Generative AI and the Future of Research Speaker Series: Yang Zhang

Yang Zhang is a Teaching Assistant Professor at the School of Information Sciences at the University of Illinois Urbana-Champaign (UIUC) and a senior researcher at UIUC's Social Sensing and Intelligence Lab. He is also a faculty affiliate of Illinois Informatics at UIUC. Previously, he was a Postdoctoral Research Associate at UIUC and a W. J. Cody Research Associate at Argonne National Laboratory. Yang earned his Ph.D. in Computer Science & Engineering from the University of Notre Dame, an M.S. in Data Science from Indiana University Bloomington, and a B.S. in Software Engineering from Wuhan University. His research focuses on human-centered AI, human-AI collaboration, deep learning, and generative AI. He has authored over 80 peer-reviewed conference and journal papers published in top venues such as ACM CSCW, ACM  Web Conference, AAAI, IJCAI, and IEEE BigData. His work has been recognized with prestigious honors, including the Outstanding Graduate Research Award from the University of Notre Dame and the W. J. Cody Research Associateship at Argonne National Laboratory.

Abstract:
Human-AI Collaboration centers on designing collaborative frameworks that integrate Artificial Intelligence (AI), particularly Large Language Models (LLMs), with human intelligence (HI) to tackle complex, real-world problems in social contexts. Human intelligence contributes unique capabilities such as reasoning, problem-solving, abstract thinking, and the ability to learn from experience. These attributes provide valuable context, domain expertise, and human-centered insights essential for understanding the intricate social and environmental factors that shape societies. Conversely, AI excels at processing large-scale data, identifying latent patterns, and making predictions, offering scalability and computational power for addressing complex issues. Motivated by the complementary yet distinct strengths of AI and HI, my research is built upon three core thrusts: human-AI collaborative design, calibration, and interaction. The design thrust leverages human-in-the-loop mechanisms to optimize neural architectures and hyperparameters efficiently, focusing on adaptive solutions for resource-constrained scenarios such as disaster response and urban monitoring. The calibration thrust addresses fairness, robustness, and cross-domain generalization by integrating AI and human intelligence through collective intelligence frameworks, ensuring alignment with diverse and dynamic domain requirements. The interaction thrust fosters seamless collaboration between humans and AI, integrating small and large language models with HI to maintain explainability, interpretability, and responsiveness in high-stakes applications. In this talk, I will discuss the technical contributions of these three thrusts, highlighting their impact on addressing societal challenges through human-AI collaboration.

About the speaker series:
The CIRSS Speaker Series continues in Spring with a new theme of “Generative AI and the Future of Research.” Our speakers will share their research on the opportunities and risks associated with the rapidly evolving landscape of generative AI usage in scholarship.

We meet most Wednesdays, 9am-10am Central time, in Zoom. Everyone is welcome to attend. More information, including upcoming speaker schedule and links to recordings, is available on the series website. For weekly updates on upcoming talks, subscribe to our CIRSS Seminars mailing list. Our Spring series is led by Yuanxi Fu and Timothy McPhillips, and supported by the Center for Informatics Research in Science and Scholarship (CIRSS) and the School of Information Sciences at the University of Illinois at Urbana-Champaign.