Daniel Chang

Dynamic Nucleic Acid Systems Lab (Elisa Franco)

• Built an automated Python pipeline using Cellpose's pretrained models to segment biomolecular condensates and nuclei in multi-channel Z-stack fluorescence microscopy images (55 slices), replacing a manual labeling workflow.
• Validated pipeline outputs against pre-labeled ROIs from the JABr dataset by computing condensate density, dilute density, and partition coefficients, comparing against established reference values.
• Extended the pipeline to automatically classify condensates as nuclear or cytoplasmic based on spatial overlap with segmented nuclei.

LS 30B: Mathematics for Life Scientists — UCLA

• Led weekly Python lab sections of 30 students and office hours (15–20 students), teaching biological modeling concepts including ODE simulations, trajectory plotting, and eigenvalue analysis with NumPy, Matplotlib, and SciPy.
• Guided non-CS majors through debugging and conceptual understanding, consistently rated for clear explanations connecting code to lecture material.
• Broke complex problems into smaller steps to build student confidence and independent problem-solving skills.

Blueprint

• Developed web and mobile apps for Southern California non-profits alongside designers and developers, delivering features in weekly sprints.
• Turned Figma mock-ups into responsive React components and API endpoints while meeting weekly sprint goals.
• Mentored junior members through internal workshops on React patterns, Git workflows, and deployment best practices.

Self-Employed

• Tutored 10+ students ranging from 3rd grade through high school juniors in English, Math (Algebra, Algebra 2, Trigonometry, Calculus), and AP Biology.
• Designed and assigned weekly homework tailored to each student's level and pace to reinforce lesson material.
• Adapted teaching strategies across a wide age and skill range, building strong rapport and measurable academic improvement.