Xin is an associate in the Intellectual Property group at Michael Best where he specializes in patent law with a focus in artificial intelligence (AI) and other complex technologies. As a registered patent attorney, Xin has successfully handled a significant number of AI patent prosecution matters for prominent companies in the AI development space. His knowledge in AI and machine learning is complemented by a robust academic background in mathematics and statistics.
Prior to joining Michael Best, Xin honed his skills at a boutique patent law firm where he handled a substantial caseload for industry giants in the software and electronics sectors. His responsibilities included patent preparation and prosecution for AI, machine learning, and cloud computing inventions across task domains including image processing, natural language processing, computer vision, and autonomous systems. His work encompassed a wide range of neural network architectures including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Generative Adversarial Networks (GAN), Transformers, and Diffusion Models.
Xin has a keen interest in exploring emerging issues in intellectual property law related to AI and machine learning. He has published articles on topics such as claim interpretation for AI inventions in PTAB appeals and technical analyses of generative AI models.