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Class of 2024 Exercise Science Awards

Students are posed in graduation outfits

The Department of Exercise Science is pleased to recognize the outstanding work of its graduating students:

Undergraduate Research Excellence Award

The Undergraduate Research Excellence award is given to a graduating student who has been extensively involved in research during their undergraduate studies, excelling in originality, creativity, and significance of their work. Students are selected based on their overall involvement in research, including collection of data, presentation of research at conferences, preparation of peer-reviewed manuscripts for publication, and impact of their work.

Recipient: Dylan Marshall Malinowski

Dylan has been an integral part of the Neuromuscular Physiology Lab over the past year, assisting in research design, data collection and analysis, and manuscript writing. He presented his work as lead author at SU Neuroscience Research Day, is a co-author on an abstract to be presented at the 2024 National Strength and Conditioning Association Annual Conference, and is a co-author on a manuscript in preparation. His work ethic, attention to detail, and intellect have made him an exceptional young researcher and will serve him well in his future career.


Graduate Research Excellence Award

The Graduate Research Excellence award is given to a graduating student who has been extensively involved in research during their graduate studies, excelling in originality, creativity, and significance of their work. Students are selected based on their overall involvement in research, including collection of data, presentation of research at conferences, preparation of peer-reviewed manuscripts for publication, and impact of their work.

Recipient: Reese Patrick Michaels

Reese has made significant contribution to the project that investigates the feasibility of using an AI-based algorithm to analyze video-captured falls of older adults. Despite having no prior programming experience, Reese quickly learned and played a key role by developing crucial code for analyzing hip acceleration during a fall. He dedicated a great amount of time to multiple steps of the analysis process, including editing video data, applying the AI algorithm, identifying biomechanical components, running statistical analyses, and generating formal reports. Reese consistently met project deadlines and presented a conference poster at the 2023 Mid-Atlantic Regional Conference-ACSM. The manuscript for this project is now submitted to the Scientific Report, and he is the first author.