Sayyed Mohsen Vazirizade

Post Doctoral Researcher/Data Scientist

About me

I’m a postdoctoral researcher at Vanderbilt University, Department of Electrical Engineering and Computer Science. As a member of SCOPE Lab (Smart and resilient Computing for Physical Environment) under the supervision of Dr. Abhishek Dubey, I work on multiple projects including developing Artificial Intelligence agents for integrated data-driven technologies for smart cities and analyzing transportation systems using network science.
I earned my PhD from the University of Arizona under the supervision of Prof. Achintya Haldar focused on developing an intelligent integrated method for reliability estimation. Upon completion of my PhD, I also received The Outstanding Graduate Student Award in 2019.
Risk requires the modeling of the environment, which was another part of my research using statistical modeling. Additionally, I developed a model using Recursive Neural Networks (RNN) to imitate the response of a structure and find the location as well as the severity of the damage. Previously, I collaborated as a Data Scientist on an NEH funded project for developing a new OCR technique using Computer Vision (CV) and Long Short-Term Memory (LSTM) networks, and a hurricane predictive model using high-dimensional spatio-temporal data.

A comical adage by renowned economist Ronald Coase says:
“If you torture the data long enough, it will confess to anything”.
Even though this statement is ambiguous, I would prefer to be optimistic and interpret this as using the correct tools to coerce the data to a correct confession. The role of a data scientist is to find and apply the correct tool. I am passionate about working with numbers. Developing models to predict/imitate a behavior/feature is quite magical. I’m very interested in solving real-world problems by using machine learning and my data science knowledge. For fun, I follow Formula 1. It is, indeed, one of the most heavily-invested-in-data-science sports. During a race, thanks to the over 300 sensors on each car, more than 1.5GB of real-time data is transfered back to the engineers, ref.