Donny Bertucci

Currently working on predicting and exploring biology at Axiom Bio.
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

Experience

PRESENT

Axiom Bio | axi.om, Engineer, Member of Technical Staff

Building interactive tools and ML/AI models to predict biology.
9.2023 – 6.2024

Georgia Institute of Technology | Visualization Lab, Graduate Research Assistant

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 | Venom Biochem Lab, Research Assistant

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

Carnegie Mellon University | Data Interaction Group, Research Assistant

Summer 2023
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
Cross-filtering for large-scale data with Falcon [_] with Dr. Dominik Moritz. Researched human-centered ways to evaluate Machine Learning model behavior within Zeno [_] with Dr. Alex Cabrera.
Summer 2022
Carnegie Mellon HCII Summer Research Program: developed user interfaces to interactively discover poor behavior in neural networks [_]. Advised by Dr. Alex Cabrera and Dr. Adam Perer. Program led by Dr. Laura Dabbish.

Oregon State University | Data Interaction and Visualization Lab, Research Assistant

8.2021 – 5.2022
Developed user interfaces to visualize large data and interpret complex machine learning models [_, _]. Published to ICAPS and IEEE VIS. Mentored and advised by Dr. Minsuk Kahng.
Summer 2021
EECS Summer Research Cohort to improve research presentation skills mentored by Dr. Alan Fern, Dr. Yue Cao , Dr. David Hendrix, and Dr. Patrick Donnelly.
2.2021 – 6.2021
URSA Engage Undergraduate Research Program: developed interactive interfaces to visualize difficult concepts in learned neural networks and published to VISxAI workshop [_, _]. Advised by Dr. Minsuk Kahng.

Education

8.2024 – 11.2024

Ph.D. Computer Science (incomplete)

Georgia Institute of Technology
9.2020 – 6.2024

B.S. Computer Science

Oregon State University
Degree Focus: Artificial Intelligence, Minor: Mathematics

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.

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.
Paper Demo Code
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
Paper Demo Code
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).
Paper

Workshop

W4

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
W3

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
W2

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
W1

An Interactive Introduction to Autoencoders

Donald Bertucci
Workshop on Visualization for AI Explainability (VISxAI, IEEE VIS 2021).
Demo Code

Miscellaneous

M8

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
M7

Explore ARC-AGI

Donald Bertucci
Visualize the ARC-AGI dataset with live crossfiltering for compression metrics.
Demo Code
M6

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
M5

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
M4

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
M3

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
M2

Visualizing Neural Network Compression

Donald Bertucci and Adam Perer
An interactive article exploring how model compression error affects neural network behavior.
Demo Code
M1

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

S4

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
S3

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
S2

TensorScript: Tensor Library accelerated by WebGPU

Donald Bertucci
Tensor operations and auto differentiation with custom WebGPU kernels.
Code
S1

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

References

Dr. Minsuk Kahng

Computer Science Professor at Yonsei University
minsuk.com

Dr. Alex Cabrera

Founding Engineer at Axiom Bio
cabreraalex.com

Dr. Adam Perer

Computer Science Professor at Carnegie Mellon University HCII
perer.org

Dr. Dominik Moritz

Computer Science Professor at Carnegie Mellon University HCII and Apple ML Research Scientist
domoritz.de

Dr. Nathan Mortimer

Biochemistry Professor at Oregon State University
biochem.oregonstate.edu/directory/nathan-mortimer

Dr. Alex Endert

Computer Science Professor at Georgia Institute of Technology
va.gatech.edu/endert