Dr. Utku Culha

* Leading a team of 9 research scientists on applying machine learning, image analysis, and feedback control for novel robotic systems in multiple length scales (i.e. micrometer to the centimeter). * Developing self-organizing multi-body robotic systems for cooperative manipulation and cargo-transfer tasks. * Using model-free machine learning (e.g. Bayesian Optimization, NN) to design soft robots and experimentally optimize their manipulation and locomotion controllers.

* Developed tendon-driven anthropomorphic robotic manipulators using a combination of soft and rigid materials. These fingers were applied in the lettuce-picking tasks of Sainsbury's Supermarket Ltd. in the UK. * Developed Finite Element Methods (FEM) based simulation tools to optimize the tendon-driven actuation of soft robotic manipulators. * Organized a robotics workshop for ∼100 scientists at the "International Soft Robotics Week 2015" in Livorno, Italy.

* Designed and programmed an active robotic sensing system that fabricates sensors to probe unknown objects in its environment. * Designed and built an untethered robot moving in free-space by fabricating spider-inspired draglines using thermoplastics. * Developed an optimization algorithm that designs complex sensor morphologies for sensing soft surface deformations. * Developed a modular musculoskeletal robot toolkit with soft ligaments and tendon-driven actuation.

Developed the rigid-body dynamics simulation of a cheetah-inspired robot with an actuated spinal joint to increase the bounding locomotion performance.

Designed, developed, and patented a digital stethoscope that diagnoses heart diseases using machine learning. Established collaborations with national research hospitals and funding agencies.

Built a gecko-inspired amphibious running robot with compliant feet and developed its gait locomotion control.

Developed the embedded software and the control interface for military-grade sensing and monitoring equipment.

Dissertation: "Inhomogeneous Deformations of Thermoplastic Materials for Physically Adaptive Soft Matter Robots"

Thesis: "Articulated Back Spine Architecture for Locomotion in Quadruped Robots"

Robotics, embedded systems, machine learning