Building real-time computer vision systems, NLP document pipelines, and cybersecurity tools. Research Assistant at Lawrence Tech — 4 publications, 5 EC-Council certs, MS in CS (GPA 3.75/4.0).
I'm a CS engineer at the intersection of AI research and production engineering. Currently a Research Assistant at Lawrence Technological University, I build real-time behavior detection systems with YOLOv8 and PyTorch — from dataset curation and YAML pipeline design through Grad-CAM explainability and deployment.
My technical range spans computer vision (YOLOv8, Grad-CAM, OpenCV), NLP and API engineering (FastAPI, regex pipelines, document generation), deep learning (CNN-LSTM hybrid models for seismic prediction), and cybersecurity (buffer overflow analysis, exploit research, EC-Council certified across 5 domains).
I have 4 published and in-progress research papers spanning enterprise cybersecurity, AI-based behavior detection, earthquake prediction with CNN-LSTM, and NLP-driven document intelligence. I care deeply about model interpretability, responsible AI, and clean modular architecture.
This paper presents a hybrid CNN-LSTM deep learning architecture for earthquake prediction and the generation of synthetic seismograms. The model leverages convolutional layers for spatial feature extraction from seismic waveform data and LSTM layers for temporal sequence modeling, enabling accurate magnitude prediction and realistic synthetic seismogram synthesis for data augmentation and simulation purposes.
Seeking AI Engineer / ML Engineer roles. 4 publications, MS CS 3.75 GPA, EC-Council certified. Southfield, MI — open to remote.