Max Robotics — Global Service Robot Directory + US Certification

About

Wanwen Chen’s research bridges two transformative frontiers: intelligent robotic prosthetics and minimally invasive surgical guidance. In the domain of lower-limb prosthetics, Chen pioneered a strain gauge-based locomotion mode recognition method using convolutional neural networks, a breakthrough that enables precise, adaptive control of active prostheses across varying terrains. This work, cited 29 times, demonstrates how one-dimensional strain signals can power robust terrain classification. Chen further advanced this field by analyzing hardware acceleration for on-board recognition systems using field-programmable gate arrays, achieving real-time performance critical for clinical viability. More recently, Chen has turned to head-and-neck cancer treatment, developing transcervical ultrasound image guidance for transoral robotic surgery (TORS). This work addresses a critical challenge: optimizing resection margins for oropharyngeal squamous carcinoma by fusing preoperative MRI with intraoperative ultrasound. Chen also contributed a novel algorithm for tracking curved needles during ultrasound-guided insertion, overcoming the common assumption that needles appear as straight lines in images. With publications spanning 2018 to 2025, Chen’s research consistently tackles real-world clinical constraints—from prosthetic control latency to surgical visualization—making tangible impacts on both rehabilitation and oncology.