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Dawood Khan

Principal Engineer at Thndr

Dawood Khan, PhD has a diverse work experience spanning over multiple industries and roles. Dawood started their career as a Senior Design Engineer at DarbarTAG, where they developed a SCADA system for remote monitoring and diagnostic reporting. Dawood then worked as a Senior Software Engineer at Streaming Networks, contributing to the development of a multimedia embedded system for digital video/audio recording.

Dawood's research career started at INRIA, where they worked as a Doctoral Researcher, focusing on distributed embedded systems. Dawood then joined LAAS-CNRS as a Postdoctoral Research Fellow.

In 2013, Dawood became an Assistant Professor at the University of Kashmir, conducting research and supervision in distributed embedded systems and machine learning.

Moving into industry again, Dawood joined fetchr as the Head of Applied R&D, where they played a pivotal role in revolutionizing logistics across emerging markets. Dawood then served as the Head of Applied R&D at noon, a large e-commerce platform in the Middle East.

Dawood's leadership skills and technical expertise led him to become the Head of Data, AI/ML at Hyke, where they shaped the technical roadmap and worked on various projects with a focus on data and ML ecosystem implementation.

Their most recent role was as a Principal Engineer at Swvl, where they provided technical leadership and mentoring, designed and built infrastructure for scalability and availability, and designed Swvl's MLOps platform.

Currently, Dawood is working as a Principal Engineer at Thndr.

Dawood Khan, PhD, obtained their Phd in Computer Science and Engineering from Universite de Lorraine in 2011. Prior to that, they completed their Master of Science in Computer Engineering from the University of Engineering and Technology, Taxila, from 2004 to 2006. Dawood also holds a BEIT degree in Engineering from Hamdard University, which they completed from 1999 to 2002. Additionally, they have obtained various certifications in fields such as AWS infrastructure, Docker automation, GitHub actions, Apache Spark, C++, and deep learning, among others.

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