I am an AI Specialist currently completing my Master of Science in Artificial Intelligence. With over a decade of experience in data analysis, I specialize in building intelligent systems that solve complex real-world challenges, from materials discovery to cybersecurity.
- Hackathon Winner: Top-ranked in the KACST "GenAI for Materials Discovery" Hackathon.
- Research Interests: Hybrid Agentic LLM frameworks, Spatio-Temporal modeling, and Generative Networks.
- Technical Stack: Python, PyTorch, TensorFlow, Transformers (BERT/T5), and LLM Prompt Engineering.
An award-winning platform from the KACST Hackathon that uses Generative AI (CDVAE & ALIGNN) to discover novel materials for
- Key Impact: Achieved 92% prediction accuracy and accelerated discovery speed by 90%.
A machine learning pipeline for cybersecurity that identifies malicious phishing attempts using TF-IDF and Random Forest classifiers.
- Result: Balanced detection with >90% accuracy on real-world email datasets.
Implementation of a Spatio-Temporal model using CNN + LSTM architectures to classify human actions in video sequences.
A Deep Convolutional Generative Adversarial Network trained on the CelebA dataset to synthesize high-fidelity human faces.
A comparative study of Transfer Learning strategies for text classification, covering Zero-Shot, Few-Shot, and Full Fine-Tuning.
- LinkedIn: https://www.linkedin.com/in/anwar-alghamd/
- Specialization: AI Specialist
- Location: Saudi Arabia
"Turning data into intelligence, one epoch at a time."