Mohammad Aghababaei

About Mohammad Aghababaei

As a Research Engineer at Verisk, I apply my quantitative skills and domain knowledge to develop innovative solutions for the insurance industry. With a PhD in Engineering and years of academic and professional experience in quantitative research, I have a strong background in Machine Learning, data analytics, stochastic modeling, risk-based decision making, reliability analysis, and agent-based modeling. I have the ability to work effectively in fast-paced environments, love to be challenged by new problems, and have the specialty to learn new skills very fast. In the past three years at Verisk, I contributed to developing and enhancing various Verisk CAT models in different regions of the world. I added a new wildfire sub-peril to the US wildfire model through a novel quantitative approach based on Machine Learning techniques to capture risk more accurately for insurance companies. I have also collaborated with a team of software developers to implement our models into the product and test them. I contributed in development and enhancement of earthquake models in Canada and Mexico. I am also the process owner of developing earthquake models for the renewable energy sector. Additionally, I have mentored a newly joined data scientist and performed extensive data analysis on the claims data from large (re)insurance companies. My mission is to leverage data and technology to improve the understanding and management of uncertain events and their impacts.

Experience

1. Research Engineer Ii

   Verisk

   Dec 2021 — Present · Boston, MA, US

   Model owner of a new wildfire sub-peril to be added to the Verisk\'s US wildfire model to more accurately capture risks by insurance companies. Main responsibilities:• Developed a novel quantitative approach based on Machine Learning techniques to predict the hazard intensity and risk of exposures subject to this sub-peril. • Collaborated with a team of software developers to implement the model into the product and test it.• Performed extensive data analysis on the claims received from large (re)insurance companies to benchmark losses as well as calibrate the existing wildfire ML models.2. Mentored a newly joined data scientist to analyze insurance claims data.3. Worked on earthquake vulnerability model for various regions, including Canada and Mexico. Main responsibilities:• Extracted data necessary to develop damage functions• Developed visualization tools using Shiny library in R to summarize and visualize extensive amount of information effectively to be communicated to stakeholders and clients• Developed unknown weights (for age, height, etc.) for Mexico EQ model• Analyzed client books to identify the areas of improvement4. Model owner of vulnerability module for renewable energy sector subject to seismic hazard; Developed predictive models to estimate direct losses and business interruption to renewable energy sector in cases of earthquake and tsunami.5. Developed business interruption models using Machine Learning to estimate business interruption days subject to extreme events.

Education

• Texas A&M University

  Doctor of Philosophy - PhD

  2017 — 2021

• Isfahan University of Technology

  Bachelor of Science (BS)

  2010 — 2014

• Sharif University of Technology

  Master of Science (M.Sc.)

  2014 — 2016