Success Story: NIW Approval for Iranian Teacher Assistant Leveraging LLMs in Computer Engineering
Client’s Testimonial:
“I’m extremely grateful for all your support throughout the process.”
On February 5th, 2025, we received another EB-2 NIW (National Interest Waiver) approval for a Teacher Assistant in the field of Computer Engineering (Approval Notice).
General Field: Computer Engineering
Position at the Time of Case Filing: Teacher Assistant
Country of Origin: Iran
State of Residence at the Time of Filing: Florida
Approval Notice Date: February 5th, 2025
Processing Time: 14 days (Premium Processing Requested)
Case Summary:
We are pleased to share the success story of an EB-2 NIW (National Interest Waiver) approval. This approval was granted to a Ph.D. candidate from Iran whose work is advancing AI-driven hardware design. At the time of filing, the client was conducting research at a U.S. university, with a focus on streamlining electronic system development using large language models. His research proposed novel ways to improve hardware workflows and reduce time-to-market. These advancements align with national interests in AI and critical technology infrastructure.
Proposed Endeavor with National Significance
The client’s endeavor centers on leveraging, integrating, and optimizing large language models (LLMs) to streamline the hardware design workflow and reduce production delays for electronic systems. His research contributes to the U.S. electronics manufacturing industry, which supports trillions in GDP and global leadership in semiconductor technologies. By automating Verilog code generation and integrating AI with electronic design automation (EDA), the client’s work addresses national priorities in technological competitiveness and innovation.
Well Positioned to Advance the Proposed Endeavor
With an M.Sc. in computer engineering, the client has produced impactful research on both arithmetic optimization in residue number systems and AI applications in hardware verification. His publication record includes 2 peer-reviewed journal articles, 2 conference papers (including 1 first-authored), 5 preprints, and technical reports. One of his journal articles ranks in the top 10% most-cited engineering papers of its publication year. He has also completed at least 5 peer reviews for top-tier venues such as IEEE TCAD and IEEE CAS-I. These credentials affirm his ability to lead further innovation in this domain.
Evidence of Influence and Recognition
NAILG highlighted the client’s scholarly impact through citation analysis and third-party usage of his work. His research has been cited 22 times and adopted by global researchers to improve Verilog code generation, arithmetic hardware design, and hardware verification. One paper was used as a foundation for Verilog code generation, as it introduced a comprehensive dataset specifically designed for training LLMs. Independent experts emphasized that his contributions support the growing need for reliable and efficient AI tools in semiconductor and electronics workflows.
Expert Testimonials Supporting the Petition
Two experts, including one independent recommender, endorsed the client’s petition by highlighting his technical innovations in electronic design automation (EDA).
One recommender noted:
“Overall, [Client]'s research has provided methods for AI integration with traditional EDA procedures, contributing to streamlined hardware design, reduced error rate, and accelerated innovation in semiconductor advancement.”
These endorsements underscored the national relevance and scientific merit of his work.Strategic Filing and Approval Outcome
NAILG built a strong petition demonstrating how the client’s proposed endeavor addressed critical U.S. technology interests. With documented influence, scholarly productivity, and future research plans, his petition was approved without an RFE.
We are proud to have supported this accomplished researcher and look forward to his continued innovations in AI-driven EDA. This approval underscores NAILG’s dedication to securing immigration success for experts contributing to U.S. scientific leadership.