华人研究者在KDD 2024大会上荣获多项荣誉，孟瑜摘得杰出博士论文奖
The 30th edition of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), the longest-standing and largest international top-tier academic conference in the field of data mining, unfolded from August 25 to 29 in the vibrant city of Barcelona, Spain. This prestigious event, which has historically been a pioneer in introducing concepts such as big data, data science, predictive analytics, and crowdsourcing, saw the announcement of its 2024 awards, recognizing outstanding achievements in research and application.
Among the highlights of this year’s awards, Dr. Yu Meng, an assistant professor at the University of Virginia (UVA), was honored with the ACM SIGKDD Outstanding Doctoral Dissertation Award for her work titled Efficient and Effective Learning of Text Representations. Dr. Meng, who joined UVA’s Computer Science (CS) Department in 2024 on a tenure-track position, completed her Ph.D. at the University of Illinois at Urbana-Champaign (UIUC) under the guidance of Professor Jiawei Han. She also served as a visiting researcher at the Princeton NLP Group, collaborating with Professor Denny Chen.
Dr. Meng’s groundbreaking dissertation focuses on developing efficient and effective methods for learning text representations in the context of natural language processing (NLP). It highlights the potential of spherical space for text representation learning, demonstrating superior capabilities in capturing semantic relationships through directional similarity. The study introduces self-supervised techniques in spherical space, discovers topic structures, and leverages large language models (LLMs) to generate training data for natural language understanding (NLU) tasks, thereby reducing the reliance on manually annotated data.
The Best Paper Award (Research Track) was jointly awarded to a team of six华人 scholars for their work, CAT: Interpretable Concept-based Taylor Additive Models. This innovative research contributes to the interpretability of complex models, a critical aspect in the field of data science.
In the Best Student Paper (Research Track) category, the prestigious award went to a collaborative effort between the University of Science and Technology of China (USTC) and Huawei for their study, Dataset Regeneration for Sequential Recommendation. The project explores new approaches to improve recommendation systems, an essential component in today’s data-driven world.
LinkedIn emerged as the recipient of the Best Paper Award (Applied Data Science Track), showcasing the practical applications and real-world impact of data mining research.
In addition to these main awards, two Time Test Awards were also presented, recognizing the lasting influence of research in the field.
The KDD 2024 conference not only celebrated the achievements of华人 researchers like Dr. Meng but also highlighted the global impact of their work on data mining, data science, and artificial intelligence. These awards serve as a testament to the dedication and innovative spirit of researchers in advancing the frontiers of knowledge discovery and data-driven decision-making.
For more information on the awarded papers, readers can access the following links:
- Dr. Yu Meng’s Outstanding Doctoral Dissertation: Link
- Ziniu Hu’s runner-up Outstanding Doctoral Dissertation: Link
The ACM SIGKDD Conference continues to foster a platform for researchers, practitioners, and academics to share their insights and advancements, pushing the boundaries of data mining and knowledge discovery to new heights.
【source】https://www.jiqizhixin.com/articles/2024-08-28-5
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