Matias Ignacio Pinto Chavez
Durham
Summary
Analytical undergraduate specializing in Machine Learning and Statistical Theory. Developed predictive frameworks and conducted advanced data analysis, including qualitative modeling and toolkit development. Technical expertise in Python and R, supported by a strong foundation in Real Analysis, Inference, and Natural Language Processing.
Overview
2
2
years of professional experience
1
1
Certification
Work History
Research Assistant
Nicholas School Of Environment, Duke University
Durham
11.2025 - Current
- Cleaned and analyzed qualitative workshop transcripts using MAXQDA, identifying key themes for thematic analysis.
- Collaborated with research team to identify key themes and insights from community engagement workshops.
- Conducted literature review to assess public perception of water reuse and inform community engagement strategies.
- Assisted in preparation of peer-reviewed journal manuscript by drafting sections, formatting references, and creating tables and figures.
Researcher
Computer Sciences Department, Duke University
Durham
01.2026 - 05.2026
- Fine-tuned LLaMA models with LoRA to enhance instruction following and code generation accuracy.
- Analyzed performance trade-offs across tasks and optimized hyperparameters, resulting in improved model outcomes.
- Designed multi-task training pipeline integrating diverse datasets and assessed models using automated benchmarks.
- Developed training and evaluation workflows in Python and Tinker platform to streamline model assessment.
Research Assistant
Bass Connection, Duke University
Durham
06.2025 - 04.2026
- Integrated dMRI and fMRI data to investigate brain network topology, correlating findings with AD pathology and cognitive performance outcomes.
- Developed predictive frameworks using machine learning and statistical methods to enhance analysis of high-dimensional neuroimaging data.
- Applied computational topology and geometry to analyze MRI-based biomarkers, contributing to early detection of Alzheimer's.
Undergraduate Research Fellow
Department of Statistics, Duke University
Durham
05.2025 - 06.2025
- Selected for competitive two-week mentored research workshop funded by Trinity Research Enhancement Grant.
- Analyzed 2022 Durham Resident Survey to assess quality of life perceptions across demographics, identifying key areas for community improvement.
- Utilized R for data wrangling, visualization, and ordinal logistic regression analysis.
- Explored spatial trends using zip code-based clustering techniques to reveal demographic patterns and inform research conclusions.
- Collaborated with graduate student mentors and faculty PI in a focused research team, contributing to project development and knowledge exchange.
- Developed research communication and mentorship skills; achieved CITI certification for responsible conduct.
Global Fellowship Member
Duke International Student Center
Durham
01.2025 - 05.2025
- Completed intensive program on intercultural and leadership development through eight bi-weekly training sessions, enhancing personal and peer understanding.
- Supported global programs and events, fostering engagement within Duke's international community.
- Liaised with visiting scholars to foster cross-cultural understanding.
- Developed resource guide and social media campaign as part of final service project, improving access to resources for international students.
Data Analyst Intern
Duke Career Center
Durham
02.2025 - 04.2025
- Developed visualizations and statistical reports with Tableau and Excel, enhancing insights for long-term engagement strategies.
- Analyzed 1,000 student engagement data points, ensuring data accuracy for effective dashboard integration.
- Interviewed staff to clarify data analysis processes, establishing clear engagement metrics for improved tracking.
- Refined workflows for automated data cleaning and reporting.
Researcher
Computer Sciences Department, Duke University
Durham
08.2024 - 12.2024
- Developed persistent homology algorithm for 3D facial feature segmentation, enhancing accuracy of facial recognition systems.
- Implemented k-d tree neighbor searching and region-growing techniques, improving scalability of 3D point cloud segmentation processes.
- Evaluated segmentation accuracy with Wasserstein distance, refining mesh resolution and topological features for better analytical outcomes.
Education
Bachelor of Science - Computer Sciences, Statistical Sciences
Duke University
Durham, NC05-2027
High School Diploma -
International School Nido De Aguilas
Santiago, Chile05-2023
Skills
- Programming: Python, C/C, Java
- Machine Learning & AI: Natural Language Processing (NLP), TensorFlow, Random Forests, Cross-validation, Data Mining
- Research methodologies
- Statistics & Mathematics: Generalized Linear Models (GLMs), PCA, Regression Analysis, Probability Theory, Cluster Analysis
- Technical Tools: Data Visualization (Matplotlib, Tableau), MAXQDA (for qualitative analysis)
Languages
English
Proficient (C2)
C2
Spanish
Native
Native
German
Intermediate (B1)
B1
Certification
- Undergraduate Student Responsible Conduct of Research
Timeline
Researcher
Computer Sciences Department, Duke University
01.2026 - 05.2026
Research Assistant
Nicholas School Of Environment, Duke University
11.2025 - Current
Research Assistant
Bass Connection, Duke University
06.2025 - 04.2026
Undergraduate Research Fellow
Department of Statistics, Duke University
05.2025 - 06.2025
Data Analyst Intern
Duke Career Center
02.2025 - 04.2025
Global Fellowship Member
Duke International Student Center
01.2025 - 05.2025
Researcher
Computer Sciences Department, Duke University
08.2024 - 12.2024
Bachelor of Science - Computer Sciences, Statistical Sciences
Duke University
High School Diploma -
International School Nido De Aguilas