Phil Xie
Phil Xie
I'm passionate about neurotechnology, medical devices and imaging, machine learning, and music, and I'm actively working on these things.
I'm an electrical engineer at Science, where I'm building next-generation biomedical technologies as part of an excellent, interdisciplinary team.
I'm also a research engineer in UC Berkeley's Sensorimotor Neural Engineering Lab, where I am building a hand kinematics-tracking wearable for stroke rehabilitation, driving electronics and form factor design in our space-constrained, easy-to-apply wireless device.
Previously, I've done research in Transcranial Magnetic Brain Stimulation and Machine Learning for 3D Multi-class Cancer Tumor Segmentation on MRIs. More about my research experience on LinkedIn, and check out my Projects!
During undergrad, I am grateful to have had the chance to lead Neurotech@Berkeley 🧠, a group of 120+ undergrads actively building BCI devices, software, and wetware, consulting with companies, and getting more people interested in the field through our student-led courses, publications, and diverse event series.
I love playing and thinking about music — I play the piano, bassoon, and chromatic harmonica in jazz, classical, and pop genres, and am always curious about the connection between music and our brains and bodies. I'm currently trying to learn more about sound design!
I do not (yet) own Philz Coffee, but will still thank you for your business if you decide to buy a coffee from the Californian chain. For reasons not so obvious, I'm a fan of their Philtered Soul and Philharmonic drinks.
Always happy to chat or grab a coffee — please send me an email at phil.xie [at] berkeley [dot] edu or on LinkedIn!
🛠 This website is under construction. More cool stuff coming soon!
🦾 Here are some highlighted projects! To see what I'm researching, check out my LinkedIn.
A multi-sensor, easy-to-apply wireless wearable for continuously monitoring the hand kinematics of patients with motor impairments.
A modular, fully customizable, daisy-chainable EEG headset for independent neuroscience research.
A pair of PCBs with an opposing grid of transducers, for floating small particles!
A wearable sleeve that translates live speech into phoneme-inspired haptic stimulation patterns with low-latency.
Developed novel sampling and regularization algorithms on Transformer-CNN hybrid models for multi-class cancer segmentation in 3D mp-MRI images.
The statements below are under construction.