1. The Proposed Endeavor

The client proposed to develop and deploy AI-enabled sensing and data-fusion methods for real-time roadway condition assessment. By using computer vision and edge-AI technologies to detect pavement distress and integrate this data into agency workflows, the endeavor aimed to improve transportation safety, system reliability, and lifecycle cost efficiency.

Because these technologies support predictive, safety-aware maintenance at scale, the proposed work has clear relevance for U.S. infrastructure agencies responsible for managing large and aging transportation networks.

2. The Strategy

To secure approval in just 20 days without an RFE, the petition strategy was carefully mapped to each NIW prong under Matter of Dhanasar.

Establishing National Importance Through Government-Recognized Priorities (Prong 1)

We framed the client’s civil engineering research through the lens of Artificial Intelligence, explicitly connecting his work to the National Science and Technology Council’s Critical and Emerging Technologies (CET) list. By aligning AI-driven roadway sensing with federally recognized priorities in infrastructure resilience and intelligent systems, we demonstrated that the proposed endeavor was not merely academic in nature but directly supported national transportation and safety objectives.

This positioning reinforced that the work addressed challenges of national importance rather than localized or institution-specific concerns.

Demonstrating Independent Impact Despite Student Status (Prong 2)

To address USCIS concerns regarding student status, we relied on objective evidence of the client’s influence in the field. Several of his publications ranked in the top 1% and top 10% of most-cited articles in their respective years, demonstrating that his research was already shaping scholarly and technical discourse.

In addition, his extensive peer-review activity and first-authored publication record established that he was operating at a level comparable to, or exceeding, that of many established researchers. This evidence showed that the client was well-positioned to advance the proposed endeavor independently, despite still being enrolled in a Ph.D. program.

Bridging Student Status and Future Contributions With a Letter of Intent (Prong 2 and Prong 3)

To address the absence of a permanent job offer, we advised the client to obtain a Letter of Intent from his academic institution. The letter confirmed the university’s intent to employ him as a Research Associate upon completion of his Ph.D.

This document served a dual purpose. First, it demonstrated continuity of work and credible future plans, supporting the conclusion that the client was well-positioned to advance the endeavor after graduation (Prong 2). Second, it strengthened the argument that waiving the labor certification requirement would benefit the United States by allowing his urgently needed AI expertise to be deployed without delay or procedural barriers (Prong 3).

Attorney’s Note: Letters of Intent and the Labor Certification Waiver

For Ph.D. candidates and early-career researchers, the lack of a permanent job offer is common and does not preclude NIW approval. A formal employment contract is not required. In this case, the Letter of Intent provided persuasive evidence that the applicant had secured future work in the field while avoiding the delays associated with the labor certification process. When combined with strong evidence of independent impact, it supported the conclusion that waiving the job offer requirement was beneficial to the United States.