[Event at CIG] KDD 2024 - Call for Undergraduate Consortium

[Jordi Vitria]

 KDD 2024 - Call for Undergraduate Consortium

> Description
>
> The Undergraduate Consortium at KDD 2024 (KDD-UC) is an initiative that
> endeavors to expand and enhance the participation of undergraduate students
> of diverse backgrounds in research pertaining to knowledge discovery from
> data. Towards that goal, the KDD-UC will:
>
>    - Provide an undergraduate research paper submission track which will
>    be used to both provide critical feedback to undergraduate students on
>    their ongoing research projects and select a subset of students that will
>    be provided financial assistance to attend and present their work at KDD
>    2024.
>    - Organize student paper and poster presentations at KDD 2024, along
>    with participating reviewers that will provide additional feedback on talks.
>    - Match participating students with academic and industry mentors that
>    can provide them feedback on current or future research project ideas,
>    along with overall career advice.
>    - Organize a panel focused on rewards and potential challenges of
>    different research career pathways, including graduate school/PhD, research
>    labs, and industry.
>
>
> The KDD-UC will accept paper submissions from only undergraduate students
> (they should be the primary authors of the paper, and other authors and
> their advisor can be co-authors). Students exploring a career in data
> science research are encouraged to apply. Preference will be given to
> students who identify with groups traditionally underrepresented in the
> field of computing and/or students who have limited resources related to
> graduate school at their home institutions.
> Target Audience
>
> The aim of the KDD-UC is to broaden the participation of undergraduate
> students from different backgrounds in research pertaining to knowledge
> discovery from data by providing mentorship and support for the conference
> experience. We especially invite students who self-identify as
> underrepresented groups in computing, students from primarily undergraduate
> institutions, and students who have limited resources for research and
> graduate school at their home institutions.
>
> The target audience for the KDD-UC is current undergraduate students who:
>
>    - Have worked on a data science research project in one aspect of the
>    data science lifecycle including but not limited to: data cleaning and
>    preparation, data transformation, mining, inference, learning,
>    explainability, data privacy, and dissemination of results.
>    - Have genuine interest in pursuing graduate studies involving data
>    science research.
>    - Are in need of support and feedback from a mentor and data science
>    community for their interest in pursuing data science research after
>    graduation.
>
>
> Students who were not enrolled in an undergraduate program in the
> 2023-2024 academic year are not eligible for the Undergraduate Consortium.
> Important Dates
>
>    - May 23, 2024 – Submission deadline
>    - June 13, 2024 – Decisions announced
>    - August 25-29, 2024 – Undergraduate Consortium (exact date TBA)
>
> Application Instructions
>
> Applications must be submitted in full via the submission portal by
> 11:59:59 pm UTC-12 (Anywhere on Earth) on the stated deadline date.
> Application materials should not be anonymized.
>
> Submit the following materials using the following Web site:
> https://cmt3.research.microsoft.com/KDDUC2024.
> 1. Research Paper
>
> The research paper MUST be 4-6 pages, excluding references, using the ACM
> Conference Proceeding templates (two column format). References are limited
> to 1 page. Template guidelines are available here:
> https://www.acm.org/publications/proceedings-template. In addition,
> authors can provide an optional one (1) page supplement at the end of their
> submitted paper (it needs to be in the same PDF file and start at page 8)
> focused on reproducibility (include details for how someone can reproduce
> your work). An undergraduate student must be the leading author of the
> paper. Once the paper has been submitted, the set of authors cannot be
> changed.
> 2. Personal Statement
>
> The student’s personal statement will be submitted at the same time as the
> research paper using the CMT submission system. It should help readers
> understand the student’s interests, research experiences and contributions,
> and future goals for data science research. In their statement, they should
>
>    1. Answer the following questions:
>       - How did they start data science research, and how did they join
>       the presented research project in particular?
>       - Did they have difficulties in their pursuit of data science
>       research and how did they overcome these?
>       - What excites them about their research area that would drive them
>       to continue working on those problems after graduation?
