Success Stories: NIW Approved for a Ph.D. Student in the Field of Computational Biology in 7 Months
Client’s Testimonial:
"Thank you very much for helping with the I-140.”
On January 28th, 2020, we received another NIW (National Interest Waiver) approval for a Ph.D. Student in the Field of Computational Biology (Approval Notice).
General Field: Computational Biology
Position at the Time of Case Filing: Ph.D. Student
Country of Origin: Iran
State of Residence at the Time of Filing: Utah
Approval Notice Date: January 28th, 2020
Processing Time: 7 months, 1 day
Case Summary:
With a M.Eng. in electrical engineering and many years of experience working in the field of computational biology, our client decided that the time had come for him to secure a green card. He approached North America Immigration Law Group (NAILG) for help with the first step of the green card process: filing an I-140 petition. After evaluating his credentials, we determined that he would be a suitable candidate for EB-2 NIW (National Interest Waiver). These are some of the key points included in his petition:
- We noted the 6 peer-reviewed journal articles (2 of them first-authored) to his name, all of which were published in well-known scientific journals. The dissemination of our client’s work via journals ensured that various researchers around the world had access to his findings, and thus, are able to work collectively to progress the field as a whole.
- Thanks to Google Scholar and other reliable sources such as Scopus, we determined that our client's work had been cited 103 times at the time of filing. This proved to the USCIS that his findings impact the work of other researchers.
- To back up our argument that our client deserved the national interest waiver, we included recommendation letters volunteered by four other experts in the field. According to one of them: “This is incredibly useful because it often takes over a decade to get a new drug to the market in the United States. Therefore, computational biologists like [client], who apply machine-learning to biomedical study in order to significantly speed up and enhance these research projects, are a pivotal resource in modern medicine.”