization

Donald Bertucci and Alex Endert

Interact with and visualize a Variational Autoencoder directly in the browser.

Paper Demo Code

DS569k: Protein Sequence and Function Joint Embeddings Dataset

Donald Bertucci and Alex Endert

Protein embeddings based on function (ProteinCLIP + ESM2) for ~569k proteins from UniprotKB. And web app to query similar proteins given a sequence.

Paper Demo Code

Random Number Generator with Elementary Cellular Automata in Matlab

Donald Bertucci

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

Paper Code

ProteinScatter: Visualizing Structurally Similar Proteins with 3Di Embeddings

Donald Bertucci

Trained a GPT-like model on 300+ thousand protein 3Di sequences (from Foldseek) and visualized embeddings in a 2D scatterplot via UMAP.

Molecular Modeling with Juan Vanegas, Oregon State University (2024). Corvallis, OR

Paper Demo Code

Visualizing Neural Network Compression

Donald Bertucci and Adam Perer

An interactive article exploring how model compression error affects neural network behavior.

Demo Code

Finding the Distance Function in the Poincaré Disk using Stereographic Projection

Donald Bertucci

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

Paper

Software/Packages

nsdget: Quickly use Single Trial Betas and COCO Images from the Natural Scenes Dataset

Donald Bertucci

Python library to easily download and use the single trial betas (1.8mm res) and COCO images from the Natural Scenes Dataset.

Blog Code

DeepLocalizer: A Library to Find Functional Specialization in Deep Neural Networks

Donald Bertucci

Python library to find function specific activations in artificial neural networks using fMRI-like localization.

Blog Code

TensorScript: Tensor Library accelerated by WebGPU

Donald Bertucci

Tensor operations and auto differentiation with custom WebGPU kernels.

Code

FalconVis: A Library to Cross-Filter Billions of Data Entries on the Web

Donald Bertucci and Dominik Moritz

A JavaScript library for visualizing big data on the web with your custom visualizations and scalable data formats.

Demo Code

Skills

Languages Python, Javascript/Typescript, C/C++, Matlab, R, Mathematica, Bash.
ML/AI PyTorch, Jax, TensorFlow, Keras, Scikit-learn, NumPy, CUDA.
Bio/Neuro ChimeraX, Mol*, BioPython, NiBabel, FSL.
Frontend Figma, HTML, CSS, Svelte, React, Vue, Tailwind.
Backend Pandas, FastAPI, Flask, NodeJS, MySQL, DuckDB, PostgreSQL, Assembly.
OS Linux, Git, SSH, FTP, NGINX, Apache, Docker.
HPC Slurm, CUDA, OpenCL, OpenMP, MPI.
Data Vis D3, SVG, Canvas, WebGPU, Vega, Matplotlib, Seaborn, Altair.
Research LaTeX, Figure Design, Statistical Analysis.
Relevant Coursework Machine Learning, Artificial Intelligence, Parallel Programming, Molecular Modeling, Animal Genetics, Human Behavioral Biology, Discrete Math, Linear Algebra I & II, Numerical Linear Algebra, Non Euclidean Geometry, Differential Calculus, Integral Calculus, Vector Calculus, Mathematical Statistics I & II.