Bilingual physics graduate from UC Berkeley with 8+ years of experience tutoring STEM subjects across educational levels and platforms. Hands-on experience in laboratory instrumentation, circuit analysis, and data modeling using Python and Tableau.
Transforming complex physics concepts into innovative data solutions
UC Berkeley Physics graduate with comprehensive education in quantum mechanics, thermodynamics, classical mechanics, electromagnetism, and scientific computing. Strong foundation in mathematical modeling and experimental physics.
8+ years of experience tutoring STEM subjects across educational levels and platforms including WyzAnt, BetterGradez, and institutional settings. Specialized in adapting communication strategies to diverse student needs and learning styles.
Professional experience in AI content evaluation and data annotation with Scale AI and MindNT. Proficient in Python, data modeling using Tableau, and laboratory instrumentation including circuit analysis and spectroscopy.
Academic foundation in physics and mathematics
Comprehensive physics education with focus on theoretical foundations and experimental methods.
Strong foundational education in mathematics and physics, preparing for advanced studies at UC Berkeley.
Cutting-edge research combining physics and machine learning
Designed and analyzed analog/digital circuits using oscilloscopes, function generators, and Multisim. Modeled sensor behavior and constructed amplifier circuits with impedance matching.
Calibrated NaI detectors with known radiation sources to identify energy peaks. Applied Gaussian fitting and statistical analysis to evaluate spectral resolution and detector efficiency.
Explored hyperfine structure in rubidium using magnetic fields and optical transitions. Automated data analysis in Python and calculated nuclear g-factors and relaxation times.
Developed Python-based numerical solver using Runge-Kutta method to simulate chaotic motion. Demonstrated sensitivity to initial conditions and linked to classical chaos theory.
Conducted nanoscale imaging using AFM to observe surface topology and mechanical behavior. Investigated surface roughness, adhesion forces, and sample stiffness.
Comprehensive toolkit for data science and research
Professional journey in AI and education
Interested in collaborating on machine learning projects, quantum research, or AI applications? Let's discuss how we can work together.
© 2025 Angel Michel Yam. UC Berkeley Physics Graduate & Data Scientist.