Courtney Kunselman ’20 received the Conference of Southern Graduate Schools’ (CSGS) 2021 outstanding master’s thesis award. |
Image: Courtesy of Courtney Kunselman
Former Texas A&M University graduate student, Courtney Kunselman ’20, has been named a Conference of Southern Graduate Schools’ (CSGS) 2021 outstanding master’s thesis award winner. Nominations for this award were reviewed by faculty members in the field from CSGS member institutions and evaluated on the basis of clarity of style and presentation, scholarship, research methodology and contributions to the field or discipline.
Kunselman attended the United States Air Force Academy for her undergraduate degree and later graduated from Texas A&M with her master’s degree in materials science and engineering and a graduate certificate in materials, informatics and design in 2020. She is currently an intelligence officer in the Air Force, and supports the B-52 strategic bomber at Barksdale Air Force Base.
Her thesis, “Semi-Supervised Learning Approaches to Class Assignment in Ambiguous Microstructures,” builds a framework for classifying microstructure images in the semi-supervised context and proposes a new method for quantifying error when a large portion of the training data has no label. She earned this award in the category of “mathematics, physical sciences and engineering.”
Kunselman said she is extremely humbled for her thesis to be recognized with this award. “Good research is a product of good teamwork at all levels,” she said. “Throughout my time at Texas A&M, I was supported by an amazing group of researchers who held me to a rigorous standard, pushed me outside of my narrow comfort zone, and helped get our work out to be seen and used by the greater scientific community. Their dedication to my success was boundless, and I cannot thank them enough for it."
“My experience at Texas A&M made me a better collaborator, initiative-taker, communicator, student, teacher, mentor and critical-thinker,” she said. “All of these traits are extremely important for the job that I am doing now, and I am very thankful for the opportunity to sharpen these skills through my time researching at A&M.”
Additionally, Kunselman said she was greatly influenced and inspired by one of her colleagues, Dr. Vahid Attari. “He was an extremely patient, kind and generous mentor,” she said. “I knew that if I had any questions or needed any assistance, he would do all that he could to help me without hesitation.”
Kunselman’s advice to graduating engineering students is to not be afraid to pursue what interests you, even if it doesn’t quite fit your degree or other people’s views of what your education should be used for. “As an intelligence analyst, I am constantly having to make assessments and predictions with partial data and communicate how available evidence led me to those conclusions,” she said. “Your education taught you how to be a problem-solver – now go solve whatever problems you want to.”
Likewise, her advice to undergraduate engineering students is to pay attention in mandatory math classes, and look beyond the calculations to see the beautiful logic underlying the process.
“My bachelor’s degree is in mathematics rather than engineering, and I was pretty nervous at first that I would be behind the curve in an engineering graduate program,” she said. “But I quickly learned that math is a superpower – if you have a strong enough math skill set, you can learn almost anything STEM related.”
Kunselman attended the United States Air Force Academy for her undergraduate degree and later graduated from Texas A&M with her master’s degree in materials science and engineering and a graduate certificate in materials, informatics and design in 2020. She is currently an intelligence officer in the Air Force, and supports the B-52 strategic bomber at Barksdale Air Force Base.
Her thesis, “Semi-Supervised Learning Approaches to Class Assignment in Ambiguous Microstructures,” builds a framework for classifying microstructure images in the semi-supervised context and proposes a new method for quantifying error when a large portion of the training data has no label. She earned this award in the category of “mathematics, physical sciences and engineering.”
Kunselman said she is extremely humbled for her thesis to be recognized with this award. “Good research is a product of good teamwork at all levels,” she said. “Throughout my time at Texas A&M, I was supported by an amazing group of researchers who held me to a rigorous standard, pushed me outside of my narrow comfort zone, and helped get our work out to be seen and used by the greater scientific community. Their dedication to my success was boundless, and I cannot thank them enough for it."
“My experience at Texas A&M made me a better collaborator, initiative-taker, communicator, student, teacher, mentor and critical-thinker,” she said. “All of these traits are extremely important for the job that I am doing now, and I am very thankful for the opportunity to sharpen these skills through my time researching at A&M.”
Additionally, Kunselman said she was greatly influenced and inspired by one of her colleagues, Dr. Vahid Attari. “He was an extremely patient, kind and generous mentor,” she said. “I knew that if I had any questions or needed any assistance, he would do all that he could to help me without hesitation.”
Kunselman’s advice to graduating engineering students is to not be afraid to pursue what interests you, even if it doesn’t quite fit your degree or other people’s views of what your education should be used for. “As an intelligence analyst, I am constantly having to make assessments and predictions with partial data and communicate how available evidence led me to those conclusions,” she said. “Your education taught you how to be a problem-solver – now go solve whatever problems you want to.”
Likewise, her advice to undergraduate engineering students is to pay attention in mandatory math classes, and look beyond the calculations to see the beautiful logic underlying the process.
“My bachelor’s degree is in mathematics rather than engineering, and I was pretty nervous at first that I would be behind the curve in an engineering graduate program,” she said. “But I quickly learned that math is a superpower – if you have a strong enough math skill set, you can learn almost anything STEM related.”