Incoming first year PhD at the California Institute of Technology | Previously Electrical and Computer Engineering student at the University of Toronto
Feel free to reach out, always happy to talk :)
yuan.sui@mail.utoronto.ca · 604-652-5482 · Personal Website · LinkedIn
Research
Machine Learning Research @ SickKids, advised by Dr. Jennifer Quon
Fig 2. UNet architecture
Brain Blood Vessel Segmentation Using Deep Learning
- Efficient and accurate medical image analysis is essential for treating cerebrovascular diseases such as arteriovenous malformation (AVM)
- Investigating existing deep learning architectures for brain blood vessel image segmentation including UNet, GAN, Diffusion, and Attention Models
- Following rigorous review article protocols
Bioelectronic Research @ X-Lab, advised by Prof. Xilin Liu and Dr. Taufik Valiante
Fig 3. OpenMEA electrical system
Microelectrode Array System PCB
- OpenMEA is a 64-channel interface that stimulates and records brain tissues to understand complex neural network behavior in an epileptic state
- Designed an LVDS adaptor PCB for STM32 Microcontroller that communicates to the stimulation and recording IC with reduced noise
- Fabricated the entire electrical system including power PCB, Intan IC PCB, and Headstage PCB
Fig 4. Dual channel 40V neurostimulator
Miniature Neural Stimulator PCB
- Miniature neural stimulator is a device that stimulates rat’s brain in real-time during in vivo experiments to study the effect of stimulation on stroke recovery
- Designed stimulator PCB capable of delivering 3.3V and 40V stimulation in sinusoidal and biphasic waveforms at precise frequencies
- Participated in the CRANIA 2023 pitch competition to investigate the commercial plausibility of neural stimulator
Brain Machine Interface Research @ ISML Lab, advised by Prof. Roman Genov
Fig 5. Peripheral nerve stimulation at Krembil Brain Institute
Neural Interface Chip DAC Driver FPGA
- Targeted neuromodulation is an important part of modern Brain Machine Interface (BMI) research
- Designed an FPGA circuit to drive the neural chip Digital to Analog Converter (DAC) to perform stimulation at precise frequency and intensity
- Performed in vivo experiment of peripheral nerve stimulation and maintained correct signal output
Fig 6. Recorded action potential from human brain slices
Neural Interface Chip ADC Receiver FPGA
- Accurate brain signal acquisition is an important part of the modern Brain Machine Interface (BMI)
- Designed an FPGA circuit to transmit non-uniform neural chip Analog to Digital (ADC) output to the computer via Ethernet protocol
- Performed human brain slice recording and successfully recorded multiple neural action potential
Publications
Fascicle-Selective Ultrasound-Powered Bidirectional Wireless Peripheral Nerve Interface IC
Fascicle-Selective Bidirectional Peripheral Nerve Interface IC with 173dB FOM Noise-Shaping SAR ADCs and 1.38pJ/b Frequency-Multiplying Current-Ripple Radio Transmitter
Projects
CV available upon request
My personality described by music :)
Introspective and Focused
Me playing “Dawn” on piano
Motivated and Collaborative
My favorite film “Zootopia”
Ideas for Navigating University