Mohsen Vazirizade

About Mohsen Vazirizade

At Apple, I design and deploy deep learning–based solutions and leverage the proper metrics to enhance user experiences. Previously at Cruise, I focused on enhancing the performance, safety & reliability of our AV stack, which involves utilizing field data, simulations, statistical methods, Deep Learning & Machine Learning techniques. I also lead a team of contractors preparing safety metrics for NHSTA. As an ML SWE at Walmart, I bridged the gap between data science and engineering teams by integrating ML pipelines into DevOps workflows. At Rivian, I leveraged big data tools to develop prediction, diagnostics, prognostics, and anomaly detection models. I also built large-scale data pipelines and created an internal data interaction library that saved over $4M/year.Previously, I worked on multiple projects, including developing Artificial Intelligence agents for integrated data-driven technologies for smart cities and analyzing transportation systems using network science. During my Ph.D, supported by NSF, the focus of my research was risk estimation, uncertainty modeling, and AI. Risk requires the modeling of the environment, which was another part of my research using Bayesian statistical modeling and MCMC. 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.I have published in prestigious venues like ECML and ICDM and have authored over 30 peer-reviewed papers, books, and reports, resulting in over 250 citations, which establishes me as a top-tier researcher. Computer Skills: Python (pytorch, tensorflow, numPy, scipy, pandas, geopandas, statsmodels, scikit-learn, keras, tensorflow, flask, dash, pyspark, pulp, networkx, nxviz, plotly, folium, shapely, LifeLine, scikit-survival, darts, prophet, pycaret, causalinference, mlflow, etc.), R (shiny, Swirl, knitr, caret, tm, dplyr, ggplot2, plotly, googleVis, leaflet, igraph, etc.), MATLAB, C++, SQL (Microsoft SQL Server, BigQuery, Athena, Redshift), NoSQL (MongoDB), AWS, GCP, Azure, Databricks, Airflow, DLT, DBT, AutoML, MLflow, MLOps, DataOps, Tableau, Apache Superset (Preset and Glass), Grafana, CICD, Jenkins, Docker, Terraform, ArcGIS, Auto CAD

Experience

1. Sr Machine Learning Software Engineer

   Apple

   Apr 2025 — Present · San Francisco, CA, US

Education

• Iran University of Science and Technology

  Bachelor's degree, Civil and Environemntal Engineering

• Vanderbilt University

  Post Doctoral, Computer Science

• University of Arizona

  Doctor of Philosophy - PhD, Major: Engineering Mechanics, Minor: Computer Science

• University of Arizona

  Master's degree, Industrial Engineering

  2017 — 2019

• Sharif University of Technology

  Master of Science (M.Sc.), Risk and Earthquake Engineering

  2013 — 2015

Skills

• Matlab
• Arena Simulation Software
• Seismoartif
• Reliability
• Machine Learning
• Microsoft Powerpoint
• Structural Analysis
• Etabs
• Neural Networks
• Research
• Probabilistic Modeling
• Autocad
• Acdsee
• Failure Mode and Effects Analysis (Fmea)
• Ansys
• Moldeing
• Seismostruct
• Opensees
• Analytical Skills
• Engineering
• Python
• Responsible Conduct of Research
• Mathematical Analysis
• Artificial Neural Networks
• Simulation
• Artificial Intelligence
• Rt
• Structural Engineering
• Problem Solving
• Root Cause Analysis
• Root Cause Problem Solving
• Seismosoft
• Microsoft Office
• Seismic Design
• Seismobuild
• R
• Quality Engineering
• Sap
• Teaching
• Steel Design