# REU Site: Research on Prescriptive Analytics for AI-enabled Operations Engineering

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of Missouri-Columbia (MO) · $419,402

## Abstract

This Research Experiences for Undergraduates Site renewal will engage 10 undergraduate students each year in a 9-week summer research program on artificial intelligence (AI)-enabled operations engineering. Many important systems in transportation, healthcare, manufacturing, and services operate under uncertainty, limited resources, and changing conditions. These systems increasingly depend on analytical and computational methods that combine operations research and artificial intelligence to improve planning, coordination, and real-time decision-making. The project will provide students with mentored research, technical training, and professional development that strengthen preparation for graduate study and technical careers in computing, operations research, analytics, and intelligent systems.

The research activities will focus on AI-enabled operations engineering, including prescriptive analytics methods that combine optimization, simulation, machine learning, and related computational tools to support complex operational decisions. Students will engage with decision problems in healthcare, next-generation transportation systems, advanced manufacturing, and contested logistics. They will receive training in problem formulation, data analysis, optimization, simulation, algorithm development, machine learning, computational experimentation, and solution evaluation. Sample projects that are computationally challenging include collaborative blood inventory planning, network-aware drone logistics, urban air mobility coordination, additive manufacturing scheduling, and decision-making for logistics operations under disrupted or contested conditions. The program will strengthen student preparation in both computing and operations research methods while helping build a workforce prepared to address complex real-world challenges in critical operational domains.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using

## Key facts

- **NSF award ID:** 2548110
- **Awardee organization:** University of Missouri-Columbia (MO)
- **SAM.gov UEI:** SZPJL5ZRCLF4
- **PI:** Suchithra Rajendran
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Artificial Intelligence (AI), UNDERGRADUATE EDUCATION, REU SITE-Res Exp for Ugrd Site
- **Estimated total:** $419,402
- **Funds obligated:** $419,402
- **Transaction type:** Standard Grant
- **Period:** 10/01/2026 → 09/30/2029

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2548110

## Citation

> US National Science Foundation, Award 2548110, REU Site: Research on Prescriptive Analytics for AI-enabled Operations Engineering. Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nsf/2548110. Licensed CC0.

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