# REU Site: Interdisciplinary Computational Biology (iCompBio)

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of Tennessee Chattanooga (TN) · $464,970

## Abstract

This REU Site award to the University of Tennessee at Chattanooga (UTC), located in Chattanooga, TN, will support the training of 10 students for 10 weeks during the summers of 2026-2028. The program, Interdisciplinary Computational Biology (iCompBio), will provide research training in developing computational approaches across genomics, epidemiology, geology, ecology, evolution, biochemistry, cell biology, and molecular biology. The program will enhance participants' knowledge and research skills in both computing and life sciences, as well as soft skills, thereby better preparing them for careers in interdisciplinary STEM fields. It will also strengthen the campus research community, bring in talented students from other institutions, and raise the university’s visibility as a place where innovative, student-centered research happens. Students will learn how research is conducted, and many will present the results of their work at scientific conferences. Assessment of this program will be done through Qualtrics. Students should apply to the REU site using NSF ETAP (Education and Training Application: https://etap.nsf.gov). The training students will receive is aligned with the NSF priorities in Biotechnology, AI, and Quantum Information Science.

The iCompBio research projects integrate computational and biological approaches to address complex scientific questions. Example projects include applying artificial intelligence to metabolite identification, using bioinformatic tools to analyze bacterial proteins, modeling the spread of viral infections, studying biodiversity responses to environmental stress, and exploring quantum approaches for biological data analysis. Participating departments include Computer Science and Engineering, Biology, Geology and Environmental Science, Mathematics, Physics, Chemical Engineering, and Engineering Management and Technology. Students will begin with training in Python, data science, and machine learning, then work closely wit

## Key facts

- **NSF award ID:** 2548016
- **Awardee organization:** University of Tennessee Chattanooga (TN)
- **SAM.gov UEI:** JNZFHMGJN7M3
- **PI:** Yingfeng Wang
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Artificial Intelligence (AI), QUANTUM INFORMATION SCIENCE, Biotechnology, REU SITE-Res Exp for Ugrd Site
- **Estimated total:** $464,970
- **Funds obligated:** $464,970
- **Transaction type:** Standard Grant
- **Period:** 05/01/2026 → 04/30/2029

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2548016

## Citation

> US National Science Foundation, Award 2548016, REU Site: Interdisciplinary Computational Biology (iCompBio). Retrieved via AI Analytics 2026-05-20 from https://api.ai-analytics.org/grant/nsf/2548016. Licensed CC0.

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