Lab pages help you see who works on a question and how the work develops over time. Pick a project and move between its paper, code, and author pages instead of memorizing lab names.
Find faculty and research groups at Chinese universities
Start with a faculty directory, then follow research interests, recent papers and student pages to individual teams.
- UESTC · School of Computer Science and Engineering · Faculty profiles
- Tsinghua University · Department of Computer Science and Technology · Faculty directory
- Peking University · School of Computer Science · Research institutes
- Fudan University · College of Computing and Intelligence · Research institutes
- Shanghai Jiao Tong University · School of Computer Science · Faculty directory
- Zhejiang University · College of Computer Science and Technology · Faculty profiles
- Nanjing University · School of Computer Science · Faculty
- University of Science and Technology of China · School of Computer Science and Technology · Faculty
- Harbin Institute of Technology · Faculty of Computing · Faculty directory
- Xi’an Jiaotong University · School of Computer Science and Technology · Faculty directory
- Renmin University of China · Gaoling School of Artificial Intelligence · Faculty
- The University of Hong Kong · School of Computing and Data Science · Academic staff
- The Chinese University of Hong Kong · Department of Computer Science and Engineering · Faculty
Vision, robotics, and embodied AI
- Stanford Vision and Learning Lab, SVL: visual understanding and learning, including BEHAVIOR and ObjectFolder. Start with the robot task, then inspect data, perception, and evaluation.
- Berkeley RAIL: learning algorithms, robotics, and vision, focused on acquiring flexible behavior. Choose a project under Publications, then find its implementation under Software.
- Tsinghua Embodied Intelligence Lab: an official university introduction. Follow it toward teams and projects, alongside the embodied AI materials.
- Shanghai Jiao Tong MVIG: machine vision and intelligence, with research and application information. Follow embodied projects to individual researchers.
- Berkeley AI Research, BAIR: a broader community. Read researchers' explanations in the blog archive, then find the relevant group.
Language models and efficient computation
- Stanford NLP: connect questions through papers, members, and teaching materials.
- MIT HAN Lab: efficient AI, compression, deployment, and the interaction of algorithms and systems. Follow work such as AWQ and SmoothQuant for quantization and inference speed.
- THUDM / THUKEG open-source organization: repositories leading to models, evaluation, and papers.
Industry: original releases and technical material
OpenAI News, Anthropic Research, Google DeepMind publications, and Google Research let you trace a news item to the original work. For relevant topics, inspect tasks, data, evaluation, and limitations.
After visiting a lab page
Choose a paper whose question interests you and find earlier or later work. Look at the people behind it: student pages often contain blogs, project records, or code with details the paper leaves out.
Before reaching out, organize questions and attempts using contact and collaboration. Read current recruitment conditions: for example, SVL's application entry specifies Stanford students, and MVIG's undergraduate internship entry includes institutional eligibility conditions.