Vargha Dadvar

Vargha Dadvar has a diverse work experience spanning multiple roles and industries. Vargha started their career as a Software Developer at شرکت جهان گستر پارس رادن, where they were responsible for designing and developing various systems using web and mobile platforms. Vargha then moved on to Planhat, where they worked as a Software and Machine Learning Engineer. In this role, they designed and developed the customer churn prediction data and ML pipeline, applying ensemble models learned from multiple time-series and text data sources. Vargha also worked at the University of Waterloo as a Graduate Researcher, where they proposed and developed a pipelined framework for explaining image classifier CNNs and developed a deep learning model for evaluating the effectiveness of COVID-19 policies. Currently, they are working at Mariner Partners as a Software and Machine Learning Engineer.

Vargha Dadvar completed a Bachelor of Science (B.S.) degree in Computer Science from the Baha'i Institute for Higher Education (BIHE) from 2007 to 2013. In 2020, they pursued a Master of Mathematics degree in Computer Science at the University of Waterloo, which they are expected to complete in 2022. Additionally, Vargha Dadvar obtained several certifications, including the "Building Cloud Computing Solutions at Scale Specialization," "Cloud Machine Learning Engineering and MLOps," "Cloud Data Engineering," "Cloud Computing Foundations," and "Cloud Virtualization, Containers and APIs" from Coursera in 2022. Vargha also obtained the "Mathematics for Machine Learning: Multivariate Calculus" and "Mathematics for Machine Learning: Linear Algebra" certifications from Coursera in 2020. Vargha Dadvar also completed certifications in subjects such as Linux, Linear Algebra through Computer Science Applications, Data Science and Machine Learning Essentials, and Introduction to Cloud Computing from various institutions like edX and Coursera between 2014 and 2016. Furthermore, they also pursued certifications in Introduction to Artificial Intelligence, Machine Learning, Pattern Discovery in Data Mining, Programming Mobile Applications for Android Handheld Systems, and Python for Data Science, although the specific details such as the institution and year are not provided.