R

Pratik Sachdeva, Ph.D.

Availability: By appointment only

Consulting Areas: Python, R, SQL, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Deep Learning, Machine Learning, Python Programming, R Programming, Regression Analysis, Hierarchical Models, Means Tests, Software Output Interpretation, Bash or Command Line, Excel, Git or Github, RStudio

Tom van Nuenen, Ph.D.

Availability: By appointment only

Consulting Areas: Python, R, SQL, LaTeX, HTML / CSS, Javascript, Julia,Data Manipulation and Cleaning, Data Science, Data Visualization, Digital Humanities, Machine Learning, Mixed Methods, Natural Language Processing, Python Programming, Qualitative methods, R Programming, Surveys, Sampling & Interviews, Text Analysis, Web Scraping,Regression Analysis,Bash or Command Line, Excel, Gephi, Git or Github, NVivo, Qualtrics, RStudioFairness, Perceptions of AI, Hermeneutics

Pratik Sachdeva, Ph.D.

Data/Research Scientist, Senior Consultant, and Senior Instructor

I am staff at the Social Sciences D-Lab. I received my Ph.D. in the Physics department at Berkeley. My research lies in the realm of theoretical/computational neuroscience, which aims to use mathematical and computational tools to better understand how neural systems operate and process information. My projects include using information-theoretic techniques to study how neural variability impacts information processing in neural circuits and investigating the statistical issues that impede the interpretation of parametric models of neural activity.

Beyond research, I'm
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Yue Lin

Data Science Fellow 2024-2025
Political Science

Yue is a Ph.D. student in Political Science at the University of California, Berkeley, with a Designated Emphasis on Political Economy. Using mixed methods, she studies foreign lobbying, geopolitical risk, and economic security to understand when, how, and why multinational corporations become the targets and weapons of state power rivalry.

Taesoo Song

Data Science Fellow 2024-2025
City and Regional Planning

Taesoo is a Ph.D. candidate in the City and Regional Planning department at the University of California, Berkeley. He studies the nexus of housing policy, neighborhood change, and residential outcomes for low-income and minority households.

His dissertation aims to reassess the prevailing narrative that Asian Americans face minimal barriers in the housing market using quantitative and qualitative methods. Taesoo has worked with the Terner Center for Housing Innovation and the Urban Displacement Project at UC Berkeley, as well as the Seoul Institute in South Korea.

Paul Salamanca

Instructor
Sociology

I am a PhD student in sociology. I study imperialism, race, and gender, with a historical focus on the colonial Philippines. In my free time, I like to cook and bake.

Alex Stephenson

Senior Data Science Fellow
Political Science

I am a Ph.D. Student in the Travers Department of Political Science. My primary research interests are military organizations, policing, the determinants of political violence, and causal inference. I am also interested in creating tools to make software easier to use for non-technical political scientists.

Amanda Glazer

Instructor
Statistics

Amanda is a PhD candidate in the statistics department at Berkeley. Her research focuses on causal inference with applications in education, political science and sports. Previously she earned her Bachelor’s degree in mathematics and statistics, with a secondary in computer science, from Harvard.

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.

R Fundamentals: Parts 1-4

August 20, 2024, 9:00am
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.