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<p style="text-align:center"> | ||
<name>Jiawei Zhang</name> | ||
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<p> I am incoming Ph.D. student in Computer Science at the <a href="https://cs.illinois.edu/">University of Illinois Urbana-Champaign</a>. I work as a research assistant in <a href="https://aisecure.github.io/GROUP/">Secure Learning Lab</a> advised by <a href="https://aisecure.github.io/">Prof. Bo Li</a>. Before that, I got my Bachelor's degree from <a href="https://www.zju.edu.cn/english/">Zhejiang University</a> in July 2021. | ||
<p> I am first-year Ph.D. student in Computer Science at the <a href="https://cs.illinois.edu/">University of Illinois Urbana-Champaign</a>. I work as a research assistant in <a href="https://aisecure.github.io/GROUP/">Secure Learning Lab</a> advised by <a href="https://aisecure.github.io/">Prof. Bo Li</a>. Before that, I got my Bachelor's degree from <a href="https://www.zju.edu.cn/english/">Zhejiang University</a> in July 2021. | ||
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My current research mainly focuses on <b>trustworthy machine learning</b>, emphasizing robustness, privacy, fairness, and explainability. Specifically, I aim to explore certifiably robust learning algorithms based on knowledge-enabled logical reasoning and develop more reliable machine learning systems in areas like computer vision and autonomous driving. | ||
My current research predominantly centers on <b>Trustworthy Machine Learning</b>, especially for Large Language Model (LLM). I’m particularly interested in enhancing their trustworthiness by mitigating issues like hallucination, using external knowledge sources as leverage. While my foundation in robustness, privacy, fairness, and explainability remains intact, my renewed focus aims at the integration of these principles into the development and understanding of LLMs, thereby ensuring they align more closely with human values and expectations. | ||
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<a href="mailto:[email protected]">Email</a>  /  | ||
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