Leila joined NECSI as a postdoctoral research fellow. She holds a Ph.D. in Physics. Leila’s research includes studying the dynamics of complex systems, using various statistical, artificial intelligence, and machine learning methods and analysis. She is interested in techniques that are applicable in health, social and economic systems. Her focus is on understanding the structure of systems and changes in their structure over time, using geospatial statistical analysis, agent-based modelings, network analysis, and various machine learning techniques. She was the PI in an NSF granted project to optimize the quarantine policies using the mobility patterns of individuals and the severity of COVID-19 contagion in different areas. She also developed a model to understand the evolution of the epidemic and to plan efficient management strategies. Now, she is working on another project to find the topological network of symptoms and diseases related to COVID-19 to better help patients and doctors with decision makings and treatments.