Columbia University's Data Science Institute

09/03/2026

Where Data Takes Us: Nami Jain MSDS '26

This summer, Nami worked as a Data Science Summer Analyst at JPMorganChase, where she built an automated, end-to-end test framework to help ensure compliance with the firm’s data-usage policy, replacing manual validation with scalable testing across thousands of policy scenarios to improve reliability and release confidence.

We caught up with her about her internship experience:

➡️ How did your experience at Columbia University's Data Science Institute contribute to your internship?

DSI gave me so many opportunities to connect with JPMorganChase through career fairs, networking events, and hackathons, which ultimately helped me land this internship. Once I got there, the collaborative, hands-on environment at DSI gave me the confidence to take ownership of projects and make meaningful contributions from day one.

➡️ How will this internship shape the rest of your time at DSI and your future career?

This experience completely changed how I think about building technology. Instead of creating solutions that only solve today’s problem, I learned how to design systems that are scalable, sustainable, and built for long-term impact. I’m excited to bring that mindset back to DSI and into my future career in AI and data science.

➡️ What was your favorite part of the internship?

Seeing the impact of the work I was doing! I had the opportunity to present my project to senior leadership, meet people across the organization, and even meet Chairman and CEO, Jamie Dimon. It was an incredible reminder that interns can make a real difference when they’re trusted with meaningful work.

Nami is pictured here with her fellow JPMorganChase intern and DSI student, Emily Ramond.

09/03/2026

The Center for Sustainable Futures at the Teachers College, Columbia University is taking climate education to the next level with a new TC Academy online module: the 2026 Climate Education Knowledge Sharing Convening 🌎

The self-guided, online resource is an evolution of the Center’s multi-year research-practice partnership with NYC Public Schools and LEAP at Columbia University, which has reached more than 600 NYC educators.

DSI Member Tian Zheng, who is the Deputy Director, Education Director and Chief Convergence Officer at LEAP and a Professor with the Department of Statistics, says: “What's exciting about this convening is that it turned three years of on-the-ground work with NYC teachers into a resource the whole field can build on. That kind of knowledge-sharing is exactly what LEAP makes possible.”

Read more:

A new asynchronous online course from the Center for Sustainable Futures presents years of insights and resources

08/31/2026

It's the exciting first week of their Master's degree - and their future careers - for these 248 DSI students! 🙌 🌎

This week, the incoming students in Columbia University’s Master of Science in Data Science program start their orientation. These future data scientists represent the best and brightest students from across the country and the world.

Their time at Columbia University's Data Science Institute will give them foundational knowledge & skills, hands-on experience, and a strong grounding in ethical practice through the Data Science Institute’s commitment to Data For Good.

Welcome to Columbia! 🦁

08/21/2026

Where Data Takes Us: Diya Bedi MSDS '26

🛞 This summer, Diya worked as a Data Science Intern at Bridgestone Americas Technology Center, where she built machine learning models to predict how different tires perform in winter conditions. She also helped design a simulation tool that brought together several separate testing environments into one interface, and built out a statistical pipeline for analysing tire wear over time. 🛞

We caught up with her about her internship experience:

➡️ How did your experience at Columbia University's Data Science Institute contribute to your internship?

The coursework at DSI, especially statistical inference and applied deep learning, meant I could walk in and start building instead of catching up. Beyond that, DSI gave me opportunities to open up, as an introvert, the push I got through networking events, hackathons, and career fairs gave me just the confidence I needed, which turned out to be exactly what the internship and the people at the company loved about me.

➡️ How will this internship shape the rest of your time at DSI and your future career?

It taught me that a good model isn't enough on its own, it has to be something people actually trust and use. I want to carry that mindset into the rest of my time at DSI and into whatever I build next, whether that's in ML engineering or research.

➡️ What was your favorite part of the internship?

My favorite moment was watching a model I built actually influence a real design decision, and knowing something I made on my laptop turned into something real is a feeling I'll carry with me long after this summer. I also loved that I never felt imposter syndrome there, everyone from interns to senior engineers was learning and growing right alongside each other, and being part of that was one of the best feelings.

