As a data scientist at Cognomotiv, I apply my machine learning and deep learning skills to develop innovative solutions for autonomous driving and vehicle diagnostics. I work with a team of engineers and researchers to design, implement, and test ML algorithms and models for time-series IoT data using Python, C++ and ONNX.I am also a PhD candidate in Electrical and Electronics Engineering at the University of Houston, where I conduct cutting-edge research on federated learning, differential privacy, and data-driven optimization for wireless networks. In my recent work, I developed a cost-efficient federated learning algorithm and implemented it on edge devices (Jetson TX2, Xavier, and Nano). I have published tens of journals and conferences, including two of the top conferences for efficient federated learning design.I am passionate about solving real-world problems using machine learning and software development, and I am eager to learn new skills and technologies. I am looking for a full-time job that will challenge me and allow me to contribute to impactful projects.