Success Story: NIW Approval After RFE for an Artificial Intelligence Researcher Advancing Trustworthy AI
Client’s Testimonial:
"I am very grateful to the team for helping me successfully obtain my NIW approval. They guided me throughout the process, helped me draft the petition materials, and identified and organized the supporting documents that were most helpful for my case. Their professional support made the entire process much easier. Thank you very much for your excellent help!”
On May 29th, 2026, we received another EB-2 NIW (National Interest Waiver) approval for a PhD Candidate/Graduate Student Researcher in the Field of Artificial Intelligence (Approval Notice).
General Field: Artificial Intelligence
Position at the Time of Case Filing: PhD Candidate/Graduate Student Researcher
Country of Origin: China
State of Residence at the Time of Filing: New Jersey
Approval Notice Date: May 29th, 2026
Processing Time: 24 months, 7 days
Case Summary:
We are pleased to share that the client’s I-140 NIW petition was approved after receiving a Request for Evidence. The client holds an M.Sc. in electrical and computer engineering and works in the field of artificial intelligence, with a research focus on developing trustworthy models for real-world AI applications.
The client’s proposed endeavor centered on continuing research into state-of-the-art trustable AI models to improve the reliability and performance of technologies used in areas such as autonomous driving, chatbots, and mobile image and language processing. We presented this work as nationally important because trustworthy AI is not only a technical research goal, but also a necessary foundation for broader, safer adoption of AI systems in critical and everyday settings.
The client is currently conducting artificial intelligence research in a U.S. university research environment and plans to continue working on model alignment and model training for safety-critical applications. This current work aligned closely with the proposed endeavor and helped show that the client was not merely proposing a future research direction but was already making progress in the same specialized area.
We highlighted the client’s publication record in the context of computer science, where peer-reviewed conference publications can serve as major scholarly outputs. The client’s record included 5 peer-reviewed conference articles, 2 of them first-authored, 3 peer-reviewed conference workshop papers, 1 of them first-authored, and 1 first-authored preprint. The client’s published work had received 1,315 citations, which we explained as evidence that other researchers had repeatedly relied on the client’s methods and findings.
We did not present the citation count as sufficient by itself. Instead, we showed how an adjudicator could interpret the record as evidence of influence because several of the client’s papers were cited at unusually high rates for their field and year of publication. The petition also explained how independent researchers used the client’s work as a benchmark, comparison method, or technical foundation for their own AI studies. This helped demonstrate that the client’s research had moved beyond publication and had become part of the field’s ongoing development of more reliable AI systems.
The petition also emphasized the client’s peer-review activity. The client had completed at least 12 reviews for major AI research venues, showing that the field trusted the client’s technical judgment to evaluate the work of other researchers. To demonstrate the client’s significance, we organized the case around three main research themes about deep learning and large language models' safety and training efficiency. These themes allowed us to connect the client’s technical contributions to the broader national need for trustworthy, secure, and high-performing artificial intelligence.
The case was further supported by 2 recommendation letters from experts in the field. These letters helped explain the client’s technical contributions and connected the objective evidence, including publications, citations, peer review, and funded research, to the client’s ability to continue advancing the proposed endeavor.
“[Client’s] prowess in understanding model biases and his strong record of high-impact publications situate him as a leader in the field and establish his inherent value to the U.S.”
By presenting the client’s work as a focused, nationally important AI endeavor, and by explaining how the client’s research record showed independent reliance, peer trust, and continued progress in the field, we demonstrated that the client was well-positioned to advance the proposed endeavor and that waiving the job offer and labor certification requirements would benefit the United States.
We congratulate the client on this NIW approval and wish the client continued success in advancing trustworthy artificial intelligence research.