Jonathan Daniels

My research investigates how movement is learned, adapted, and shaped by evolutionary history, bridging computational cognitive science and biomechanics. My doctoral work at Princeton University developed computational models of human neuromotor development, using motion capture, pose-estimation, and physics-based simulation to characterize how motor skills are acquired and retained across the lifespan. At the Max Planck Institute for Evolutionary Anthropology, I direct a comparative biomechanics facility that applies motion capture, force plate, and EEG methods to human and primate movement, working with functional morphologists and archaeologists to connect experimental biomechanics with fossil and archaeological evidence of hominin locomotion and tool use. Across these projects, I combine machine learning, statistical modeling, and multimodal sensor data to ask how the motor system adapts, both over milliseconds of learning, years of development, and millions of years of evolution.

Career & Education:

• M.A., Ph.D., Princeton University (2023, 2026)
• B.A. (Hons), Case Western Reserve University (2019)

Research experience:

• Human Factors Engineer, Apple^â (2025)
• Clinical Research Associate, Noom^â (2024-2026)
• Research Associate, Yale University (2019-2021)
• Senior Research Assistant, Case Western Reserve University (2017-2019)
• Research Assistant, Weill Cornell Medicine (2016-2019)

Research awards & funding:

• US National Science Foundation; Graduate Research Fellow (2023-2028)
• US National Academy of Sciences Predoctoral Fellow (2022-2027)
• Princeton University Centennial Fellow (2021-2026)
• Case Western Reserve University Fellow (2015-2019)

Languages:

• English (Native)
• German (Intermediate, A2/B1)

Biomechanics of Human Evolutionary Behaviors (MPI-EVA, current): Comparative motion-capture studies of locomotion and tool-use behavior, contextualizing ape biomechanics data against human experimental findings to inform interpretations of hominin locomotor and tool-use evolution. Collaborators: Dr. Adam van Casteren and Dr. Charlotte King (primate evolutionary biomechanics), Dr. Shannon McPherron (human evolution of tool-use).

Motor Development in Infancy (Princeton, Baby Lab): Longitudinal characterization of movement coordination and motor control across early development, using pose-estimation of behavioral video data. Collaborator: Prof. Casey Lew-Williams (human development).

Sensor-Based Human Factors Research (Apple^©): Integrated motion capture, gaze tracking, and behavioral survey data to inform sensor R&D and early-stage feature development for next-generation hardware.

Computational Models of Human Motor Adaptation (Princeton, Intelligent Performance and Adaptation Lab): A 200-participant longitudinal study of motor skill acquisition and retention, using neural networks, unsupervised learning, and physics-based simulation to model individual learning trajectories. Collaborators: Prof. Jordan A. Taylor (motor-skill learning), Prof. Shreya Saxena (Yale; engineering and computational motor control).