SIGKDD Awards

ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining. The original call for nomination is available here.

Review Criteria:

Relevance of the Dissertation to KDD
Originality of the Main Ideas in the Dissertation
Significance of Scientific Contributions
Technical Depth and Soundness of Dissertation (including experimental methodologies, theoretical results, etc.)
Overall Presentation and Readability of Dissertation (including organization, writing style and exposition, etc.)

Congratulations to all the outstanding students who were nominated and to the winners of this year.

Following are the granted awards, including one winner, one runner-up, and two honorable mentions.

WINNER

Dissertation title: On the Predictive Power of Graph Neural Networks
Weihua Hu, Stanford University (USA)

Weihua Hu works at Kumo AI to productionize Graph Neural Networks (GNNs) on modern relational databases. He received a Ph.D. degree from the Department of Computer Science at Stanford, advised by Prof. Jure Leskovec. He built machine learning theory/methods/benchmarks for graph-structured data, aiming to improve diverse real-world applications, such as recommender systems, drug/material discovery, and weather forecasting.

Before that, Weihua received a B.E. in Mathematical Engineering in 2016, and an M.S. in Computer Science in 2018, both from the University of Tokyo, where he worked with Prof. Masashi Sugiyama on machine learning and Prof. Hirosuke Yamamoto on information theory. He also worked with Prof. Jun'ichi Tsujii and Prof. Hideki Mima on natural language processing.

RUNNER UP

Dissertation title: Characterization and Detection of Disinformation Spreading in Online Social Networks
Francesco Pierri, Politecnico di Milano (Italy)

Francesco Pierri is an Assistant Professor in the Data Science Lab within the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. He is also affiliated with Indiana University Bloomington’s Observatory on Social Media (OSOME) and he has been a Visiting Scholar at the University of Southern California’s Information Sciences Institute.

He studies Responsible AI at the intersection of Artificial Intelligence and Computational Social Science, focusing on how digital platforms and online environments are shaped by generative AI. My work develops data-driven methods to build trustworthy and safe AI systems, with a particular focus on mitigating AI-amplified misinformation and disinformation, and strengthen the safety, accountability, and integrity of digital platforms as they adapt to these challenges.

HONORABLE MENTION

Dissertation title: Efficient and Secure Message Passing for Machine Learning
Xiaorui Liu, Michigan State  University (USA)

Xiaorui Liu has been an Assistant Professor of Computer Science at North Carolina State University since August 2022. He received his Ph.D. degree in Computer Science from Michigan State University in 2022 under the supervision of Dr. Jiliang Tang. Before that, he received his Master's and Bachelor's degrees from South China University of Technology. He was awarded the ACM SIGKDD Outstanding Dissertation Award (Runner-up, 2023), Amazon Research Award (2023), NCSU Data Science Academy Award (2023), NCSU Faculty Research and Professional Development Award (2023), Chinese Government Award for Outstanding Students Abroad (2022), Best Paper Honorable Mention Award at ICHI (2019), MSU Cloud Computing Fellowship (2021), and MSU Engineering Distinguished Fellowship (2017).