Shahin Movassagh

AI/ML Researcher | Python Developer | PhD Student in Artificial Intelligence

I am a PhD student in Artificial Intelligence at Islamic Azad University, Tabriz, with a strong research and development background in Artificial Intelligence, Machine Learning, Deep Learning, and Python.

My expertise and research interests include Deep Learning, Transformer architectures, Generative AI, Reinforcement Learning, Time-Series Forecasting, Natural Language Processing, and Biomedical Signal Processing. I have experience developing AI-based solutions and conducting research on real-world problems using Python and modern machine learning frameworks.

My research has resulted in multiple publications and international conference papers, including research on ECG arrhythmia classification using Autoencoder-Transformer architectures, electricity load forecasting, deep reinforcement learning for portfolio optimization, stock forecasting, and software analysis.

Selected Research

• HAT-ECG – Hybrid Autoencoder-Transformer for ECG Arrhythmia Classification

Physiological Reports, 2026

"PubMed" (https://reference-url-citation.invalid/0)

• AeroFormer – Lightweight Autoencoder-Augmented Transformer for Electricity Load Forecasting

IPAPS 2026

"ResearchGate" (https://reference-url-citation.invalid/1)

• Adaptive Portfolio Optimization with Multi-Agent Deep Reinforcement Learning

2025

"ResearchGate Profile" (https://reference-url-citation.invalid/2)

• LoopGAN – Multi-Step Generative Architecture for Sequential Stock Forecasting

CSICC 2025

"DBLP" (https://reference-url-citation.invalid/3)

I am currently looking for remote opportunities in AI/ML, Python development, Machine Learning research, AI engineering, and AI research projects. I am particularly interested in working with international teams on challenging problems where I can combine my research experience with practical AI development.

Research: 5+ publications | 8+ citations