generative models

Advancing Domain-Specific Intelligence with LLMs & KGs: A Five-Year Journey Toward the Future

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B9 L2 R2325

This talk will cover my research journey in AI, focusing on developing AI-powered Knowledge Graph engines, LLM-driven chatbot platforms, and data science automation, leading to impactful collaborations and publications and striving towards LLM-powered generative AI in specialized domains, exploring their potential and limitations across various applications.

Xiaoqian Shen

Education Xiaoqian Shen is a Master's student at Vision-CAIR group in Visual Computing Center (VCC), King Abdullah University of Science and Technology (KAUST). • 2018-2022: BSc in Computer Science & Technology Dept. of Computer Science and Technology, Jilin University, China Research Interest • My research mainly focuses on leveraging natural language to facilitate better visual representation in a low-resource setting. Work Experience • Medical relation extraction for Chinese medicine instructions, 2021, Tsinghua University, China • Self-supervised Learning for medical image segmentation

Ivan Skorokhodov

Ph.D. Student, Computer Science
Ivan Skorokhodov is a Ph.D. candidate in the Computer Science Program under the supervision of Professor Peter Wonka at Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). His research interests include such areas of deep learning as generative models, hypernetworks and neural rendering. Ivan Skorokhodov has obtained his Ph.D degree and graduated in March 2023. Education and Early Career Ivan obtained his bachelor's degree in Management from the Moscow Engineering Physics Institute in 2014. He continued his studies there and received his master's degree