Success Story: NIW Approved Without an RFE! We Assisted a Chinese Research Scientist in Securing Approval
Client’s Testimonial:
"I am very excited about the approval, which I greatly attribute to the clear guidance, prompt responses, and the experienced team at this firm. I also note that minimal edits were required on my end, which further reflects the quality of their work."
On June 2nd, 2026, we received another EB-2 NIW (National Interest Waiver) approval for a Research Scientist in the Field of Machine Learning (Approval Notice).
General Field: Machine Learning
Position at the Time of Case Filing: Research Scientist
Country of Origin: China
State of Residence at the Time of Filing: Massachusetts
Approval Notice Date: June 2nd, 2026
Processing Time: 22 months, 11 days
Case Summary:
We are pleased to share that the client’s I-140 National Interest Waiver petition was approved. The client, who holds an M.S. in computer science, is an expert in machine learning whose work focuses on probabilistic machine learning and Bayesian hierarchical modeling.
At the time of filing, the client was conducting machine learning research at a U.S. university and planned to continue developing probabilistic machine learning techniques, studying domain-specific information in statistical and machine learning models, and improving the efficiency of machine learning systems through various optimization methods. The petition framed this work as nationally important because stronger machine learning and data analysis tools support progress in predictive technologies, healthcare analytics, security, transportation, and next-generation artificial intelligence.
The client’s record included 5 peer-reviewed conference papers, 4 of which were first-authored. In computer science, conference publications can represent highly selective and influential scholarly output, so the petition explained the field-specific importance of this publication record rather than treating the number alone as sufficient. The client’s publications had also received 33 citations, including papers cited at rates above field averages for their publication years. We used this evidence to show that other researchers had relied on the client’s work in certain areas.
The petition also highlighted the client’s peer-review service. Having completed at least 10 reviews for respected machine learning and statistics conferences, the client had been trusted to evaluate other researchers’ work in the same field. This supported the argument that the client’s expertise was recognized by the professional community.
Another important part of the case was the funding record. The client’s research had received support from the National Science Foundation and the Key Technologies R&D Program of China. This helped demonstrate that the client’s work was connected to broader scientific and technological priorities, including the advancement of machine learning and data-driven research.
Expert Support
The petition included 4 letters of recommendation from experts in the field. These letters helped explain the technical importance of the client’s research and connected the client’s algorithms and frameworks to broader progress in machine learning and Bayesian statistics. One expert stated that: “It is clear that [Client] stands at the top of his field…”
The Approval
In presenting the case, we demonstrated the client’s significance through a combination of field-specific publication evidence, citation analysis, peer-review activity, funded research, and expert support. The petition showed that the client was not only producing research in a critical technology area but also developing tools that other researchers could use to improve advanced machine learning systems.
We congratulate the client on this I-140 NIW approval and wish him continued success in advancing machine learning methods that support more efficient, reliable, and impactful data analysis technologies.