Mohsen Saffari, Ph.D.

Assistant Professor of Computer Engineering

Introduction

Mohsen Saffari joined the Electrical and Computer Engineering department at PNW in Fall 2024. His teaching and research focus on the real-world applications of machine learning models for spatiotemporal data.

Research Overview

Mohsen Saffari’s research focuses on the theory and application of machine learning and deep neural architectures for analyzing spatiotemporal data in power systems and computer vision.

Select Publications

Saffari, Mohsen, and Mahdi Khodayar. “Spatiotemporal Deep Learning for Power System Applications: A Survey.” IEEE Access (2024).

Saffari, Mohsen, and Mahdi Khodayar. “Low-rank sparse generative adversarial unsupervised domain adaptation for multi-target traffic scene semantic segmentation.” IEEE Transactions on Industrial Informatics (2023).

Saffari, Mohsen, et al. “Behind-the-meter load and PV disaggregation via deep spatiotemporal graph generative sparse coding with capsule network.” IEEE Transactions on Neural Networks and Learning Systems (2023).

Saffari, Mohsen, Mahdi Khodayar, and Mohammad E. Khodayar. “Physics-Informed Graph Capsule Generative Autoencoder for Probabilistic AC Optimal Power Flow.” IEEE Transactions on Emerging Topics in Computational Intelligence (2024).

Teaching Focus

With a strong foundation in artificial intelligence and machine learning, Dr. Mohsen Saffari’s teaching focuses on machine learning, the theory and applications of artificial neural networks, deep learning, and software engineering.

Why I Became an Engineer

Engineers play a vital role in shaping every aspect of human life. The ability to think critically, innovate, and solve complex problems through creative ideas brings a deep sense of fulfillment and joy.