Gabriel C. Fonseca
Pittsburgh, PA,USA
Overview
2
2
years of professional experience
Work History
Graduate Teaching Assistant - Machine Learning
Carnegie Mellon University
01.2024 - 05.2024
- Conducted office hours to help students understand complex concepts more clearly.
- Collaborated with fellow teaching assistants to provide engaging course resources and exam design, leading to improved academic outcomes.
Medical Research Internship
University Of Pittsburgh Medical Center
05.2023 - 08.2023
- Applied spatial transcriptomics DSP to study gene expression in segmented cancer tissue
- Assisted in research support of data processing, developing R and Python Conda environments through remote HPC servers
- Enhanced complex research analysis by integrating statistical techniques, such as LME models and PCA, into single SOP pipeline
Scientific Associate, Bioanalysis
Worldwide Clinical Trials
12.2021 - 07.2022
- Enhanced research quality through meticulous data collection, analysis, and interpretation.
- Maintained accurate records of experimental data, ensuring timely communication of results to team members.
- Ensured safe working environment by adhering to laboratory protocols and safety regulations.
Education
Master of Science - Computational Biology
Carnegie Mellon University
Pittsburgh, PA05.2024
Bachelor of Science - Biology
University of Texas At Austin
Austin, TX05.2021
Skills
- Programming and Software: R, Python, Go, PySpark, SQL, Pymol, ApE, Web development, GitHub, BLAST, AWS, Google Cloud and Collab, HPC (cloud computing), VS Code, Bioinformatics, Algorithms, Pytorch
- Machine Learning: Classical Machine Learning, PCA, Clustering, Generative AI, Deep Learning, Artificial Intelligence, NLP, CNN, Active Learning
Projects
- Built a population dynamics web app using HTML, JavaScript and Go
- Demonstrated link between neural cell types and brain size using R phylom statistical analysis
- Analyzed COVID-19 data via time-series machine learning methods to predict future trends
- Studied protein-protein interactions in human spliceosomes in a wet lab setting
- Explored relevant literature and created research proposals using molecular biology data
- Applied novel generative diffusion model for enhancer sequence generation of spinal cord cell types
- Developed novel active learning methods for data imputation of medical record data
Timeline
Graduate Teaching Assistant - Machine Learning
Carnegie Mellon University
01.2024 - 05.2024
Medical Research Internship
University Of Pittsburgh Medical Center
05.2023 - 08.2023
Scientific Associate, Bioanalysis
Worldwide Clinical Trials
12.2021 - 07.2022
Master of Science - Computational Biology
Carnegie Mellon University
Bachelor of Science - Biology
University of Texas At Austin
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