Partha Acharjee has worked in various roles since 2010. In 2010, they were a Specialist and Engineer of Network Optimization at Robi Axiata Limited, where they built automation toolsets to generate daily reports, designed a library of customized equations in VBA, and performed GSM network tuning and refresh projects. From 2012 to 2014, they worked as a Graduate Research and Teaching Assistant at the University of Maryland Baltimore County, where they designed and published a machine learning algorithm to remove gradient artifact from concurrently collected EEG-fMRI data. From 2014 to 2017, they were a Graduate Research Assistant at The University of Texas at Arlington, where they developed and published algorithms to extract 3D features from the airborne LiDAR point cloud, collaborated with a government agency and ESRI in an agile software development environment to implement the published feature extraction algorithm, and proposed and published an algorithm to estimate annual solar potential on the urban scene. Since 2017, they have been a Sr. Research Engineer at Topaz Labs, where they designed and implemented an OpenGL-based inference engine to deploy Deep Learning models. This inference engine is optimized for various GPUs on MAC and Windows.
Partha Acharjee has obtained four degrees in the field of Electrical and Electronics Engineering. Partha earned a Bachelor of Science (B.Sc.) from Bangladesh University of Engineering and Technology in 2009. Partha then went on to obtain a Master of Science (M.Sc.) from the same university in 2012. In 2014, they earned a Master of Science (M.S.) from the University of Maryland Baltimore County. Finally, they earned a Doctor of Philosophy (PhD) from The University of Texas at Arlington in 2017.
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