Illinois Tech Assistant Professor Receives Award for Using Insights from Human Immune System to Strengthen AI

Inspired by antigen-generating B cells, Ren Wang aims to make AI systems more robust and address the 鈥榖lack box鈥 problem

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Figure of Adaptive/Computational Immune Systems

CHICAGO鈥擩uly 25, 2023鈥For his groundbreaking research in fortifying artificial intelligence systems with insights gained from the human immune system, Ren Wang of Illinois Institute of Technology has received the prestigious from Oak Ridge Associated Universities (ORAU). Wang鈥檚 research may be used in the future to strengthen AI systems, making them more robust and resilient.

As AI has increasingly permeated our daily lives through technologies, such as ChatGPT鈥檚 natural language processing and facial recognition in smartphones, the technology鈥檚 vulnerability to attacks and errors has been exposed鈥攊ncluding everything from self-driving cars crashing to T-shirts designed to foil facial recognition.

鈥淭his is a very dangerous phenomenon,鈥 says Wang, an assistant professor in the Department of Electrical and Computer Engineering. 鈥淎 very small perturbation can lead to a totally wrong answer. For example, the AI model might predict a speed limit sign when there is actually a stop sign.鈥

Because AI systems are like a black box鈥攖hat is, it鈥檚 often not possible to know why an AI system makes any given decision鈥攊t鈥檚 difficult to develop techniques to keep them safe. To address this, Wang borrowed insights from the immune system鈥攕pecifically the adaptive mechanisms of B cells, which are integral components of our immune defenses.

鈥淏 cells generate antibodies to defend against certain types of attack, and that attack could be any antigen,鈥 says Wang. 鈥淲e hope to learn from this whole process and to capture some important patterns that we can use to improve the AI system.鈥

Wang鈥檚 research is not limited to broad-based AI applications; he鈥檚 particularly focused on AI-driven power system applications, such as power system control and stability analysis, requiring a high degree of robustness. By integrating physical constraints into his immune-inspired learning approach, Wang aims to create robust AI models for complex power grids that necessitate less data and have a refined search space.

鈥淚 believe that this is a very novel idea,鈥 says Wang, 鈥渁nd I believe this adaptive immune-inspired system will be very powerful.鈥

Wang is among 35 recipients selected from 167 applicants in 2023 for the Powe Award, which provides seed money for junior faculty members demonstrating exceptional promise in scientific research.

鈥淚t is a tremendous honor to have been selected as one of this year鈥檚 awardees, and I am immensely grateful,鈥 says Wang.

The award follows another notable achievement by Wang, who recently received a Computer and Information Science and Engineering Research Initiation Initiative award from the National Science Foundation.

Image: The process of the adaptive immune system developing solutions to remove antigens inspires the computational system model for developing solutions to remove adversaries. Information collected from the power grid and physical constraints are used in the practical implementation of the computational system.

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