Saeid Asgari

I am a Principal Machine Learning Research Scientist at Autodesk AI Research and an Adjunct Research Professor at the School of Computing Science (ranked #1 in Computer Vision in Canada), Simon Fraser University (SFU), Canada. Previously, I explored real-world machine learning and computer vision problems in startup environments.

I completed my PhD in Computing Science at SFU under the supervision of Prof. Ghassan Hamarneh. During my PhD I had multiple research visits/internships at different research institutions such as MILA (Montreal, Canada), Siemens Healtheneers (Princeton, USA), and Imagia Canexia Health (Montreal, Canada).

Outside of work, I have a strong passion for soccer and running track - the 100m sprint. I've had the privilege of competing and earning a few medals in inter-university competitions in these areas.

I lead research and development initiatives in safety, reliability, interpretability, and fairness for machine learning models, including generative models like LLMs and VLMs.

• Reliability and Robustness: Designing experiments and datasets to analyze generalization, memorization, and robustness in generative models, ensuring they perform reliably across diverse scenarios.
• Interpretability and Explainability: Building tools to understand ML model behavior, improve transparency, and ensure models meet safety and ethical standards.
• Data Bias and Mitigation: Developing scalable tools to identify hidden and known biases in datasets, while enhancing datasets and designing models to better handle biases, out-of-domain samples, and improve generalization.

Design template by Jon Barron