Call for Papers - SIAM Conference on Data Mining 2024

SDM 2024 - Houston, US

Image credit: SDM 24

I am honored and overjoyed to have been selected as the Publicity Chair alongside with Li Zhang (incoming Assistant Professor at University of Texas Rio Grande) and Guanjie Zheng (Assistant Professor at Shanghai Jiaotong University) for the prestigious SIAM Data Mining Conference. As the Publicity Chair, I am enthusiastic about showcasing the groundbreaking work of researchers and fostering a sense of excitement and anticipation for the upcoming event. I look forward to leveraging my role to engage with the global data mining community and ensure the conference’s success in fostering knowledge exchange and innovation.

Venue: Westin Houston, Memorial City | Houston, TX, U.S.

Time of the conference: April 18 - 20, 2024

Call for contributions

Abstract Submission: September 15, 2023, 11:59pm (US Pacific time) Full Paper Submission: September 22, 2023, 11:59pm (US Pacific time) Blue Sky Idea Submission: September 22, 2023, 11:59pm (US Pacific time)

Workshop Proposals: October 6, 2023, 11:59pm (US Pacific time) Tutorial Proposals: October 6, 2023, 11:59pm (US Pacific time)

Apply for Assistance (Travel Fund Application Deadline: SIAM Student Travel Award and Early Career Travel Award Applications): January 18, 2024, 11:59pm (US Pacific time)


We invite researchers and practitioners to contribute to the SIAM Conference on Data Mining and Knowledge Discovery (SIAM-SDM), a platform for the exploration and dissemination of valuable knowledge derived from data—the heart of Data Science. This conference serves as a vital forum for addressing challenges in various domains, including science, engineering, healthcare, business, and medicine, where vast, intricate, and noisy datasets demand sophisticated and principled analysis techniques.

Data mining plays a pivotal role in extracting insights and patterns from large datasets, driving advancements in diverse fields. We are seeking publications in a wide range of topics, including data mining methods and algorithms, applications, as well as topics related to human factors and social Issues.

Workshop and Tutorials

A series of focused workshops will be held on the conference’s final day, providing a collaborative space to delve deeper into specific data mining topics. Consider organizing workshops or tutorials, as my team did last year with Algorithmic Fairness in Artificial intelligence, Machine learning and Decision making Workshop!

Blue Sky Idea Track

One nice thing about SDM’24 is the Blue Sky Idea Track. The goal of the Blue Sky Idea Track is to invite members of our research community to present position papers that may help inform or shape new directions of research. These are not typical conference research papers, rather they are expected to be visionary papers that set a direction. It would be nice to see what the novel ideas are!

Submission guidelines:

Accepted contributions will be published in archival form and made available on the SIAM website, ensuring wide dissemination and recognition for your valuable research. Authors are requested to submit original and unpublished work, adhering to the formatting and submission guidelines available on the conference website.

All papers should have a maximum length of nine pages (single-spaced, two column, 10-point font, and at least 1" margin on each side). Authors should use U.S. Letter (8.5" x 11") paper size. Papers must have an abstract with a maximum of 300 words and a keyword list with no more than six keywords. Authors are required to submit their papers electronically in PDF format (postscript files can be converted using standard converters) through Microsoft CMT.

Papers must be prepared in LaTeX2e, and formatted using SIAM’s double-column macro. The macro is available here. Make sure you use the SIAM macro; papers prepared using other macros will not be accepted.

Authors are not prohibited from using large language models (like ChatGPT, LaMDA, or LLaMA) to edit or polish the authors’ written text. However, the authors are responsible for ensuring the originality and correctness of the entire content of the paper. If the proposed research method involves the use of large language models or comparison against existing large language models, the paper needs to provide sufficient details on the methodology and implementation to ensure transparency and reproducibility (e.g., adding a paragraph on “use of large language model”). Authors will be required to disclose the use of large language models in the paper submission form.