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<span style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt;">This is an announcement of Han Liu's Dissertation Defense.<br>
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Candidate: Han Liu<br>
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Date: Tuesday, May 28, 2024<br>
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Time: 10 am CT<br>
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Remote Location: <a href="https://uchicago.zoom.us/j/5431475712?pwd=T2hsWXRWZHJTRzBXc2duSkE4bkpkdz09" id="OWA60a4016e-db93-aa27-e19e-268a522c9a5e" class="OWAAutoLink" data-loopstyle="linkonly" style="text-align: left;">https://uchicago.zoom.us/j/5431475712?pwd=T2hsWXRWZHJTRzBXc2duSkE4bkpkdz09</a><br>
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Location: JCL 298<br>
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Title: Empowering humans with machines: from explanations to teaching<br>
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Abstract: Artificial intelligence has demonstrated increasing potential to assist humans in decision-making tasks. However, AI systems solve problems differently than humans, leading to varying performance in human-AI teams. An ideal human-AI collaboration
system should leverage the strengths of both humans and AI while mitigating their weaknesses. In this presentation, I will discuss how to empower humans with AI systems in decision-making tasks. First, I will explain how to understand human-AI teams under
different distribution types and interactive interfaces. Then, I will describe how to align AI models with human perceptions for better decision support. Finally, I will explore how to build AI-driven tutorials using vision-language models to assist and teach
humans in challenging image classification tasks.<br>
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Advisors: Chenhao Tan<br>
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Committee Members: Yuxin Chen, Chenhao Tan, and Aritrick Chatterjee<br>
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