Bilal Shihab
Biomedical Engineering Student at UT Austin — specializing in Embedded Systems, Edge AI, and hardware-software integration.
shihabbilal@gmail.comAbout Me
I'm a Biomedical Engineering student at UT Austin, specializing in Embedded Systems, Edge AI, and hardware-software integration.
I'm passionate about developing low-level firmware and high-performance data pipelines — currently leading the Edge AI team at Longhorn Neurotech, building projects in neural network deployment on embedded platforms, medical device development, and real-time signal processing.
Projects
Cloud to Edge Heart Rate Monitor
End-to-end pipeline from Cloud Storage → Raspberry Pi 5 → Pi Pico, with a custom C-based inference engine running quantized neural networks on a dual-core Cortex-M0+ to classify heart conditions.
View on GitHubEmbedded Multiplayer Racer
Award-winning bare-metal racing game in C for TI MSPM0 — register-level UART/ADC/DAC drivers, custom networking protocol, and real-time physics on ARM Cortex-M0+.
View on GitHubML Interpretability with Neurotech
Capsule network architecture for model interpretability in neural signal processing, improving understanding of brain-computer interface models.
View on GitHubECG PCB Project
Custom Electrocardiogram PCB designed in Fusion 360 with instrumentation amplifiers and active bandpass/notch filtering to isolate cardiac signals.
Laser Speckle Project
Real-time Laser Speckle Analysis UI in Python, interfacing with Basler cameras and Arduinos for automated laser intensity control during surgery.
View on GitHubMotorMind: EEG Signal Processing
Python framework for EEG signal processing using RAG with Google's Gemini AI — data acquisition, tokenization, vector storage, and inference.
View on GitHub