Abhishek Nagaraj, Professor

Closed (1) Impact of Mapping in the Age of Discovery (1600-1800)

Applications for Spring 2019 are now closed for this project.

While we have a clear idea of what the world looks like today, the map of the modern world was a mystery to Europeans in the middle ages. It was only in the age of discovery that sailors and explorers cross uncharted waters and filled out the map of the world as we know it today. What were the main changes in our knowledge of the globe? And what were the impacts of these maps on shipping patterns and shipping accidents? We are looking to investigate these questions by building a unique dataset and analyzing quantitative data on the impact of mapping on shipping activity.

We are looking for motivated research assistants who can help us collect, clean, analyze and interpret datasets of geographic information on this topic. We will also be looking into historical archives and trying to find novel sources of data. We are looking for someone with an interest in Economic History as well as in data analysis and data science.

Students with experience in data analysis / economics are encouraged to apply. Expertise in analyzing data using Stata is a bonus.

You may contact me at nagaraj@berkeley.edu for any questions or concerns.


You will be involved with literature review, finding new sources of data and creating datasets from unstructured data, structuring and cleaning these data using python and analyzing them using STATA. You will perform analyses and jointly work with me towards understanding the impact of better maps on shipping outcomes.

Qualifications: The following skills will be needed and familiarity with them is preferred: a) interest in economic history and the history of navigation b) data collection / cleaning skills c) regression analysis using STATA (preferred)

Weekly Hours: 9-11 hrs

Closed (2) Weather Innovation: Big data analysis of weather predictions

Applications for Spring 2019 are now closed for this project.

How much has weather prediction improved? Which places have benefited most from improvements in prediction? What are the causes of improved prediction and what are the consequences of better weather prediction for the economy? We are working on a number of questions in around the science of weather prediciton

You will analyze troves and troves of data on weather predictions and help us develop summary statistics, analysis around weather. We are looking for those with some background and interest in meteorology to perform fieldwork in this area and interview scientists who work on weather prediction.

Qualifications: URAP will need to be familiar with regression analysis and summary statistics using R/STATA. Some knowledge of python / command line data manipulation is also desired. Experience with analysis of large datasets is a big plus.

Weekly Hours: 9-11 hrs

Related website: http://www.abhishekn.com

Closed (3) Quantifying Innovation in Machine Learning/Computer Vision Algorithms

Applications for Spring 2019 are now closed for this project.

In this project, we are interested in understanding algorithms in the area of computer vision. Through an analysis of different online datasets we will uncover how the field has changed over the decades and how technological improvements have improved the quality of object recognition in computer vision algorithms.

You will be involved in quantiative "data science" research around analyzing computer vision algorithms / machine learning innovation.

Qualifications: URAP will need to be familiar with regression analysis and summary statistics using STATA/R. Some knowledge of python / command line data manipulation is also desired. Interest in computer vision / machine learning history is a bonus.

Weekly Hours: 9-11 hrs

Related website: http://abhishekn.com