ACTIVE PROJECTS
Wireless Microdevices
We develop injectable wireless microscale implants for neural recording and stimulation. The devices combine custom integrated circuits, wireless power transfer, electrodes, and advanced packaging to enable minimally invasive interfaces distributed throughout the nervous system.
Collaborators: Nitish Thakor (JHU), Sun Nian (NU), Zhenan Bao (Stanford)
Funding: NIH DP2, NSF EAGER
Differential Tissue-Coupled Powering for Thread-like Injectable Neural Technology (TINY)
We are developing TINY, long, thread-like injectable neural interfaces for minimally invasive stimulation and recording. The implants are wirelessly powered using DTCP, which transfers energy through tissue from a compact wearable transmitter. The approach enables slender, alignment-robust implants for interfacing with targets such as the spinal cord and peripheral nerves.
Collaborators: Baibhab Chatterjee (UF), Shriya Srinivasan (Harvard University)
Funding: NIH DP2, NIH R01 (1R01EB039082)
In News: UF
Edge-AI Sub-Scalp EEG for Brain Monitoring and BCI
We are developing an ultra-low-power ssEEG implant with on-device ML for continuous brain monitoring. By integrating neural recording, an analog-computing ML ASIC, wireless power, and telemetry into a miniature implant, the system can analyze neural signals locally rather than continuously transmitting raw EEG data.
Collaborators: Aatmesh Shrivastava (NU), Jose Principe (UF), Sydney Cash (MGH/Harvard Medical School)
Funding: NIH R01 (1R01NS154768)
BlueME: Underwater Communication Using Magnetoelectric Antennas
We are developing BlueME, a ME transducer system for low-power underwater communication between robots and sensor nodes. BlueME uses resonant ME antenna arrays to transmit low-frequency electromagnetic signals through water, enabling communication without the line-of-sight requirements of optical links or many of the multipath and Doppler limitations associated with acoustics.
Collaborators: Jahid Islam (UF)
Non-Invasive Glucose Monitoring Using NIR and Machine Learning
We are developing a non-invasive smartwatch-based glucose monitoring platform that combines near-infrared (NIR) spectroscopy with machine learning to estimate glucose continuously without an implanted sensor. The system will be validated against commercial CGMs while incorporating physiological and behavioral data such as heart rate, activity, sleep, meals, and insulin use to improve prediction accuracy. Institutional Review Board
Collaborators: Parissa Rashidi (UF), Desmond Schatz (UF), Mark Atkinson (UF)
Funding: AIIRI Seed fund
COMPLETED PROJECTS
Transcranial Magnetic Stimulation
This project seeks to develop a radically new brain stimulation technique based on temporal interference of two high-frequency sinusoidal magnetic fields.
Collaborators: Sun Nian (NU), Jennifer Rodger (UWA), Sydney Cash (MGH & Harvard Medical School)
Micro-magnetic Stimulation
We are developing efficient micro-magnetic stimulation probes for chronic neuromodulation, with the goal of providing a minimally invasive alternative to conventional electrode-based stimulation technologies.
Collaborators: Sun Nian (NU), Amir Yacoby (Harvard), Sydney Cash (MGH & Harvard Medical School)