About

Xiangjun (XJ) Wang is an accomplished Chief Algorithm Officer with over 15 years of experience in the field of Artificial Intelligence. He specializes in Machine Learning, Deep Learning, Reinforcement Learning, Data Mining, Information Retrieval, and Natural Language Processing. XJ is currently leading a team of world-class researchers and engineers at inspir.ai, working on decision-making AI with a focus on Deep Reinforcement Learning and Multi-Agent Reinforcement Learning in the areas of Game AI and Robotics. XJ's expertise in AI has been recognized by some of the most prestigious organizations in the industry. His team's accomplishments include an efficient Deep Reinforcement Learning agent, SCC, which mastered the game of StarCraft II and won the ICML 2021 competition. In addition, his team's Deep Reinforcement Learning agent beat a professional champion in the StarCraft AI competition in June 2020, and they won first place in the CVPR 2020/2021 Robotics Sim2Real Challenge. XJ's team also won first place in the NeurIPS 2018 Multi-Agent RL competition for Pommerman. Prior to his current role, XJ worked as a Lead Machine Learning Engineer/Researcher at Netflix, where he focused on R&D in recommendation and personalization algorithms. He also worked as a Researcher/Engineer at AT&T Interactive, where he focused on search indexing, ranking, and relevance. XJ holds a PhD in Computer Science from Arizona State University, where he is currently a candidate. He also holds a Master of Science and Bachelor of Science in Computer Science from Huazhong University of Science and Technology in China. XJ's technical expertise includes Reinforcement Learning, AI, ML, Information Retrieval, Search, Deep Learning, NLP, and Research Scientist. He is a highly accomplished professional with a passion for AI and a drive to push the boundaries of what is possible in the field.