>       - What is their expectation from participating in the UC and
>       receiving mentorship?
>    2. Discuss their specific role and contributions in the data science
>    project presented in their submitted research paper. They should:
>       - Write a short summary (2-3 sentences) describing the data science
>       project presented in the submitted research paper in a way that can be
>       understood by a broad audience within data science.
>       - Discuss whether project work was done as part of a team and/or
>       independently.
>       - Discuss their specific contributions to the submitted research
>       project, including:
>          - Did they design or implement algorithms?
>          - Did they design or implement the evaluation protocol?
>          - Did they contribute to the analysis of results?
>          - Did they contribute any other specific ideas of the project?
>       3. Provide contact information for the student’s advisor. The
>    advisor will be asked to submit a reference letter for the student (see
>    Item 3 below). The advisor’s name, institution, position, email, and phone
>    number should be included.
>
>
> Formatting
>
> Personal statements must be written using the NSF GRFP statement
> formatting guidelines, which require standard 8.5″x 11″ page size, Times
> New Roman font for all text, no smaller than 11-point (except text that is
> part of an image), 1″ margins on all sides, and no less than single spacing
> (approximately 6 lines per inch). Please use the provided template of the
> personal statement as follows.
> Template for personal statement
> <https://1drv.ms/w/s!AiezBGDS3-iYgRiqWteLkveT0aUk?e=grurks>
> 3. Reference from Advisor
>
> A request will be emailed to an advisor of the student’s choice (not
> necessarily a co-author of the paper) who can speak towards the student’s
> data science research interests and abilities. The advisor will be asked to
> provide some details about the student’s contribution to the submitted
> research project; the student’s progress through their current
> undergraduate program; and how they believe the student can contribute to,
> and benefit from, participating in the UC. The advisor should be a faculty
> member, post-doc, or professional researcher with a graduate degree who can
> speak to all of these points.
>
> Advisor questionnaires will be sent out shortly after the application
> submission deadline, and they are expected to be completed within a week.
> No letters of recommendation will be accepted.
> Review Criteria
>
> Applications will be reviewed according to the following criteria:
>
>    - Clarity and completeness of the submission packet;
>    - Level of progress in the student’s undergraduate degree program;
>    - Significance of the student’s research contribution in the submitted
>    research paper;
>    - Overall participation of the student in research projects;
>    - Utility of the UC participation and mentorship in support of the
>    student’s continuing in post-graduate data science research;
>    - And assessment of how the student can contribute to others
>    participating in the UC.
>
>
> Accepted applicants who also attend the UC will have their papers
> published by KDD (online only). Additionally, a subset of the students will
> be invited to present their papers orally during the UC, while the rest
> will be invited to present their work in the form of a poster.
> Financial Assistance
>
> All accepted applicants will receive some financial support towards
> attending the conference, in exchange for volunteering a few hours of their
> time at the conference. The maximum amount of support provided to each
> grantee is set by the sponsors (ACM SIGKDD, NSF), and they are intended to
> partially cover the grantee’s expenses. Travel may or may not be partially
> covered depending on the total availability of funds and the number of
> awards given. Conference registration will be waived for all students with
> accepted UC papers.
> Acknowledgments
>
> Support for the 2024 Undergraduate Consortium is graciously provided by
> ACM SIGKDD and the National Science Foundation.
> Undergraduate Consortium Chairs
>
> David Anastasiu <https://davidanastasiu.net/>, Santa Clara University
> Agata Lapedriza <https://s3.sunai.uoc.edu/web/agata/index.html>, EAI at
> Northeastern University / Universitat Oberta de Catalunya
> Agoritsa Polyzou <https://www.cis.fiu.edu/faculty-staff/agoritsa-polyzou/>,
> Florida International University
> Jordi Vitrià <https://algorismes.github.io/>, Universitat de Barcelona
> Contact email: KDD24-undergraduate-consortium-chairs at acm.org
>

-- 

*Jordi Vitrià*
https://algorismes.github.io/

*Departament de Matemàtiques i Informàtica*
Facultat de Matemàtiques i Informàtica
*Universitat de Barcelona*
Despatx P2.37
Gran Via de les Corts Catalanes, 585, 08007 Barcelona (map
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)
Tel. +34 934 021 653, www.ub.edu

*DataScience at UB*