Success Story: From Large Language Model Systems Research to EB-1A Approval for a Machine Learning Systems Expert
Client’s Testimonial:
"Thank you so much to the whole team for supporting my case. Special thanks to the two attorneys, who helped with my initial filing and the RFE response. There are no words to fully express my gratitude. It has been so nice working with you to get things landed, and I greatly appreciate your support. This approval means a lot to me, especially at a time when immigration policy seems to be getting stricter and stricter.”
On August 26th, 2026, we received another EB-1A (Alien of Extraordinary Ability) approval for a Ph.D. Candidate in the Field of Machine Learning Systems (Approval Notice).
General Field: Machine Learning Systems
Position at the Time of Case Filing: Ph.D. Candidate
Country of Origin: China
State of Residence at the Time of Filing: Pennsylvania
Approval Notice Date: August 26th, 2026
Processing Time: 3 months, 27 days (Premium Processing Requested)
Case Summary:
As industries increasingly rely on large language models and advanced artificial intelligence (AI) systems, researchers face an important challenge: making AI infrastructure more efficient, scalable, reliable, and practical for real-world deployment. Our client, an expert in machine learning systems with an M.S. in computer science, has built a strong research record addressing these broader technological needs. We represented the client in an I-140 EB-1A petition, which was ultimately approved after a Request for Evidence (RFE).
Building More Efficient and Reliable AI Systems
The client’s work focuses on machine learning systems and large language model infrastructure. Rather than presenting the research as a set of isolated technical contributions, we emphasized how the client’s work helps improve the performance, reliability, and scalability of modern AI systems while reducing computational overhead and supporting more practical large-scale deployment.
At the time of filing, the client was pursuing a Ph.D. at a U.S. university and planned to continue his research career in the United States. His proposed work would advance machine learning systems and artificial intelligence while supporting efficient computing, technological innovation, and U.S. competitiveness.
A Record of Research That Others Have Used
To demonstrate that the client had reached the level required for EB-1A classification, we presented several complementary indicators of research productivity, recognition, and influence, including 8 peer-reviewed conference articles (1 of which was first-authored), 5 preprints, 872 citations to the client’s published research, and at least 13 completed peer reviews.
The petition did not rely on these figures as accomplishments that spoke for themselves. Instead, we demonstrated how independent researchers had recognized, referenced, and built upon the client’s research, methods, and technical contributions in subsequent work within the broader fields of machine learning, artificial intelligence, and computer science.
The petition was additionally supported by 4 letters of recommendation from experts in the field. These letters helped explain the originality, influence, and continuing importance of the client’s research in machine learning systems, large language model infrastructure, and high-performance artificial intelligence deployment. One expert noted:
“Ultimately, [Client’s] background in the machine learning systems field indicates that his work must continue in the United States.”
We further showed that the client’s work had received support from the National Science Foundation (NSF), the Defense Advanced Research Projects Agency (DARPA), and the U.S. Department of Energy (DOE), demonstrating the relevance of the client’s work to science, technology, artificial intelligence, and national defense. In addition, we highlighted the client’s open-source contributions and the use of his tools by major technology platforms, showing that his work had practical value beyond publication and had contributed to the development of modern AI infrastructure.
EB-1A Approval
After USCIS issued an RFE, North America Immigration Law Group submitted a comprehensive response highlighting the client’s research impact, peer-review activity, open-source contributions, expert support, and continued U.S. work. USCIS subsequently approved the I-140 EB-1A petition, recognizing the client’s extraordinary ability in machine learning systems and artificial intelligence infrastructure.