Currently, I work as a remote Algorithm Engineer at SW-Motion Company, where I contribute to the development of Advanced Driver Assistance Systems (ADAS) for mass production. My responsibilities encompass designing and implementing algorithms for functionalities such as Adaptive Cruise Control (ACC), Automatic Emergency Braking (AEB), Forward Collision Warning (FCW), Traffic Jam Assist (TJA), and Lane Assist Control (LAC). Following a Test-Driven Development (TDD) approach, I ensure robust algorithm performance through unit testing, software-in-the-loop (SIL) testing, and hardware-in-the-loop (HIL) setups prior to vehicle integration. Leveraging C/C++ for core development and Python for data visualization, I thrive in environments requiring precision, innovation, and adherence to high-quality standards.

As a graduate student and research assistant at Amirkabir University of Technology (Tehran Polytechnic), I deepened my expertise under the mentorship of Dr. Hassan Taheri. My work focused on advanced topics such as Deep Neural Networks, Artificial Intelligence, and Digital Electronic Systems, including embedded devices, FPGAs, and high-performance processors like GPGPU, DSP, and multicore CPUs. My master’s dissertation, inspired by a seminal MIT research paper, explored compressing Deep Neural Networks for faster training and inference. This research was successfully published by the IEEE Computer Society and laid the groundwork for efficient AI deployment on edge devices with limited computational resources.