TLDR: Dr. Han Zhao, an assistant professor of computer science at the University of Illinois Urbana-Champaign, has been awarded two significant grants from the National Science Foundation (NSF): a CAREER award and a CISE CORE award. These grants, totaling $1.1 million, will support his pioneering research in developing robust, fair, and interpretable artificial intelligence and machine learning systems.
Dr. Han Zhao, an esteemed assistant professor of computer science at the Siebel School of Computing and Data Science within The Grainger College of Engineering at the University of Illinois Urbana-Champaign, has been honored with two major National Science Foundation (NSF) awards: the prestigious CAREER award and a CISE CORE award. These grants underscore his significant contributions to the field of trustworthy machine learning and artificial intelligence.
The CAREER award, a highly competitive grant for early-career faculty, provides $600,000 in funding through July 2030. Dr. Zhao’s research under this award, titled ‘Efficient and Trustworthy Machine Learning via Post-Processing,’ will primarily focus on enhancing the trustworthiness of modern machine learning systems. This includes addressing critical aspects such as robustness, fairness, and privacy. The project specifically aims to improve group fairness, generalization across diverse tasks and domains, and data attribution. It will also explore post-processing techniques scalable to large language models (LLMs) to mitigate their inherent weaknesses in accuracy, robust generalization, and interpretability. Outcomes from this research are slated for integration into both undergraduate and graduate courses, and will be released as open-source software packages.
Concurrently, Dr. Zhao also received an NSF CISE CORE award, providing $500,000 for a period ending in August 2028. This grant supports his project, ‘Small: Neural Probabilistic Circuits: Towards Compositional and Interpretable Neuro-Symbolic AI.’ The core objective of this research is to propose and construct a neuro-symbolic AI system that is inherently interpretable by design, addressing a key challenge in making complex AI models more transparent and understandable.
Commenting on the dual recognition, Dr. Zhao expressed his gratitude, stating, “Needless to say, I was thrilled to hear the good news from my NSF program directors, especially during these challenging times. I am thankful to all the unwavering support and guidance offered from the school, my mentors, and my colleagues. I want to thank all my students for their sustained effort in pushing our research agenda forward.”
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Both award-winning projects align seamlessly with the mission of Dr. Zhao’s research group, the ‘Trustworthy Machine Learning Group.’ He noted the synergy between the two, explaining, “The CAREER award will focus on the robustness, fairness, and privacy aspects of modern machine learning systems. The CISE CORE award attempts to propose and build a neuro-symbolic AI system that is interpretable by design.” This dual focus highlights his comprehensive approach to building AI systems that are not only powerful but also reliable, equitable, and transparent.
