Success Story: NIW Approval for a Control Engineering Expert Advancing AI-Driven Automated Insulin Delivery Systems
On May 18th, 2026, we received another EB-2 NIW (National Interest Waiver) approval for a Sr Staff Algorithm Research Engineer in the Field of Control Engineering (Approval Notice).
General Field: Control Engineering
Position at the Time of Case Filing: Sr Staff Algorithm Research Engineer
Country of Origin: Spain
State of Residence at the Time of Filing: Virginia
Approval Notice Date: May 18th, 2026
Processing Time: 5 months, 13 days (Premium Processing Upgrade Requested)
Case Summary:
The client, a Ph.D. in automation, robotics, and industrial informatics, was approved under the EB-2 National Interest Waiver (NIW) category for his work in control engineering and machine learning applied to automated insulin delivery systems. His proposed endeavor focuses on developing advanced control algorithms and neural network-based methods to improve insulin dosing systems, aiming to enhance glycemic control and quality of life for individuals with type 1 and type 2 diabetes.
He is currently engaged in research and development within the medical technology sector, where he applies control theory, disturbance rejection methods, and machine learning to next-generation automated insulin delivery devices. His work bridges engineering and healthcare by enabling more adaptive and computationally efficient insulin delivery solutions.
The petition demonstrated that the client has a strong record of research excellence and field influence, including 11 peer-reviewed journal articles (7 first-authored), 9 conference papers (6 first-authored), and 4 abstracts (2 first-authored), along with 513 citations to his work. He has also completed over 30 peer reviews, reflecting recognition of his expertise by the scientific community. In addition, his research has been supported by funding from a major U.S. federal health agency, further reinforcing its national relevance.
His research contributions include developing disturbance-observer-based control methods, extending robust control frameworks to complex dynamic systems, and designing lightweight neural networks that replicate computationally intensive insulin dosing algorithms for wearable devices. These innovations have been widely cited and adopted by other researchers, demonstrating independent reliance on his work across both control engineering and biomedical applications.
The case was further strengthened by four expert recommendation letters from recognized specialists in control systems and diabetes technology. These experts highlighted the client’s technical originality, the practical impact of his work, and his ability to advance automated insulin delivery systems. One recommender emphasized that: “Thus, his contributions to control engineering contribute to the safety of U.S. citizens and are in the best interests of the nation.”
Overall, the evidence established that the client is well positioned to continue advancing his proposed endeavor, which addresses a major and growing public health challenge. USCIS approved the NIW petition based on the substantial merit and national importance of his work, as well as his demonstrated ability to contribute meaningfully to the field of intelligent medical control systems.