Zifeng Wang

Zifeng Wang is an accomplished researcher with extensive experience in machine learning and deep learning models. Zifeng worked at i-VisionGroup and Future Communications & Internet LAB at Tsinghua University, focusing on video tracking and big data mining. Collaborations with Harvard Medical School led to the development of a pioneering deep learning model for predicting smoking status, resulting in a publication in PLoS Computational Biology. Zifeng also contributed to Google as a Research Intern and Senior Research Scientist, where significant advancements in large language model alignment were made, including the introduction of a novel continual learning method called DualPrompt. At Northeastern University, Zifeng led research in continual/lifelong learning, achieving multiple publications in prestigious AI/ML conferences while pursuing a PhD in Machine Learning.