I am a computer science researcher with a strong foundation in machine learning and software development. I am engaged in cutting-edge research focused on the reliability and response of deep learning applications under various hardware conditions. My research specifically addresses the effects of hard and soft errors on specialized hardware such as systolic arrays and GPUs aiming to enhance the robustness of deep learning models for real-world use. With experience in developing advanced AI workflows and conducting performance analysis, I have applied my knowledge to various innovative projects, from face recognition systems to robotics. My background combines technical depth with a passion for solving complex problems, equipping me to make significant contributions to innovative research and development efforts.
The mission of Make Programming Simple Lab is to investigate novel architectural, compiler, runtime, and system operation mechanisms to make the task of programming complex and ambitious applications easier on distributed and heterogeneous computing platforms.