Qianqian Wang, incoming Assistant Professor at Harvard University and the Kempner Institute, is recruiting multiple PhD students for the 2026 cycle. Her research group focuses on computer vision and intelligence, with particular interests in 3D/4D perception, active perception, memory, representation learning, and visual reasoning. The group aims to understand and model the dynamic 3D world from everyday images and videos, with the long-term goal of building intelligent systems capable of perceiving, understanding, and continually learning from the ever-changing physical world.

Applicants with backgrounds in computer science, mathematics, engineering, or related quantitative sciences are encouraged to apply. The research environment at Harvard SEAS and the Kempner Institute offers opportunities to work on cutting-edge topics such as dynamic scene understanding, 4D reconstruction, and advanced representation learning. The group values curiosity and encourages students to explore new directions within the broad area of vision and intelligence.

The PhD program at Harvard SEAS requires a completed application, statement of purpose, three recommendation letters, transcripts, and a CV or resume. GRE scores are not accepted. International applicants must provide TOEFL or IELTS scores unless they hold a qualifying degree from an English-instruction institution. The application deadline is December 15, 2025. Applicants should list Qianqian Wang as a faculty of interest in their application.

While the post does not specify funding details, Harvard SEAS PhD positions are typically fully funded, covering tuition and providing a stipend. Prospective students are encouraged to review the official program website for the most up-to-date information on funding and eligibility.

For more information about Qianqian Wang's research, visit her academic page at https://qianqianwang68.github.io. To apply, follow the instructions on the Harvard SEAS graduate admissions page: https://seas.harvard.edu/prospective-students/prospective-graduate-students/how-apply.