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What third grader loves pie? All of them. 

What third grader loves Pi? Kamal Albousafi.

Albousafi became intrigued by Pi when his brother was talking about Pi Day (March 14) at his Sioux Falls middle school. Knowing that 3.14 is the ratio of a circle's circumference to its diameter wasn’t enough for Albousafi. He had a passion to learn as many of the almost endless digits of Pi that he could.

While he got up to 50 digits, his mathematical fire was somewhat quenched when a family member said, “OK, but what can you do with that?”

Fast forward 13 years and Albousafi has found plenty of things he can do with his fascination with figures, fractions and formulas. The South ��ֱ���� State University senior is among 12 students chosen as Future Innovators of America by the Jerome J. Lohr College of Engineering.

The fellowships were created to provide unique research opportunities for undergraduate students in the college. Any student is eligible to apply as long as they are attending full time and have a GPA of 3.0 or higher. Recipients are awarded $5,000 with $4,500 as a stipend and $500 to cover the cost of lab supplies or travel to disseminate the results of their project. 

Math makes grazing more sustainable

Albousafi, a senior math and statistics major from Sioux Falls, is working with associate professor Hossein Moradi Rekabdarkolaee to leverage statistical techniques (dynamic linear modeling and Bayesian filtering) to analyze, predict and forecast crop health through the use of satellite imagery and climate data. 

The aim is to be able to use this data to predict well in advance the supplemental feed needs for grazing livestock. 

Taking it to the simplest terms, the premise of the project is to obtain a vegetation index from the study of satellite images, create a model that incorporates temperature, precipitation and drought levels, and then, based on that algorithm, be able to predict how much grazing that land can support in the coming growing season.

Consequently, the rancher would know in advance to obtain supplemental feed stocks, reduce herd size or find other pasture.

That’s the simple explanation. But to make the simple possible, a lot of senior- and graduate-level mathematics is needed.

In second year working with Moradi

Albousafi said real analysis, which is an advanced form of calculus, and linear algebra “really help you to be able to wrestle with any mathematics you might encounter. They really help with mathematical maturity.”

Moradi said, “Kamal is good at analyzing data while being able to dive deep on mathematical concepts.”

They have been working together on satellite data research since early 2024. Then in summer 2024 Albousafi participated in a 10-week Research Experience for Undergraduates program at SDSU in which he worked under math faculty members Moradi and Jung-Han Kimn using satellite images and dynamic modeling to predict crop health.

Giving direction to data

The Future Innovators of America project Albousafi started working on in January uses the same process and data but looks at pastureland rather than cropland.

NASA’s Landsat 5 and 8 satellites produce overhead images every 16 days and have been doing so since 1980. By looking at near-infrared and red light bands, an average normalized difference vegetation index is created for each image. That index provides a metric to measure vegetation density or health.

Measurements of temperature, precipitation and drought levels are obtained from the National Oceanic and Atmospheric Administration. Each value is figured on the basis of a 75-day average to eliminate the wild swings South ��ֱ���� is known for, Albousafi said.

When he did this type of work with his Research Experience for Undergraduates study, Albousafi focused on images of a 75-tract of corn and soybeans in Edmunds County. As of mid-February, a site for their ranchland observation hadn’t been finalized. 

The focus has been documenting the procedures and methods for the project, explaining how data is obtained and the challenges with the data. Albousafi said the challenge is clouds, which skews the index, making the surface look less green than it actually is. Consequently, the researchers are tossing out those images in building their algorithm.

If past success is an indicator

Should Albousafi be as successful in his Future Innovator project as he was with the Research Experience for Undergraduates project, the grassland guess work could be gone.

After training the crop model on data from 1980 to 2020, Albousafi then applied the predictive model to 2021-23 and “got solid results,” predicting with 80% accuracy, and it was accurate regardless of crop rotation or harvest timing, he said.

Albousafi gave a poster presentation on his work at the summer South ��ֱ���� EPSCoR (Established Program to Stimulate Competitive Research) conference at the Sioux Falls Arena and at the SDSU Data Science Symposium Feb. 7. He won a $200 first prize in the undergraduate division for his SDSU presentation.

For his current research, Albousafi hopes to generate a paper that will be accepted into a peer-reviewed journal.

Research makes ‘cool’ knowledge useful

The 4.0-GPA student is also in the accelerated master’s program, meaning he will earn his bachelor’s degree in May and his master’s degree in May 2026. In between, he hopes to gain a summer internship.

Albousafi said he enjoyed the first three years of his college experience and the chance to learn “cool math,” but “with classes I didn’t understand how the information would be useful. When I started doing the actual research, it helped me see where all the applications could go. 

“It was a big motivation to see math become something powerful like that. For me, the problem-solving capabilities of mathematics was pretty life changing. It was eye opening to see that you can take these crazy ideas for a problem and rationally approach and solve them.

“Before I felt lost and unsure if this was right for me. Once I started seeing it in practice, it gave me that purpose, it gave me direction instead of feeling lost. To me, it’s mind boggling how you can model the world with mathematics.”