In my current role, I serve as the leader of the AI research team and work closely with other interdisciplinary teams. I focus on developing new AI models and algorithms, and exploring the application of AI technologies to areas such as autonomous driving, healthcare, and smart cities. I also collaborate with academia and actively participate in the AI community, publishing several academic papers and patents.

With the rise of AI technology, I turned to AI research and joined the AI research team at NVIDIA. I began to focus on deep learning and convolutional neural networks (CNN), proposing and implementing a novel image recognition algorithm that improves the efficiency of deep learning training on GPUs.

At Intel, a leading semiconductor company, software engineers play an important role in its organization and are responsible for developing and maintaining various software applications, tools, and drivers to meet the needs of Intel products. This may involve the development of underlying system software, optimizing the software to take full advantage of the performance and capabilities of Intel processors. This may include writing optimized code, tuning algorithms, optimizing memory usage, etc.

Design, develop, and optimize machine learning models in areas such as supervised learning, unsupervised learning, and reinforcement learning. This may involve data cleaning, feature engineering, model training and tuning, and optimization and adjustment of machine learning algorithms for Intel hardware platforms to fully utilize the performance and capabilities of hardware resources. This may include using Intel's hardware accelerators, instruction sets, and other features.

As a Data Intern, you will assist in collecting, organizing, and cleaning large-scale data to ensure data quality and consistency. Using statistics and machine learning techniques, you will perform data analysis to provide deep insights into your business and products. You will play an important role in building and evaluating data science models, providing critical feedback to the team on model performance and effectiveness. Through data visualization tools, you will present data and analysis results to help your team better understand and utilize data. Working closely with the AI team will enable you to gain a deep understanding of project needs and provide data support and solutions.