Education
This section covers my academic background in Computer Science, Machine Learning, and interdisciplinary studies as well as my awards and certifications.
Academic Background
Master of Science in Computer Science
Georgia Institute of Technology
Currently pursuing a graduate degree in Machine Learning and Artificial Intelligence at one of the top computer science programs in the United States. Core-requirement courses not included below.
Relevant Coursework
- Knowledge-Based AI: This course focused on building AI agents capable of human-like intelligence and gaining insights into human cognition. Core topics such as incremental concept learning, and explanation-based learning; common tasks such as diagnosis, and design; and advanced topics such as analogical reasoning and meta-reasoning.
- Natural Language Processing: Modern data-driven techniques for natural language processing. The course moved from shallow bag-of-words models to richer structural representations of how words interact to create meaning, including language models, attention, and comprehension.
- Human-Computer Interaction: Principles of human–computer interaction framed through cognition, perception, and decision-making. The course examined users' attention, working memory, and cognitive load during interactions with computers, paired with hands-on projects in need-finding, user evaluation, feedback, and iterative design.
- AI, Ethics, and Society: Covered how artificial intelligence and machine learning systems impact individuals and society, with an emphasis on fairness, bias, and ethical deployment. The course taught techniques in quantifying and mitigating algorithmic bias while considering legal and ethical implications.
- Machine Learning for Trading: Application of machine learning based trading strategies from information gathering to market orders. This course delved into statistical approaches like linear regression, Q-Learning, KNN, and regression trees and how to apply them to actual stock trading situations.
Bachelor of Arts
Case Western Reserve University
Majors:
Computer Science Economics PhilosophyMinors:
Artificial Intelligence Political Science EthicsCompleted an intense interdisciplinary study with a technical focus in Data Science and software and an analytical focus on the economy, state and society. Many courses could not be included below due to volume. All courses below were taken at the Junior-Senior level unless otherwise noted.
Computer Science Coursework
- Machine Learning (Graduate-level): Modern ML methods, including SVMs, NNs, decision trees, and ensembles
- Sequential Decision Making (Graduate-level): Reinforcement learning, knowledge representation, and planning
- Database Systems: SQL, distributed systems, relational database design and optimization
- Probability Theory: Mathematical foundations of probability theory
Economics Coursework
- Advanced Econometrics (Graduate-level): Statistical modeling and regression analysis for economic data
- Game Theory: Strategic decision-making, Nash equilibria, and mechanism design
- Microeconomic Theory: Consumer behavior, market structures, and welfare economics
- Macroeconomic Theory: National economic models, monetary and fiscal policy
Philosophy Coursework
- Civil Liberties (Pre-law): 1st amendment freedom of religion, speech, press, assembly and association
- Constitutional Law (Pre-law): Judicial review, separation of powers, due process, and equal protection
- Modern Philosophy: Consciousness, philosophy of the mind, and the nature of cognition
- Social Justice in Latin America: Historical identity, revolution, democracy, and populism
- Global Poverty: Theories of harm, poverty, and duty in global relations
- Religion and Human Rights: Theoretical religious foundations and applications in society
Academic Awards & Honors
Scholar
Jack Kent Cooke Foundation
Selected as an Undergraduate Scholar in 2018 and Graduate Scholar in 2024
Scholar
Hispanic Scholarship Fund
Selected as an HSF Scholar in 2020
Technical Skills
Programming Languages
Python, Java, Swift, Kotlin, C++, JavaScript, R, SQL, Stata
Machine Learning & AI
TensorFlow, PyTorch, Scikit-learn, Keras, OpenCV, NumPy, Pandas, SciPy, NLTK
Data & Analytics
SQL, Tableau, Snowflake, Qualtrics, PySpark, Excel, Statistical Modeling
Development Tools
Git, AWS, Jupyter, VS Code, Prompt and Context Engineering
Specialized Areas
Computer Vision, Natural Language Processing, Reinforcement Learning, Deep Learning, Statistical Analysis, Data Engineering, Algorithm Design, Knowledge-Based AI
Certifications & Additional Training
Google Advanced Data Analytics Professional Certificate
- Statistical analysis and hypothesis testing
- Regression modeling and machine learning
- Data cleaning and exploratory data analysis
- Data visualization and stakeholder communication
- Project planning and execution in data science