The winners of the 2026 D2K Spring Showcase with D2K director, Chad Shaw.
Fifteen undergraduate student teams presented interdisciplinary capstone projects at Data-to-Knowledge (D2K) Lab’s 2026 Spring Showcase on April 27. The D2K Lab at Rice University’s George R. Brown School of Engineering and Computing acts as a dynamic hub for innovative interdisciplinary data science education and practice. This biannual showcase offers students an opportunity to share the remarkably creative projects they have completed.
Each semester, student teams address real-world problems presented by government, industry, and community sponsors across varied sectors such as energy, aerospace, health, finance, public transport, arts, and environment. The student teams work collaboratively with mentors from sponsoring entities, Rice faculty, and graduate student researchers known as D2K Fellows to solve these challenges using cutting-edge machine learning, artificial intelligence (AI), and computational approaches.
This initiative shows how interdisciplinary multi-institutional collaborations can drive meaningful improvements in public health and safety, enhance both natural and built environments, and address major global challenges facing humanity.
Team NASA Reentry won first place at the 2026 D2K spring showcase. Their project was titled “Predicting Spacecraft Reentry Conditions with Machine Learning.”
When a spacecraft reenters Earth’s atmosphere at hypersonic speeds, the air in front of it becomes highly compressed, generating extremely hot plasma. Existing computational simulations for modeling these rapid and intense heat changes are both time-consuming and expensive. Sponsored by NASA’s Johnson Space Center, the project aimed to efficiently and accurately determine the best spacecraft thermal protection systems to accelerate the design and prototyping of new models. The team used machine learning and AI approaches to analyze data from previous NASA missions to quickly and precisely estimate heat flux during different reentry conditions. The team was mentored by NASA’s Andrew J. Hyatt, Rice professor Xinjie Lan, and D2K Fellow Vishesh Kumar. Rice students who collaborated on the project include Arush Adabala, Ethan Hsu, James Foxworth, Kyle Zheng, Livia Cordeiro, and Todd Hao.
"Working with Rice D2K Lab provided an opportunity for us to evaluate if machine learning approaches could solve computational and spaceflight engineering problems that we’d previously addressed using more brute force approaches,” Hyatt said. “This collaboration demonstrated that machine learning approaches can provide robust and more efficient solutions than some traditional methods. Students involved in this project were engaged and eager to learn and have made significant contributions to solve the technical challenges we face during spacecraft reentry.”
Team Hawkeye won second place for their project titled “Scene Understanding and Semantic Retrieval for Industrial Safety.”
This project, sponsored by TechnipFMC, aimed to improve industrial safety by enabling analysts to search video content using natural language and free-form descriptions instead of relying on specific keywords. To accomplish this, Team Hawkeye developed AI-powered video analysis software that rapidly detects objects and automatically generates captions from industrial footage. The team was mentored by TechnipFMC’s Partha Dutta, Rice associate professor Arko Barman, and D2K Fellow Nhi Le. Team members included Rafael Tinajero-Ayala, Kunyang Li, Richard Xu, Marcos Miranda, Laura Chirila, and Alan Johnson.
Team Palyno-Minds won the third-place award for their project titled “Automated Detection of Palynomorphs in Digital Microscopy.”
The Smithsonian Museum stewards tens of thousands of microscopy slides of organic microfossils such as pollen, spores, fungi, and algae, termed palynomorphs. The sheer volume of these specimens in the museum makes it time-consuming to analyze and catalog them manually. Team Palyno-Minds designed a scalable pipeline to automate the detection and localization of palynomorphs from high-resolution digitized microscopy images. By enabling rapid analysis and annotation of a wide range of specimens on each slide, this new automated, efficient workflow will accelerate the pace of discovery in palynological research. The team was mentored by Ingrid Romero and Scott Wing from the Smithsonian, Rice associate professor Arko Barman and D2K Fellow and PhD mentor Tony Yu. Student members of this team were Abbas Shaikh, Teon Golden, Aditya Viswanathan, Praise Mayor, Patrick Ainlay-Vazquez, and Eric Zhang.
“Working with the Rice students was an absolute pleasure and remarkably productive from beginning to end,” Wing said. “They organized our collaboration with impressive focus and efficiency, and consistently demonstrated how bright, energetic, and deeply knowledgeable they are. Their advisors were equally outstanding, providing exceptional guidance throughout. The students exceeded our expectations at every turn—what the Rice D2K team has delivered marks the beginning of a new digital era in the study of fossil pollen. Their work will transform how we conduct our research and how scientists around the world engage with our collections. This project has shown us the tremendous value of partnering with Rice students to bring 21st-century methods to our fossil collections. And we had a lot of fun along the way.”
“I am extremely proud of the Rice D2K students and mentors for their enthusiastic participation in these projects and for the incredible impact they bring to our industry and community partners each semester,” said Chad Shaw, D2K director.
All projects from the 2026 Spring Showcase can be found here.