Mehrdad Mokhtari is an Applied Software Engineer with the Berlinguette Group at the University of British Columbia (UBC). His work focuses on applying Bayesian optimization and advanced data science techniques to accelerate autonomous experimentation in self-driving laboratories. In addition to developing machine learning models that guide data-driven scientific discovery, he designs user interfaces and dashboard tools that improve accessibility and efficiency for experimental researchers. Through this combination of optimization methods, automation, and software engineering, Mehrdad supports the integration of artificial intelligence into experimental science and contributes to advancing next-generation research infrastructure.