I'm an undergraduate biomedical engineer (B.S., expected May 2028; GPA 3.83, Dean's List) working at the intersection of flexible electronics fabrication, deep learning, and dexterous robotics.
I like building the full signal chain of an instrument — fabricating the electrode, writing the firmware that drives it, and training the model that makes sense of what comes back. I am currently working as an undergraduate reseearch at the Columbia Laboratory for Unconventional Electronics (CLUE) under Dr. Ioannis (John) Kymissis.
A wearable system using flexible LED–photodiode arrays to non-invasively screen for breast cancer by reconstructing optical absorption through tissue. Wrote STM32 firmware (STM32CubeIDE) for individual LED addressing, and optimized illumination/detection patterns to maximize source–detector coverage and SNR.
A four-electrode sensor for ventriculoperitoneal shunts: an upstream pair pulses the conductive CSF and the downstream pair times the ion cloud's transit, mapping to flow rate and revealing obstruction. Built the benchtop loop (NE-1000 syringe pump, artificial CSF, Keysight WaveGen + capture), characterized Pt–Ir electrodes via EIS, and designed a translational version with cleanroom metal deposition + Parylene-C.
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.
Integrating SpikeATac piezoelectric tactile sensors onto the fingertips of CRAFT, an open-source tendon-driven hand with hybrid hard–soft compliance, then designing a multimodal architecture that fuses touch + vision to train manipulation policies.
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.