Openings
We welcome enquiries from self-motivated researchers interested in robust machine learning, AI safety, computer vision, and learning from imperfect information.
Prospective PhD Students
Students with strong programming skills and a solid mathematical or statistical foundation are encouraged to get in touch, especially if their interests overlap with:
- learning with noisy, coarse, or incomplete supervision;
- AI safety, certification, and robust evaluation;
- foundation models for visual and multimodal data.
Visitors and Postdocs
Researchers with overlapping interests and their own fellowship, scholarship, or visiting support are welcome to discuss collaboration opportunities.
- short-term visits and research exchanges;
- joint papers on robust learning and AI safety;
- collaborative projects across machine learning and computer vision.
How to Apply
Please email Dr. Feng with the subject line [Prospective Student/Visitor] Your Name - Your Current Institution. Include the following materials:
- an up-to-date CV;
- transcripts for BSc and MSc degrees, where applicable;
- a brief research statement explaining your interests and fit with the lab;
- links to papers, code, or research projects, if available.