layout |
---|
homepage |
Hi! I’m Richard, a junior from the Northern Mariana Islands studying CS and Data Science at UC Berkeley. My interests lie at the intersection of data science, software engineering, and user-experience design, with a focus on creating accessible, inclusive, and impactful technology. As a Pacific Islander in these fields, I aim to lead data-driven projects focused on sustainable development and social impact across the Pacific.
Beyond my academics and research, I am dedicated to finding innovative ways to make data science education accessible to everyone. As a UGSI for Data 8, "Foundations of Data Science," I lead weekly discussions for around 30 students, hold office hours for over 350 students, and guide labs to ensure understanding of Python and Jupyter Notebook. For further details on my teaching experience, please visit the teaching section.
Please feel free to feel reach out to me via email or LinkedIn!
- Lead sections of 30+ students through weekly labs and discussion sections in Data 8, ”Foundations of Data Science,” using Python and JupyterLab to master programming and data analysis skills through hands-on analysis of diverse real-world datasets.
- Provide personalized guidance during office hours, ensuring student comprehension of complex topics and facilitating their success in the course.
- Collaborate closely with professors to align course content with learning objectives, integrating inferential thinking, computational thinking, and real-world relevance into all instructional materials.
Course materials are available here.
View my students' instructor evaluations here.
- Work together with a group of 3-4 Tuskegee students within the Tuskegee Scholars program to explore a particular case study in data.
- Design a piece of curriculum for a future Data 6 course, an introduction to computational thinking and quantitative reasoning.
- Participate in project supervision, worksheet development, and Python debugging.
- Meet regularly with faculty Program Coordinator.
- Lead programming for a two-week coding bootcamp for the Tuskegee Scholars program, which is modeled off of the first two weeks of CS61A and Data 8 material.
- Run office hours to assist students in completing programming labs.
- Meet regularly with faculty program directors to ensure the success of students.
- Provide academic support to students enrolled in the Data Scholars program for historically underrepresented students in Data 8, "Foundations of Data Science," through a weekly Foundations workshop, dedicated office hours, and exam prep sections.
- Consuted with lead instructors to practice effective pedagogy and refine course materials on a weekly basis.
Course materials are available here.
View my students' instructor evaluations here.
- Provided weekly assistance to 45 students enrolled in Data Scholars program for underrepresented and nontraditional students every week in lab with questions about discussion worksheets, Jupyter Notebook assignments in Python, projects, and other course materials in Data 8.
- Met with a shadow Undergraduate Student Instructor (uGSI) throughout the semester to practice and reflect on personal pedagogy skills and professional development.
Course materials are available here.
- Machine Learning Applications: Exploring how machine learning can create meaningful impact in areas like sustainable development, community health, and social justice. I’m particularly interested in making these tools accessible and relevant to underrepresented communities.
- Human-Computer Interaction: Designing user-centered technologies that bridge technical innovation and cultural contexts, with a focus on creating intuitive tools for community engagement and advocacy.
- GIS and Spatial Data Analysis in the Pacific: Using geospatial analysis to highlight stories, challenges, and opportunities within Pacific Islander communities. I’m passionate about mapping initiatives that preserve cultural narratives and inform sustainable policy.
- Policy and Advocacy Through Data: Combining technical insights with advocacy to drive data inclusivity and equitable access to technology, particularly for Indigenous and underserved populations.
{% include_relative _includes/publications.md %}
- CS 61A: Structure and Interpretation of Computer Programs
- CS 61B: Data Structures
- CS 70: Discrete Mathematics and Probability Theory
- CS 170: Efficient Algorithms and Intractable Problems
- CS 188: Introduction to Artificial Intelligence
- DATA 8: Foundations of Data Science
- DATA 100: Principles and Techniques of Data Science
- DATA 101: Data Engineering (in progress)
- DATA 104: Human Contexts and Ethics of Data (in progress)
- MATH 1B: Calculus
- MATH 53: Multivariable Calculus
- MATH 54: Linear Algebra and Differential Equations
- CS 375: Teaching Techniques for Computer Science
- DATA 198: Directed Group Studies for Advanced Undergraduates
- POLISCI 5: International Relations
- AFRICAM 5A: African American Life and Culture in the United States
- ESPM 50AC: Introduction to Culture and Natural Resource Management
- COGSCI 127: Cognitive Neuroscience
- NUSCTX 10: Introduction to Human Nutrition