I am a biomedical AI researcher and engineer with over five years of experience applying deep learning and signal processing to neural and muscular signal data. I specialize in developing intelligent systems that support neurological assessment and rehabilitation using non-invasive signals such as EMG, EEG, fNIRS, and fMRI. My current focus is on translating state-of-the-art AI into real-world healthcare solutions for personalized recovery and functional enhancement.
At the CNAlab at NJIT, I am developing a deep learning model to track motor units across sessions from high-density surface EMG (HD-sEMG), enabling clinicians to monitor recovery trends and optimize rehabilitation strategies. I also recently first-authored a review on AI-based assessment of motor impairments using myographic signals, which offers a comprehensive overview of the field and identifies opportunities for advancing clinical tools.
I am currently seeking full-time opportunities as an AI researcher or AI engineer in healthcare, neuroscience, or medical technology fields, where I can contribute to the development of impactful, data-driven solutions for human health.
Projects I led and contributed to
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Built a graph neural network model for autism classification using fMRI data with gray and white matter.
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Explored brain activation patterns during naturalistic movie watching with convolutional neural network-based video feature analysis.
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Developed AI-enhanced Raman spectroscopy tools for detecting early skin abnormalities.
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Designed real-time biosignal monitoring systems and emotion-recognition tools using ECG and EMG.
Technical Skills
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Programming & Tools: Python, MATLAB, R, Linux, Git, C/C++
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Deep Learning: CNN, Vision Transformer, Autoencoder, RNN, Transformer, LLM, AI Agents
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Machine Learning: SVM, Random Forest, KNN, Regression
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Applications: Detection, Segmentation, Classification, NLP
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Biomedical Data Processing: fMRI, MRI, EMG, ECG, Raman Spectroscopy, Ultrasound, CT
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Other: Real-time GUI with Python, Signal decomposition, PCA, ICA
Education
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M.S. in Biomedical Engineering, New Jersey Institute of Technology
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M.E. and B.E. in Biomedical Engineering, Kyung Hee University, Korea