Robust and Interpretable Machine Learning

Welcome to the RIML Lab at Sharif University of Technology, led by Dr. Mohammad Hossein Rohban. We focus on developing robust and interpretable machine learning solutions, addressing challenges in anomaly detection, adversarial robustness, and computational biology. Let's grow together.​

About the Lab

At RIML Lab, we focus on creating machine learning algorithms that can withstand adversarial conditions and provide insights into their decision-making processes. Our research aims to bridge the gap between theoretical advancements and practical implementations, ensuring that AI systems are both effective and trustworthy.

Our Goals

By embodying these principles, the RIML Lab aims to be a beacon of excellence in machine learning research, contributing to a more vibrant, growing, self-actualized, and sustainable world.

• Vibrant: Cultivating an energetic and inclusive research environment.
• Growing: Advancing knowledge and expanding impact.
• Self-Actualized: Empowering individual potential.
• Sustainable: Committing to long-term responsibility.