Success Story: A Ph.D. Candidate from Pakistan Working in the Field of Reinforcement Learning Obtains NIW Approval with the help of NAILG’s Experts

“Thanks for the help in the whole process.”

General Field: Reinforcement Learning

Position at the Time of Case Filing: Ph.D. Candidate

Country of Origin: Pakistan

State of Residence at the Time of Filing: Illinois

Approval Notice Date: April 24^th, 2023

Processing Time: 2 months, 18 days

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Case Summary:

A client from Pakistan with an M.S. in mechanical engineering approached us to help him file the I-140 NIW (National Interest Waiver) petition; we, therefore, employed our team of experts to build a convincing case for him. We included details from his professional and academic career in his petition packet to support his claim to the NIW category.

We showcased that along with his academic qualifications:

• He was also actively engaged in the field of reinforcement learning as a Ph.D. candidate.

And that his proposed endeavor is to continue his research on developing and analyzing algorithms for learning in large population settings like financial systems, social media, and cyber security to solve safety and security problems that have emerged in the face of the increasingly connected world.

• Furthermore, due to its evident national importance, the client’s research has been supported with funding from the Air Force Office of Scientific Research and the U.S. Army Research Laboratory. This funding is reserved solely for research directed at advancing the national interest, including the development of cyber-security technologies that aid in key national security interests.

On the other hand, we highlighted that his academic performance has been responsible for several publications, and citations:

1. His research has resulted in 8 peer-reviewed conference papers (6 of them first-authored), 1 peer-reviewed journal article (also first-authored), and 1 book chapter.
2. His publications have been cited 42 times according to Google Scholar.
3. He has been invited to conduct peer review for at least 9 times.

Also, Experts in the field confirm client’s record of successful research has well positioned him to continue advancing the proposed endeavor as one out of four stated:

“…Security blind spots have ballooned in the face of the COVID-19 pandemic as well, as nearly half of the American labor force is now working from home, generating, accessing, and sharing data remotely more than ever. To safeguard the American population from these threats, [client’s] reinforcement learning research must be allowed to continue.”

The above evidence shows that the client’s work on integrating reinforcement learning to multiagent systems using the Mean-Field Game paradigm helps lower the extremely high cost of cyber-crime to the U.S. economy and thus holds significant value for commercial and governmental cyber-security in the United States.

We are thus very proud that our client got his NIW approval despite waiting for a long time. It has been an amazing journey with him. We wish him the very best in his future endeavors.

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