Hello!I am a second-year Computer Engineering graduate student at the University of California, Riverside, with a strong foundation in Machine Learning, GPU Programming, Edge Computing, and Data Engineering. I also have two years of professional experience as a Software Engineer, specializing in backend development, data pipelines, and data manipulation.My technical interests lie in ML/AI acceleration, ML systems, AI on the Edge, Autonomous Vehicles, and Data Engineering. My academic and professional experiences reflect my passion for these areas.I am proficient in Python, C/C++, and CUDA C, with hands-on experience in frameworks like PyTorch, TensorBoard for model building and profiling, and ONNX & TensorRT for model optimization. Additionally, I am skilled in data manipulation and analysis using NumPy, Pandas, and SQL. My professional experience includes working with cloud platforms like Databricks, AWS, and Azure, along with simulation tools such as GPGPU-Sim, Gazebo, and CARLA, particularly in autonomous vehicle research.I’ve contributed to various projects, including developing a distributed multi-camera surveillance system, benchmarking GPU-based image convolution, and building real-time forecasting simulators on edge devices like Jetson Nano.Currently, I’m researching ways to optimize deep neural network (DNN) models for autonomous driving applications, focusing on enhancing inference speed and throughput in real-time systems with heterogeneous compute, under the guidance of Professor Dr. Hang Qiu in the CISL Lab.If you're looking for someone passionate about AI/ML, Edge Computing, GPU Acceleration, ML Performance/MLSys, Data Engineering, or autonomous vehicle technologies, feel free to reach out!