Success Story: NIW Approval After RFE for a Computer Science Researcher Advancing AI Applications in Agriculture
Client’s Testimonial:
“When I received an RFE challenging all three prongs of my NIW petition, I was honestly worried. But the Chen Immigration team turned that setback into an opportunity. They built a comprehensive response strategy, guided me through gathering the right evidence-from recommendation letters and citation analyses to my personal statement - and were responsive to every question and suggestion I raised along the way. What impressed me most was their willingness to collaborate: they reviewed my input seriously, incorporated the additions that strengthened my case, and made sure nothing was left unaddressed. My petition was approved on the strength of that response. As a PhD student self-petitioning in a competitive field, I could not have asked for better partners in this process. I highly recommend Chen Immigration to any researcher pursuing an NIW.”
On August 21st, 2026, we received another EB-2 NIW (National Interest Waiver) approval for a Research Assistant in the Field of Computer Science (Approval Notice).
General Field: Computer Science
Position at the Time of Case Filing: Research Assistant
Country of Origin: Bangladesh
State at the Time of Case Filing: Illinois
Approval Notice Date: August 21st, 2026
Processing Time: 18 months, 8 days (Premium Processing Upgrade Requested)
Case Summary:
The growing use of artificial intelligence in agriculture creates opportunities to improve productivity, support animal health, and make agricultural practices more sustainable. Working in the field of computer science, the client has focused on applying machine learning, deep learning, and computer vision methods to practical scientific and societal challenges. At the time of the petition, the client was conducting computer science research at a U.S. university. The client sought an EB-2 National Interest Waiver (NIW) based on exceptional ability, and the petition was ultimately approved after receiving a Request for Evidence (RFE).
The proposed endeavor centered on developing and optimizing advanced computational models for agricultural applications. More specifically, the client planned to continue developing AI-based approaches that could automatically identify agricultural problems affecting crops and livestock. Rather than presenting this research simply as a technical undertaking, the petition connected the endeavor to broader U.S. interests in agricultural productivity, animal health, food security, sustainability, and technological innovation. It also emphasized that artificial intelligence, machine learning, and deep learning fall within areas recognized as critical and emerging technologies.
To demonstrate that the client was well positioned to advance this endeavor, the petition presented a substantial record of scholarly activity:
- 6 peer-reviewed journal articles, including 4 first-authored articles
13 peer-reviewed conference articles, including 6 first-authored articles
- 4 book chapters, including 1 first-authored chapter
- 266 citations to the client’s publications
- At least 8 completed peer reviews
These figures were not presented as sufficient by themselves. Instead, the petition explained what they showed about the client’s standing and influence. Independent researchers had relied on the client’s methods and findings in subsequent work spanning agricultural applications, medical analysis, information processing, and other computational problems. The petition further documented that at least 15 of the client’s papers ranked among highly cited computer science publications for their respective publication years, including two in the top 1%. This comparative evidence helped demonstrate that the citation record reflected meaningful research influence rather than publication volume alone.
The petition also included 2 letters of recommendation from experts in the field. These letters provided additional context regarding the client’s technical expertise, prior research contributions, and ability to continue advancing the proposed endeavor. One recommender observed:
“Overall, [Client] promotes sustainability in agriculture, supporting national priorities in AI and machine learning for critical applications in the U.S. agricultural sector.”
The recommendation letters complemented the objective evidence by helping explain the significance of the client’s work from the perspective of other specialists rather than relying solely on numerical indicators.
Taken together, the petition positioned the client’s publication record, independent citations, peer-review activity, prior research impact, and continuing research plans as mutually reinforcing evidence. Following the additional scrutiny of an RFE, the I-140 NIW petition was approved, allowing the client to continue pursuing research at the intersection of computer science, artificial intelligence, and agricultural applications in the United States.