Javascript

Chirag Manghani

Consultant
School of Information

Chirag is a 2nd year graduate at the I-School. Proficient in Python, Java, R, and SQL, he navigates software application development, machine learning and data science. His keen interest lies in data analysis and statistical methods, driving him to bridge theory and practice seamlessly. Chirag's dedication to excellence, adaptable mindset, and innate curiosity define him as a dynamic problem solver in the ever-evolving tech landscape.

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...

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.

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.

María Martín López

Data Science Fellow
Psychology

María Martín López is a PhD student in the Cognition area within the Department of Psychology. Her research relates to cognitive computational and quantitative models of individual differences in behaviors, thoughts, and emotions. She is particularly interested in how we can create and leverage novel algorithms to understand, measure, and predict processes relating to externalizing psychopathology (e.g. impulsivity, aggression, substance use). She answers these questions using a range of computational and quantitive models including AI, NLP, SEM, time series analysis, multi-level...

Mapping Time-Series Satellite Images with Google Earth Engine API

July 17, 2023
Meiqing Li
by Meiqing Li. Remote sensing imagery has the potential to reveal land use patterns and human activities at a planetary scale. For example, nighttime light intensity extracted from can shed light on spatial patterns of human activities and settlements, especially in places where traditional data are scarce. This blog post introduces Google Earth Engine (GEE) as a general purpose tool to extract time-series remote sensing data from GEE data catalog. I walk through using GEE to obtain data, filter by time and geographic region, and visualize it on static and interactive maps.

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.

Jailynne Estevez

Consultant
Info & Data Science MIDS

Jailynne Estevez is a Data Analyst and a prospective Masters in Information and Data Science candidate at UC Berkeley. With a bachelor's in Public Policy, she brings a diverse skill set to her pursuits, demonstrating aptitude in data analysis and programming.