Wearable hydration tracking
Developing a wrist-band for non-invasive and real-time hydration tracking. This is a continuation of my 2nd Masters.
Hajj pilgrims monitoring from wearable data
Here we used data collected from different wearable sensors and explored the possibility to predict multiple health contexts, including physical tiredness, emotional mood, and activity type.
Early detection of COVID-19 using wearable data
Using consumer wearables to predict COVID-19 before symptoms appear.
RNA Splicing Analysis Pipeline for Infection-Stage Transcriptomics
A Modular RNA-seq Alternative Splicing Pipeline.
MotifXplorer
MotifXplorer is a package and web platform for ML-based transcription factor binding prediction and motif exploration from ChIP-seq.
Interpretable Machine Learning for cfDNA Cancer Screening
A machine learning pipeline used to identify cancer-specific chromatin features from cell-free DNA (cfDNA)
Spectral Diffusion Lab
Generating synthetic spectroscopy data with Diffusion Models to improve early Cancer screening.
Portable Brain-Computer Interface (BCI)
Prototype for a low-cost, portable EEG-based system controlling a robotic arm.
Immersive VR Rehab for Multiple Sclerosis
Concept and research plan for bimanual Virtual Reality rehabilitation in Multiple Sclerosis.
Edge-AI Development Board for Healthcare Applications
Build on my previous IoT Development-Board, this describes an all-in-one medical sensor board for Edge AI research and prototyping.
IoT Development Board
An ESP32-based IoT development board featuring 4 opto-isolated relays, Wi-Fi/Bluetooth connectivity, and built-in USB-UART for easy programming. Designed and sold for academic and industrial use.
Low-cost Phasor Measurment Unit (PMU)
My good old first Master's project : Here I describe the firmware and software implementation of a Low-Cost M-Class Phasor Measurement Unit (PMU).
Weka activity detection
A mobile app that helps building and deploying Activity Recognition models directly on your Smartphone.
Machine Learning for Voltammetric Trace-Lead Sensing
ML pipelines for quantifying trace lead from portable voltammetric sensors under realistic field conditions