08/07/2026

As a DSI Scholar this Spring term, Nitanshi Bhardwaj researched the capacity of data science in creative technology 🎵

The Columbia University Computer Music Center has advanced speakers and VR equipment that can create realistic 3D sound and visual experiences. These devices communicate through Open Sound Control, which allows different music and media software to send information to each other. However, there is a gap in technology that can convert data from a spreadsheet, and send it to these systems in real time. This creates repetitive work, slowing the creative process.

Nitanshi applied her data science skills to develop a Python tool that bridges this gap, with the ability to read and convert Excel and CSV data into live messages. This not only reduces friction in the creative process, but lowers the technical barriers for students, researchers, composers, and artists to creatively interact with data.

She completed her project with faculty mentor Seth Cluett of the Columbia University Computer Music Center.

08/06/2026

DSI Student Scholar Spotlight ⭐ Tanish Patel partnered with the Lamont-Doherty Earth Observatory of the Columbia Climate School to research source-level data valuation for sparse ocean carbon prediction.

Machine learning is used to predict how much carbon dioxide the ocean absorbs or releases. To make these predictions, data is combined from various locations, such as ocean observations and climate model simulations.

The problem: not all sources of data contribute equally to model performance. Some may improve regional generalization, while others can be harmful. Patel’s project applied his data-science skills to determine which data is truly worth collecting, and which data sources help prediction the most.

Tanish measured each data source as a player in a cooperative game, using Shapley values to determine the average contribution of each source. This helps scientists determine which datasets are most valuable for ocean prediction.

Throughout his DSI Scholar project, he worked with several mentors - Lamont-Doherty’s Galen McKinley, Amanda Fay, Thea Hatlen Heimdal.

08/04/2026

The DSI Student Scholar program would not be possible without our dedicated Columbia University faculty mentors 🙌

Isabelle Mueller, a Post Doctoral researcher at Columbia University Irving Medical Center, mentored two DSI Student Scholars this spring. Aniqa Nayim (left) and Akanksha Dhar (right) applied their data science skills to research fetal neurodevelopment, exploring biomarkers and the potential of at-home monitoring.

Both projects were successful in their findings, showing the power of collaboration between student and mentor 🤝

Each spring and fall, the DSI Scholars program connects Columbia students with select faculty-led projects that are seeking to apply data science methods to novel research problems.

Interested in becoming a mentor? Learn more about what that could look like for you: https://datascience.columbia.edu/research/programs/dsi-scholars/

08/03/2026

As a DSI Scholar this spring, Henrique Schmitz applied his data science skills to explore the study of ocean ecosystems 🛰️

Spectral data helps researchers study marine ecosystems by measuring wavelengths of light. This allows them to detect phytoplankton, harmful algal blooms, and coral health. The new PACE satellite provides more detailed wavelengths than past missions.

Henrique’s research aimed to pair PACE images with previous satellites, modelling an estimation of the data PACE could have collected based on data collected by other satellites. This provides more in-depth data on how climate change has affected these ecosystems across an expanded period of time. His project was successful in reconstructing historical observations, helping to improve future ocean monitoring 🌎

This DSI Scholar project was supported by faculty mentors Jinghui Wu, Joaquim Goes, and Helga Gomes of the Lamont-Doherty Earth Observatory/ Columbia Climate School.

07/23/2026

Columbia MSDS students partnered with TIFIN for their spring 2026 Capstone Project, helping to create a tool-augmented multi-agent LLM framework for transparent investment advising.

Modern financial AI systems increasingly rely on tool-calling architectures – large language models orchestrate specialized APIs for portfolio construction, analytics, fund selection, and knowledge retrieval. While this AI can produce complex financial outputs, it cannot always explain them conversationally, concisely, or faithfully to the investment logic behind them in chatbots or Q&As.

Working within TIFIN's multi-agent framework, the group advanced approaches that enforce grounded financial explanations, tying user-interface responses back to structured, inspectable evidence.

Their model shows that transparent financial QA can be improved through a pipeline design, creating more grounded and reliable responses.

Congratulations to all team members for their hard work! 👏

Could your AI systems benefit from the fresh perspectives of our talented MSDS students? Learn more about the Data Science Institute Capstone Program: https://industry.datascience.columbia.edu/engage/capstone