Columbia University Data Science Institute is pleased to announce that the Data Science Institute (DSI) and Data For Good Scholars programs for Fall 2020 are open for application.

The goal of the DSI Scholars Program is to engage Columbia University’s undergraduate and master’s students in data science research with Columbia faculty through a research internship. The program connects students with research projects across Columbia and provides student researchers with an additional learning experience and networking opportunities. Through unique enrichment activities, this program aims to foster a learning and collaborative community in data science at Columbia.

The Data For Good Scholars program connects student volunteers to organizations and individuals working for the social good whose projects have developed a need for data science expertise. As “real world” problems with real world data, these projects are excellent opportunities for students to learn how data science is practiced outside of the university setting and to learn how to work effectively with people for whom data science sits outside of their subject area.

Continue reading

Immune checkpoint blockade therapy has shown successful clinical outcomes in the treatment of various solid tumors such as head and neck squamous cell carcinoma (HNSCC), melanoma, non-small cell lung cancer (NSCLC) and others. However, immune checkpoint inhibitors work best in patients who exhibit certain tumor biomarkers. In a collaboration with the Department of Hematology Oncology, the Department of Systems Biology, and the Mailman School of Public Health at Columbia University we aim to identify biomarkers which are associated with treatment outcome in patients with solid tumors who underwent immunotherapy. The project includes bioinformatic analysis of sequencing data. Mentoring and training will be provided.

Continue reading

Freshwater supply is critical for managing and meeting human and ecological demands. However, while stocks of water in both natural and artificial reservoirs are helpful for increasing availability, droughts and floods, as well as whiplash events affect reliability on these systems, posing grave consequences on water users. This risk is particularly salient in the state of California, where many local communities have been plagued by extreme hydrological events. In this current research, we contribute to California’s Water Data Challenge effort where a diverse group of volunteers convened to form a multi-disciplinary team that addresses the crucial issues of extreme events in California using data science approaches. Members include researchers and professionals who come from a range of backgrounds representing academia and private sectors. We combine a range of publicly available datasets with Machine Learning (ML) techniques to explore predictability of extreme events during California’s water years. More specifically, we use a variety of water districts and showcase how ML prediction models are not only able to predict the flow of water at varying time horizons, they capture uncertainties posed by the climate and human influences.

Continue reading

COVID-19 has changed the way we use the internet, from taking classes to social interactions and entertainment. The FCC publishes a large dataset of network measurements from thousands of homes, with gigabytes of data. The project goal is to analyze the data and answer questions such as: Has the increased usage reduced internet speeds? Can we tell how much people are staying at home from data usage records? Is the increased use of video conferencing reflected in the upload metrics?

Continue reading

In 2013, the Chinese government launched its grand initiative to eradicate rural poverty by 2020. The initiative has made great progress since then, yet little rigorous empirical evidence is available due to data limitations. This project aims to use big data through both official and social media to analyze the trends, achievements, and challenges of this initiative and offer implications for the future and from a comparative perspective.

Continue reading

This project is the first comprehensive examination of African North Americans who crossed one of the U.S.-Canada borders, going either direction, after the Underground Railroad, in the generation alive roughly 1865-1930. It analyzes census and other records to match individuals and families across the decades, despite changes or ambiguities in their names, ages, “color,” birthplace, or other details.

Continue reading

Author's picture

Columbia Data Science Institute (DSI) Scholars Program

The DSI Scholars Program is to engage and support undergraduate and master students in participating data science related research with Columbia faculty. The program’s unique enrichment activities will foster a learning and collaborative community in data science at Columbia.

Columbia University DSI

New York, NY