Marco K. Carbullido

4 Midden Ln. Tiburon, CA, 94920 (415) 250 7871 |

mcarbullido@tulane.edu github.com/marcocarbullido

EDUCATION

Tulane University | New Orleans, LA Bachelor of Science, Majors:

Neuroscience & Computer Science Coursework: Deep Learning, Intro AI, Genetics, General Biology Lab, Cell & Molecular Biology, Organic Chemistry I & II, Molecular Neurobiology, Systems Neuroscience, Cellular Neuroscience, General Endocrinology, Data Visualization, Computer Systems and Networks, Algorithms, Human Computer Interaction, Capstone I & II

August 2020 - 2024

WORK & RESEARCH EXPERIENCE

Gragert Lab, Louisiana Cancer Research Center | New Orleans, LA

Research Assistant, Deep Learning, Software Development May 2024 – May 2025

Improved protein sequence embeddings via masked-token prediction for UniRef sequences, and trained on structures via distillation with AlphaFold2. Implemented a novel transformer-based architecture for protein b-factor prediction, achieving state-of-the-art performance (PCC>0.8).
Successfully developed and implemented a novel bioinformatics pipeline for protein epitope prediction, combining AlphaFold2 predictions with a deep learning model (including transformer architectures) trained on the majority of the Protein Data Bank for b-factor prediction—extending epitope algorithm scope beyond experimental input.
Architected and developed a web server and standalone web tool implementing state-of-the-art immunology and bioinformatics algorithms for lab and open science use.
Implemented a scalable distributed RESTful API framework for GPU-accelerated computing of computationally intensive tasks, reducing computation time by up to 180x via cloud services.
Delivered useful software for labs researching protein structure-based prediction of CD4+ T-cell epitopes and contributed to advancements in deep learning applications for biology.
Reviewed, synthesized, and communicated the latest scientific literature on protein science, bioinformatics software, and data analysis to cross-functional teams; led group discussions to enhance lab performance.
Independently managed the design and implementation of data analysis software to optimize internal protein analytics, enhancing lab workflow to support any potential protein sequence.
Wrote and contributed to scientific publications and technical reports based on original research, presenting findings to multidisciplinary collaborators.
Collaborated extensively during whiteboard sessions, proposing improvements to CD4+ T-cell epitope prediction algorithms.

Macleod Lab, Tulane University | New Orleans, LA

Data Engineer, Deep Learning Dec 2024 – Ongoing

Led efforts to analyze petabyte-scale, micrometer-resolution 3D brain scanning electron microscope (SEM) microscopy imaging data using transformer models to study cellular response to energy demand in the ventral nerve cord (VNC). Segmented each neuron and its mitochondria to analyze cellular response to energy demand. Also familiar with patch clamp and other electrophysiology techniques.
Set up and managed the entire analysis pipeline for instance segmentation of neurons in the Drosophila VNC using scanning electron microscopy (SEM) images.
Adapted the Flood Filling Network (FFN) approach for 3D vision transformer-based architectures such as SAM2 from Meta to reconstruct sparse neuronal branching and mitochondrial networks for energy density analysis.
Organized and coordinated a large-scale crowdsourcing initiative, engaging tens of thousands of contributors to generate high-quality consensus datasets for training robust machine learning models.
Analyzed mitochondrial distribution, network structure, and size across motor neurons to study relationships between neuronal energetics and morphology.
Segmented and reconstructed neurons in the peripheral nervous system, mapping projections from the VNC for comprehensive structural and functional analysis.

Tulane University | New Orleans, LA

Research Assistant, Computer Vision / Machine Learning Engineer August 2022 – Ongoing (Machine Learning Engineer: Aug 2022 – Feb 2025)

Led automation and scaling of data curation for lab experiments, boosting curation speed and throughput by up to 30x and expanding quantity and quality of research data analyzed.
Developed and deployed custom, combined deep learning models for multimodal (vision + audio) analysis of animal behavior (especially avian mating displays) over thousands of camera trap videos, tracking and annotating complex behavioral datasets.
Organized feedback and input from different research teams to optimize workflows, keep comprehensive records, and make process improvements.
Coordinated data pipeline design and system architecture for robust, publication-ready tools to be used by future research cohorts.
Collaborated closely with academics and researchers, emphasizing interdisciplinary teamwork and technical rigor in all project phases.

Counter Culture Labs | Oakland, CA

The Open Insulin Project, Laboratory Intern May – August 2022

Supported strain engineering by keeping meticulous, detailed records; preparing media and component cells; and performing mini preps, digests, and selective plating while maintaining strict lab protocols for sterile conditions. Includes ELISA assays, pipetting, centrifuge, gene gun, electroporation, western blot, bioreactors, making component cells, incubators.
Became familiar with lab automation equipment and techniques for various fermentation experiment stages, including the use of automation in the workflow.
Conducted and troubleshooted experimental procedures to optimize DNA uptake, successfully switching to a simplified electroporation method to improve results.
Coordinated project timeline collaboratively with scientists over Slack to meet transformation and expression milestones in Pichia.
Routinely collaborated with peers to enhance protocols for open-source, low-cost insulin production and maintained a sterile work environment following rigorous lab practices.
Became familiar with laboratory record keeping and experimental troubleshooting throughout genetic engineering research endeavors.

Nugget Markets | Corte Madera, CA

Cashier May – August 2021

Maintained a highly sanitary and organized store environment during the COVID-19 pandemic.
Efficiently handled customer transactions and adhered to all safety and sanitization protocols.

Rosetta Institute of Biomedical Research | Berkeley, CA

Medical Bioinformatics and Immunology, Summer Program July 2020

Analyzed large public datasets with dedicated bioinformatics tools for gene expression profiling, miRNA targets, protein characterization, and protein-protein interaction networks.
Learned bioinformatics pipeline optimization, SNP analysis, and best practices for data-driven translational research.

LEADERSHIP AND COMMUNITY ACTIVITIES

Amigos De Las Americas | Pérez Zeledón, Costa Rica

Volunteer, July – August 2019

Implemented a variety of infrastructure improvement and community projects in collaboration with local residents.

Bridge The Gap Program | Marin City, CA

Volunteer Tutor/Mentor, October 2018 – May 2019

Co-led academic tutoring and mentoring sessions for students to foster academic engagement and interests.

SKILLS & INTERESTS

Bioinformatics & Lab: Strain engineering, protein characterization, genetic engineering, fermentation, lab automation, scientific literature review, data pipeline development, experimental troubleshooting, laboratory record keeping, technical/scientific report writing, scientific presentation, rapid experimentation, creative thinking, problem solving, methods development, cross-functional collaboration.

Technical: Python, C, C#, C++, JAX, HTML, CSS, Java, Javascript, SQL, Haskell; Django, RESTful APIs; PyTorch, TensorFlow, NumPy; distributed systems, GPU-accelerated computing, authentication systems, cloud services.

Data Science & Machine Learning: Deep neural networks, computer vision, multimodal modeling (audio/vision), large dataset analysis, distributed computation.

Other: Customer service, project management, teamwork and leadership in multicultural settings.