Faculty
David Ye is an Associate Research Professor of Mathematics at Duke University, with a secondary appointment in the Department of Statistical Science and a leadership role in the MIDS program’s Quantitative Finance Concentration. With more than 25 years of experience in the financial industry, including senior roles such as Chief Risk Officer at Nomura Americas and State Street Global Markets, he brings a deep understanding of real-world finance into the classroom. He has developed and taught courses spanning algorithmic trading, risk management, and AI in finance, helping students connect data science and quantitative modeling to practical applications. Through his teaching, mentorship, and industry partnerships, he prepares students to apply their skills in dynamic, high-impact fields while also exploring new areas like the intersection of data science, risk, and climate.
Kyle Bradbury is an Assistant Research Professor in Duke’s Pratt School of Engineering and Nicholas School of the Environment, and director of the Energy Data Analytics Lab at the Nicholas Institute. His work focuses on using machine learning to better understand, plan, and manage energy systems and climate impacts. He leads projects that apply computer vision and remote sensing data to assess infrastructure at a global scale, helping inform more resilient and sustainable systems. With training in electrical engineering from Tufts and advanced degrees from Duke, he brings a highly applied, interdisciplinary approach to both his research and his work with students.
Students
Bridging Data Science and Climate Finance to Drive Sustainable Impact in Southeast Asia
Students: Adil Gazder and Shiyue Zhou
Through his work with the Climate Dialogue & Innovation Initiative, Adil is exploring how data science can support more effective climate finance. As a graduate research assistant, he is helping map how private capital flows into sustainability efforts across Southeast Asia, building data pipelines that use natural language processing and machine learning to identify climate-focused investments and organizations. His work brings together data, policy, and finance to better understand how funding aligns with climate goals and where gaps still exist. Along the way, Adil is gaining hands-on experience working with complex, real-world data while developing the skills to turn analysis into insights that can influence decision-making. His experience highlights how MIDS students are applying data science in global, interdisciplinary settings to drive meaningful climate impact.
Climate+
MIDS students are also diving into Climate+ projects that make a real difference across the globe. From building a first-of-its-kind global coastal atlas to better understand climate vulnerability in coastal communities, to improving Duke’s own greenhouse gas data systems, to using machine learning and aerial imagery to map energy access in underserved regions, students are applying data science in creative and meaningful ways while contributing to solutions that support climate resilience and sustainability.
Mapping High-Stakes Coastal Zones
Student: Leonard Eshun
Working with Nicholas School professor David Gill and a cross-disciplinary team, Leonard is helping develop the first global coastal social-environmental atlas—an interactive platform that brings together social, economic, demographic, and environmental data related to climate and ocean conservation. The project combines datasets from around the world to better understand climate vulnerability in coastal regions, while giving students hands-on experience in spatial analysis, data engineering, and full-stack development. The work will help inform policymakers and global organizations working to strengthen climate resilience and protect vulnerable communities.
Duke University Greenhouse Gas (GHG) Data System Update
Students: Nruta Choudhari and Tanya Singh
Partnering with the Duke Office of Climate and Sustainability, Nruta and Tanya are working to improve how the university tracks and reports its greenhouse gas emissions. Their team is analyzing how data moves across campus systems and implementing updates to make the process more efficient and transparent. This work directly supports Duke’s sustainability goals and helps create clearer, more accessible data to drive climate action on campus.
Energy Transition During Energy Crisis
Student: Ilseop Lee
Ilseop is part of a team using machine learning and aerial imagery to better understand energy access in developing regions. Building on previous work, the team is refining models that detect solar infrastructure and developing new tools to identify additional energy sources. Their work will help map electricity access in underserved communities, providing valuable insights for researchers and policymakers working toward more equitable and sustainable energy systems.
Advancing Climate Risk Solutions Through Market Innovation
Student: Tianji Rao
Through the MIDS program’s Climate concentration, Tianji Rao is using data-driven approaches to address critical funding gaps in climate adaptation. At the 2024 Climate Risk & Resilience Summit in Atlanta, hosted by CIRCAD, he partnered with Professor David Ye to present research on how markets price climate risk and how innovative funding structures, fair risk premia, and policy design can help attract greater private investment. By combining data science, finance, and policy, his work aims to unlock scalable solutions for climate challenges. Tianji also participated in hands-on innovation labs and was recognized with the Dean’s Research Award, highlighting both the impact of his research and MIDS’ focus on real-world, interdisciplinary problem-solving.
Alumni
Shufan Xia (MIDS ’23) is a PhD student in Energy Science and Engineering at Stanford University, where she’s using data science to tackle one of today’s biggest challenges: climate change. While at Duke, she worked on a Bass Connections project that combined satellite imagery and artificial intelligence to better understand how our environment is changing. By developing new ways to gather and analyze satellite data, her work helps researchers spot patterns across landscapes and track climate-related impacts more effectively. With a background in physics and a passion for problem solving, Shufan brings together machine learning, geospatial data, and real-world applications. Whether she’s analyzing satellite images or building models to understand risk, she’s focused on turning complex data into insights that can make a difference. Her work highlights the kind of impact MIDS students can have at the intersection of data science and global challenges.
Projects
MIDS capstone projects give you the chance to work side by side with real organizations on real problems, including some of the most pressing climate challenges facing our world today. You’ll collaborate with partners like companies, nonprofits, and government agencies while being supported by Duke faculty, building skills in teamwork, project management, and communication along the way. By the end, you’ll deliver a final presentation and white paper that share your insights and make a meaningful contribution, so you graduate not just with experience, but with work that has real impact.
Climate-Focused Capstone Projects
MIDS students regularly take on capstone projects that address pressing environmental challenges, working with partners to turn data into meaningful insights and tools for action.
Examples:
Protecting the High Seas
Students: Athena Liu and Surabhi Trivedi
Partner: Duke University Marine Lab | Industry: Environment
In this project, students explored how rising temperatures are reshaping fragile marine ecosystems in regions like the Sargasso Sea and the Costa Rica Thermal Dome. Using time series analysis and simulated climate scenarios, the team identified both short- and long-term biological changes, including links between increased carbon emissions, more frequent marine heatwaves, and declining zooplankton populations. Their findings point to significant risks for marine life and highlight the urgent need for stronger conservation efforts in these high-seas environments.
From Raw Data to Deployment: Engineering a Machine Learning Solution
Students: Caleb O’Neel and Malcom Fraser
Partner: Saving Nature | Industries: Environment, NGO
Working with Saving Nature, students developed a machine learning solution to support wildlife conservation efforts. The organization collects large volumes of trail camera footage to monitor animal activity in restored habitat corridors, but reviewing this data manually is time-intensive. The team built a model that filters out videos without animal activity, dramatically reducing the need for manual review. They also created a scalable system and user-friendly web application to streamline data processing, helping Saving Nature expand its impact without requiring technical expertise.
Course
Climate, AI, and Risk Concentration (Proposed)
MIDS is also exploring a new elective pathway, led by David Ye, focused on Climate, AI, and Risk, designed for students who want to use data science to better understand and respond to climate and environmental challenges. This concentration would bring together courses from across Duke and introduce new opportunities for hands-on learning, helping students build skills in analyzing, predicting, and managing climate-related risks using data science and AI. Whether you’re coming in with a strong interest in climate or a background in computation, this pathway offers a flexible way to connect those interests and apply your skills to real-world environmental solutions.