I'm an undergraduate biomedical engineer (B.S., expected May 2028; GPA 3.83, Dean's List) working across biomedical instrumentation, embedded acquisition systems, deep learning, and dexterous robotics.
I build and validate the software that connects experimental hardware to usable measurements, from optical sensors and multichannel electronics to high-speed cameras. I am currently an undergraduate researcher at the Columbia Laboratory for Unconventional Electronics (CLUE) under Dr. Ioannis (John) Kymissis.
Developed firmware and analysis for an inherited eight-sensor FeatherS3 optical platform. Investigated cross-sensor timing instability and implemented continuous-wave illumination as a workaround. Completed finger PPG and phantom comparisons; reconstruction remains unvalidated.
Investigating a revised electrochemical approach to CSF shunt flow monitoring. The sensing mechanism is being reconsidered, with current work exploring a potentiostat-based approach.
Conductive ink drawn directly on skin to capture EEG, ECG, and skin-impedance signals for stress detection and wearable diagnostics. Developing flexible DoS transistors, heaters, and pressure sensors, and mentoring incoming researchers in lab protocols.
Led 7 undergraduates applying AI/ML to brainwave data from commercial EEG headsets. Streamlined acquisition with an IRB-approved SOP over Lab Streaming Layer, and classified grasping motions with a Gaussian Mixture Model + K-Nearest Neighbors.
SFCN (3D CNN) and a Vision Transformer with a 3D-CNN tokenizer stem, trained on 712 ADNI subjects with paired T1 + FLAIR MRI. Full preprocessing (N4 bias correction, MNI152 registration) and transfer learning from a UK Biobank checkpoint.
Assembled and integrated an open-source CRAFT hand with working webcam teleoperation. Developing a miniaturized tactile PCB for fingertip sensing, balancing size and signal quality. Touch–vision policy learning is a future direction.
Implemented software for an existing STM32 instrument to record and replay electric-fish signals. Integrated converter communication, board modes, and a desktop interface. Bench verification is complete; electrode and water tests are next.
Developed a live camera interface and recording pipeline for a VC MIPI IMX568 on Jetson Orin Nano. ROI capture reached a reported ~770 fps; sustained disk throughput awaits original capture verification. Testing used the bare camera board.
Designed and tested a levitating sole using neodymium magnets to relieve plantar fasciitis — achieving 84.57 lbs of repulsion, an improvement over traditional EVA foam. Applied K-Means clustering to plantar-pressure and gait data to tune magnetic force across the sole for optimal redistribution.
Yu, Y. (2024). Levitating Magnetic Insoles: A Novel Approach to Alleviating Plantar Fasciitis Through the Reduction and Redistribution of Plantar Pressures. Journal of Innovations in Medical Research, 3(3), 14–35.