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Dragan Labalo has extensive work experience in the field of signal processing and firmware engineering. Dragan is currently employed at Ethernovia as a Signal Processing Engineer, working on undisclosed projects. Prior to this, they worked at Amazon Lab126 as a Senior DSP FW Engineer for five months. From 2009 to 2018, they held the position of Senior Principal Engineer at Aquantia, where they served as the DSP Firmware lead and was responsible for all signal processing firmware aspects of 10GBasetT. Dragan also played a crucial role in defining DSP specifications for next generation products. Before that, Dragan worked as a Senior Software Engineer at Digital Fountain (Qualcomm) for eight months, as a Senior DSP Engineer at ArrayComm for nine months, and as a DSP Software Engineer at Texas Instruments for two years. Dragan began their career as a DSP Software Engineer at Analog Devices, where they specialized in DSP algorithm development for DSL modem and video decoders and provided customer support. Prior to joining Analog Devices, Dragan worked for a year as a DSP Software Engineer at Comspace.

Dragan Labalo earned a Bachelor of Science (BS) degree in Electrical Engineering from The University of Belgrade from 1987 to 1994. Dragan later pursued a Master of Science (MS) degree at The University of Texas at Arlington from 1998 to 1999. In 2001, Dragan attended Northeastern University and studied Electrical Engineering, graduating in 2004. Additionally, Dragan has obtained several certifications, including the "FPGA Design for Embedded Systems Specialization," "Hardware Description Languages for FPGA Design," and "Introduction to FPGA Design for Embedded Systems" from Coursera in March 2022. Other certifications include "Functional Program Design in Scala," "Effective Programming in Scala," and "Functional Programming Principles in Scala" from Coursera in 2021. Dragan also holds certifications from Udacity, including "Self Driving Car Engineer" in November 2019, and has completed various Coursera courses related to machine learning, computer architecture, electronics, and security between 2017 and 2018.