Congratulations – Mackenzie Pitts receives Gatzert Child Welfare Fellowship!

Mackenzie is wearing an orange sweater and smiling at the camera. She has curly dark brown hair and dark brown eyes.

We are excited to announce that PhD Candidate Mackenzie Pitts is a recipient of the 2026-2027 Gatzert Child Welfare Fellowship. This UW fellowship is awarded to doctoral candidates as they write their dissertation on research that supports children with disabilities. With this award that covers one quarter of funding, Mackenzie will be dedicated to improving the quality of her work in preparation for her defense.

Dynamic Walking 2026

Members of the lab traveled to the base of Mt. Rainier for the Dynamic Walking Conference, where conversations ranged from hummingbird drumming to exoskeletons and robotics.

Dr. Kat Steele was selected to give a 20-minute talk, “Bayesian methods for individualized modeling with wearable data.” PhD student Ally Clarke gave a 5-minute talk on energy savings from bodyweight support in children with cerebral palsy, sharing results from our Cerebral Palsy Energetics study . PhD student Mackenzie Pitts also gave a 5-minute talk on her work from the Dynamic Motor Control study, discussing the mechanical strategies children with cerebral palsy use to adapt step length during split-belt treadmill walking.

We loved reconnecting with former lab members Dr. Michael Rosenberg, Dr. Momona Yamagami, and Tori Landrum.

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Congratulations, Mac! Mackenzie Pitts passed her Ph.D. General Exam!

We’re excited to share that Mackenzie Pitts has successfully passed her Ph.D. General Exam! 🎉

Mackenzie’s proposed work, titled “Personalizing Clinical Gait Assessments Using Bayesian Modeling,” was approved by her Ph.D. committee. This milestone marks an important step toward her doctoral degree, and we’re thrilled to celebrate her hard work and dedication.

Congratulations, Mackenzie!

A person standing next to a large wall-mounted screen displaying a presentation slide titled ‘Personalizing Clinical Gait Assessments Using Bayesian Modeling.