Case Summary:     

We are pleased to announce that the EB-2 NIW (National Interest Waiver) petition for a research assistant from China has been successfully approved. With a research focus on privacy-aware machine learning and distributed model training, this client is contributing to core challenges in computer science that affect both academic advancement and practical applications across industries.

Shaping the Future of Federated and Secure Learning

The client’s work explores innovative strategies to develop machine learning frameworks that are both scalable and secure. His research introduces new methodologies in federated learning, multi-center image synthesis, and privacy-preserving generative models—techniques crucial for domains requiring sensitive data protection, such as medical diagnostics, security systems, and collaborative artificial intelligence.

As a researcher, the client has consistently produced meaningful contributions on topics such as domain adaptation and robustness in synthetic data generation. His publications tackle key issues like how to train models effectively across distributed datasets without compromising data privacy, a matter of growing national interest.

Demonstrated Research Impact and Engagement

The petition emphasized the client’s active publication and peer review record:

• 1 peer-reviewed journal article,
• 5 conference papers (3 as first author), and
• 1 preprint.

These have collectively garnered 56 citations, with at least four papers ranking among the top 10% most cited in the client’s expertise field. This record was further supported by 16 completed peer reviews for respected venues, including IEEE journals and international computer science conferences.

Recognized by Leaders in the Field

In support of the petition, one independent recommender remarked:

“His innovations in federated learning and synthetic data generation models are of high value to ongoing research in the U.S., particularly where privacy regulations and distributed systems intersect.”

Such testimonials underscore how the client’s research is directly shaping future directions in distributed AI systems and secure learning infrastructure.

Approval Under the Dhanasar Framework

This petition, filed on January 29, 2024, and approved on February 11, 2025, clearly satisfied all three prongs of the Matter of Dhanasar framework. The case successfully demonstrated that:

• The client’s research possesses substantial merit and national importance,
• He is well-positioned to advance the endeavor, and
• It would benefit the United States to waive the job offer and labor certification requirements.

Another Win by NAILG

The North America Immigration Law Group (NAILG) is proud to have helped present this case with precision and clarity, leading to a swift and successful outcome. This approval affirms the client’s value as a researcher and further reflects NAILG’s commitment to supporting global talent contributing to the U.S. innovation ecosystem.