HTML / CSS

Jailynne Estevez

Consulting Drop-In Hours: Fri 3pm-5pm

Consulting Areas: Python, SQL, Stata, HTML / CSS, Javascript, Google AppScripts, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Python Programming, Surveys, Sampling & Interviews, Text Analysis, , Bash or Command Line, Excel, Git or Github, Stata

Quick-tip: the fastest way to speak to a consultant is to first ...

Chirag Manghani

Consulting Drop-In Hours: Wed 1pm-3pm

Consulting Areas: Python, R, SQL, Stata, SAS, LaTeX, HTML / CSS, Javascript, C++, APIs, Cloud & HPC Computing, Cybersecurity & Data Security, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, R Programming, Software Tools, Text Analysis, Web Scraping, Regression Analysis, Software Output Interpretation, Bash or Command Line, Excel, Git or Github, Qualtrics, RStudio, RStudio...

Lauren Chambers

Consulting Drop-In Hours: Wed 11am-1pm

Consulting Areas: Python, R, HTML / CSS, APIs, Data Manipulation and Cleaning, Data Science, Data Visualization, Python Programming, R Programming, Software Tools, Web Scraping, Regression Analysis, Software Output Interpretation, Bash or Command Line, Git or Github, OCR, RStudio

Quick-tip: the fastest way to speak to a consultant is to first ...

Reine Ngnonsse

IUSE Undergraduate Advisory Board
Genetics and Plant Biology

Reine Ngnonsse, an enthusiast for math and technology, delved into tutoring math at a community college through the EOPs program. At UC Berkeley, while pursuing Genetics and Plant Biology, She explored R programming in a CRISPR project. As an intern at Health Career Connection, Reine expanded coding skills in Python, R, and Tableau, igniting a passion for programming. With exposure to Python and Javascript, she can't wait to merge mathematical prowess with coding finesse for innovative solutions.

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.

Larissa Benjamin

Doctor of Public Health Student
Public Health

Larissa Benjamin is a second year Doctor of Public Health (DrPH) student at UC Berkeley. Her research uses a mixed-methods approach to exploring the structural determinants of cardiovascular disease inequities in the rural Southeastern United States, also called the “Stroke Belt.” She is particularly curious about how regional history, geography, and structural racism shape inequitable rural neighborhood risk environments. Larissa earned a BS in Evolutionary Anthropology and English from University of Michigan, and an MPH at UC Berkeley in Health and Social Behavior with a...

Elaine Luo

Instructor
Graduate School of Education

Elaine (Hua) Luo is a PhD candidate in the Graduate School of Education, School Psychology PhD program. Her research interests focus on adolescents’ identity development and well-being under the transactional influence of entities in their socio-ecological systems. In her research, Elaine has utilized not only quantitative but also qualitative and mixed methods to study her research topics of interest. Before coming to Berkeley, Elaine earned her Master’s in Human Development and Psychology from Harvard Graduate School of Education and her Bachelor of Art in Education Sciences from...

Hugh Kadhem

Data Science Fellow
Mathematics

Hugh Kadhem is a Ph.D. student in Applied Mathematics, with broad research interests in computational quantum physics and high-performance scientific computing.

Suraj Nair

Data Science Fellow
School of Information

I am a PhD Student at the School of Information. My research interests lie at the intersection of development economics and machine learning, with a focus on the use of large scale digital data and new computational tools to study pressing issues in global development.