If you want to wrap your mind around the concept of blockchain and cryptocurrency, you should look at the history and usage of the “rai stone,” according to Pranay Anchuri, data scientist at Princeton University.

In the Micronesia area of the Pacific Ocean, above Australia and Papua New Guinea, there is the tropical island Yap where…

The application of machine learning is growing across multiple disciplines, from astrophysics to politics. At first, it can seem challenging to know where to start or how to use machine learning if you have no prior background in the area.

To address this issue, the Center for Statistics and Machine Learning (CSML) held a three-hour…

Waheed U. Bajwa’s research is at the intersection of statistics, machine learning and signal processing. The latter discipline is an engineering subfield that concerns itself with analyzing or processing images, sound and other data.

Interview features three current Humanities Data Teaching Fellows—Akrish Adhikari (G4, French and Italian), Gyoonho Kong (G5, German), and Daniel Persia (G2, Spanish and Portuguese)—about their expectations for the fellowship, which included working with the Center for Digital Humanities and the Center for Statistics and Machine Learning to develop modules for the undergraduate course “Introduction to Data Science” (SML 201).

Singer’s research is divided into two main components: one - developing algorithms and advanced computational methods to analyze data, and two – using these tools to determine the three-dimensional structures of molecules. “The first component is more theoretical and foundational. I develop algorithms and do mathematical analysis of existing and new algorithms to analyze data. This data can be quite complex with very high dimensionality. This is data with a large amount of noise or the data set can be quite large. So, my lab members and I come up with solutions or tools to process and analyze this data. Such contextualization programing is one part of my research,” he said.

With a return to campus this fall, the Center for Statistics and Machine Learning’s flagship undergraduate course, SML 201: Introduction to Data Science, opened its enrollment to more than 150 students, the highest in its history and…

Many researchers at Princeton University and elsewhere develop their own software programs to help them elucidate complex processes and solve interesting problems, from biomedicine to water management. But when it comes to making the code available to the wider research community, these prototype programs need to make a…

As part of a major new initiative in interdisciplinary data science, Princeton University is undertaking a search for faculty members at all academic ranks across all areas of science, engineering, social science, and humanities. This initiative will involve multiple faculty hires over the next several years.  We are particularly interested in…