Sarbajit Mukherjee Email & Phone Number

I am currently employed as a Senior Software Engineer at iWorQ Systems where I design software systems that help cities and counties streamline their work processes. I use AWS cloud services to build solutions for clients alongside analyzing and working with different granularity of data.I was previously working as a Postdoctoral researcher, where I built and applied different machine learning models to understand drought progression in Utah and Colorado. We include tweets from people living in and around the drought-affected lands to add value to our model. We plan to use our drought tracker to ''fill the gap'' left by traditional weather tracking stations and give researchers a better, faster picture of on-the-ground conditions "from people who live on and know the lands well."My doctoral dissertation was conducted under the guidance of Dr. Vladimir Kulyukin, where we designed an electronic beehive monitoring system called BeePi, that can be used to extract useful information on bee colony behavior and hive health without invasive beehive inspections and transportation costs. The system captured videos of forager traffic, audio of bees buzzing through sensors connected to a low-cost raspberry pi computer. We designed several machine learning and deep learning models that analyzed the data to address different aspects related to the health of a beehive. In the above research we also utilized predictive modeling to study the effect of different meteorological variables on the foraging activity. By fitting a linear regression model, we found that 71\% of the observed variation in the forager activity can be explained by the variation in evapotranspiration, visibility, temperature, pressure, and humidity. The algorithms, models, and data are freely available to interested research and citizen science communities.Along with that I am also working on designing a mobile app to provide a unique educational tool to help young people learn the principles of fluid mechanics. The tool will enable students to learn fluid mechanics concepts and state-of-the art optical measurement techniques in hands-on, visually stimulating ways. The goal is to develop, implement and disseminate a low-cost, mobile instructional Particle Image Velocimetry (mI-PIV) tool for science outreach and undergraduate fluid mechanics education. It is funded by the Office of Naval Research through The Navy and Marine Corps STEM Education, Outreach and Workforce Program.

Listed skills include C++, Matlab, Research, Sql, and 29 others.