Temitayo (Tayo) Ajayi, a third-year graduate student in computational and applied mathematics (CAAM) at Rice University, remembers a grade-school teacher who had his students measure the distance traveled by marbles released in chutes positioned at various angles.
“I really enjoyed the project. I liked numbers and I liked quantifying the information. Right from the start I was attracted to mathematics,” said Ajayi, who earned a B.S. in applied mathematics from Yale University in 2015 and started graduate school at Rice that year.
Working with his adviser, Andrew Schaefer
, a Noah Harding Chair and professor of CAAM, and Taewoo Lee, an assistant professor of industrial engineering at the University of Houston, Ajayi is researching ways to prioritize clinical objectives in prostate cancer treatment.
“There are many possible objectives to consider when planning radiation therapy, and a proper balance of those objectives can help optimize the outcome of treatment,” Ajayi said.
Using a technique called inverse optimization, Ajayi proposes a framework that determines the priorities of different objectives based on the treatments of similar patients. Ajayi and his research partners provide two methods to determine the importance of objectives — one exact, the other approximate. “We use a greedy algorithm to select our objectives and provide theoretical guarantees to doctors,” he said.
“Tayo’s research is motivated by an important problem,” Schaefer said, “and will have a practical impact on cancer treatment. He has discovered mathematical structures that partially explain why certain simple algorithms perform well, even when we know that they won’t always give us the best solutions. In operations research we seek practical decision problems that lead to computational and theoretical insights, and Tayo’s work is a perfect example of this.”
“Operations research is a good mixture of theoretical and applied work,” Ajayi said. “It is about using advanced analytical methods to make better decisions. We use simulation, probability and optimization.”
Ajayi was born and raised in Anchorage, Alaska, where his parents emigrated from Nigeria. His mother is a chemistry teacher and his father drives a cab. “Education was always important in my family,” he said.
He started as an economics major at Yale but changed direction after taking classes in optimization and game theory. At Rice, working with Schaefer focused his research in the direction of operations research.
Since coming to Rice, Ajayi has received a RGEM (Rice Graduate Education for Minorities) Fellowship and a Ken Kennedy Institute Computer Science and Engineering Fellowship. He is now at work on his master’s thesis, “Assessing the Tightness of Linear Programming Relaxations: The Paramaterized Gap Problem,” and expects to earn his master’s degree later this year and his Ph.D. in 2020.