Eight Research Projects Receive DataX Funding
March 25, 2022
Written by Sharon Adarlo

Eight new interdisciplinary research projects have won seed funding from Princeton University’s Schmidt DataX Fund, marking the third round of grants undertaken by the fund. The fund, supported through a major gift from the Schmidt Futures Foundation, provides grants to explore using artificial intelligence and machine learning to accelerate discovery.

The eight funded projects involve 13 faculty across seven departments and programs, from computer science to Near Eastern studies.

CSML faculty featured in Robotics issue of EQuad News
March 21, 2022
Written by Sharon Adarlo

Professors Olga Russakovsky, Naomi Ehrich Leonard, Ryan Adams, Jaime Fernandez Fisac and Anirudha Majumdar are featured in the latest issue, which focuses on how robotics is spurring innovation and making inroads into our everyday lives.

Open workshop allows scholars to turbocharge research with modern tools
March 15, 2022
Written by Sharon Adarlo

On March 4th, DataX sponsored part one of a workshop on cloud computing with a focus on setting up an integrated development environment for local and cloud computing.Twenty people attended, both in person and via Zoom. Part two of the workshop will be on April 1st, which will show attendees on how to build virtual machines in Microsoft Azure and access these using PyCharm. Read more about the March 4th workshop and how to register for the next one.

Joyce Luo: using machine learning to help improve population health
March 7, 2022

For her CSML independent work project, Joyce Luo is working on a study that uses machine learning to model and analyze the opioid epidemic in the United States and then using that model to inform the optimization of a specific policy intervention. For the scope of this project, she is attempting to optimize the location of opioid treatment facilities that offer medication assisted treatment across the country.

Tavarria Zeigler: probing political and social issues with data science
March 2, 2022
Written by Sharon Adarlo

Within her major, Tavarria Zeigler is focusing on political theory. She became interested in statistical analysis in the context of politics through POL 345Introduction to Quantitative Social Science with Rocío Titiunik, professor of politics. She is now well on her way to fulfilling her CSML certificate requirements.

Edge AI detects COVID-19 from smartwatch sensors
Feb. 28, 2022
Written by Molly Sharlach, Office of Engineering Communications

Combining questions about a person’s health with data from smartwatch sensors, a new app developed using research at Princeton University can predict within minutes whether someone is infected with COVID-19.

This new breed of diagnostic tool stems from research led by 

Students encouraged to develop machine learning algorithms for international “Climate Hack” competition
Feb. 23, 2022
Written by Sharon Adarlo

Princeton Data Science Club (PDS) encourages undergraduate and graduate students to participate in Climate Hack.AI, an international competition among 25 top universities in the United States, Canada and the United Kingdom.

The goal of the competition is to use machine learning methods to develop the best predictive algorithm to…

Princeton Talks: Brandon M. Stewart on Text as Data
Feb. 10, 2022

In this recorded talk, Brandon M. Stewart introduces us to the interdisciplinary field known as: Text as Data. The study of human behavior is changing. In the last two decades, there has been an avalanche of new data: emails, tweets, Reddit posts, press releases and written books have all exploded. Social scientists realize they have a new…

Ryan Adams is working to improve manufacturing robots
Feb. 9, 2022
Written by John Sullivan

Manufacturing robots are a modern wonder, building everything from packaged food to microchips.

Ryan Adams, a professor of computer science, agrees that these machines are the foundation of the modern economy, but he thinks there is a lot of room for improvement.

Empowering young AI researchers, and advancing robots’ powers of perception
Feb. 7, 2022
Written by Molly Sharlach, Office of Engineering Communications

Olga Russakovsky’s Princeton Visual AI Lab develops artificial intelligence (AI) systems with new capabilities in computer vision, including automated object detection and image captioning.

Her team also creates tools to identify and mitigate biases in AI systems, and promote fairness and transparency.