Chowning, Luke

• Ph.D., Exercise Physiology, Texas Tech University

• M.S., Kinesiology and Exercise Science, Texas Tech University

• B.S., Kinesiology and Exercise Science, Lubbock Christian University

My research objectives center on two aims: 1) incorporating artificial intelligence (AI) with biomechanical analysis of sport performance, training interventions, and mitigating risk of injury in collegiate athletes, and 2) utilizing loaded jumps to improve muscular power in athletic populations. 

Regarding aim 1, we are investigating methodologies for integrating AI to determine levels of preparedness for training in athletes utilizing quantitative metrics such as sleep quantity and quality, caloric balance, training volume, and jumping metrics. Students involved in this research are required to assist the DSU strength & conditioning staff with data acquisition (i.e., sleep data, weight tracking, and jump performance), data processing, and will be involved in creating neural networks using AI models.

The second aim of our research investigates ideal load ranges for loaded jumps in the context of the impulse-momentum paradigm. Currently, power is the primary variable of interest as it relates to optimizing power production in training. However, recent research has suggested that power may be limited in practical application. Thus, we are examining the viability of using momentum as it provides a broader spectrum for strength coaches when determining loads. Students involved in this research project will be required to collect data, assist with l-repetition maximum protocols, process data, and assist with statistical analysis.