We invite PhD students from the general areas of databases (DB), information retrieval (IR), and knowledge management (KM) to submit their proposals for participation in a PhD Symposium, which will be held during the 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023), a hybrid conference hosted in Birmingham, UK. We welcome submissions representing a broad spectrum of research topics relevant to the CIKM community. The goal of the PhD Symposium is to provide a platform for PhD students to present and receive feedback on their ongoing research. Students at different stages of their research will have the opportunity to present their work in a hybrid conference environment and discuss their research questions, goals, methods, and results. Participants will benefit from the feedback and advice by senior researchers in the field, which will be organized in the form of one-to-one discussions.
CIKM 2023 is deeply committed to improving the field by making the research community more diverse, equitable, and inclusive. We highly encourage women and students from other underrepresented demographic groups to submit their work.
Symposium scope and format
The objectives of the PhD Symposium are:
The Symposium format
includes: student presentations with plenary discussions, individual 1:1
meetings with experienced researchers, interactive networking sessions, and
panel sessions with a special emphasis on gaining insights regarding career
paths after the PhD
While we strongly encourage
all students to attend the PhD Symposium in person, in a limited number of
cases we will try to accommodate those who cannot travel due to health, visa,
or other hard constraints.
Prospective
attendees should have written, or be close to completing, a thesis proposal (or
equivalent). It is desirable that students are not so close to completing their
PhD that the event would have little impact on their PhD work. Similarly,
students should not be so early in their PhD program that a concrete topic has
not been chosen yet. We strongly advise students to discuss this criterion with
their advisor(s) or supervisor(s) before submitting.
To
apply for a spot in the PhD Symposium, candidates should submit a paper, which
represents their thesis work and plans. The paper should be up to 4 pages in
length, solely authored by the student—see submission guidelines below.
Candidates will be selected based on the potential of their research for future
impact and their potential to benefit from participating in the Symposium.
Doctoral
students who submit to the Symposium are allowed to have previously published
their research, and they are encouraged to submit full, short, or demo papers
of their work to the CIKM 2023 conference and associated workshops.
Student travel support
Students are highly encouraged to apply for student travel support from CIKM. Priority for the travel support will be given to students who have been selected to attend the PhD Symposium. Application details for student support will be available on the CIKM 2023 website. A student must apply for the support to be considered. Also note that the availability and the number of student travel supports are dependent on sponsorship.
Submission
Submission for the PhD Symposium should be made in the form of a 4-page paper including references as PDF using the ACM camera-ready templates. Submissions are single-blind, and are single-author papers from the doctoral candidate with clearly stating the PhD supervisor(s) (“supervised by …”). The submitted paper should be discussed with the PhD supervisor(s) before submission. Submission should be structured according to the following key points:
In addition, please provide a one-page appendix which covers the following:
The submitted paper should be discussed with the students’ respective PhD supervisor(s) before submission. Papers should be submitted through the CIKM 2023 PhD Symposium online submission system
Topics
We
encourage submissions of high-quality research papers on all topics in the
general areas of artificial intelligence, data science, databases, information
retrieval, and knowledge management.
Students working on
real-world social impact of technology are particularly encouraged to apply.
Topics of interest include, but are not
limited to, the following areas:
●
Data and information acquisition
and preprocessing (e.g., data crawling, IoT data, data quality, data privacy,
mitigating biases, data wrangling)
●
Integration and aggregation (e.g.,
semantic processing, data provenance, data linkage, data fusion, knowledge
graphs, data warehousing, privacy and security, modeling, information
credibility)
●
Efficient data processing (e.g.,
serverless, data-intensive computing, database systems, indexing and compression,
architectures, distributed data systems, dataspaces, customized hardware)
●
Special data processing (e.g.,
multilingual text, sequential, stream, spatio-temporal, (knowledge) graphs,
multimedia, scientific, and social media data)
●
Analytics and machine learning
(e.g., OLAP, data mining, machine learning and AI, scalable analysis
algorithms, algorithmic biases, event detection and tracking, understanding,
interpretability)
●
Neural Information and knowledge
processing (e.g., graph neural networks, domain adaptation, transfer learning,
network architectures, neural ranking, neural recommendation, and neural
prediction)
●
Information access and retrieval
(e.g., ad hoc and web search, facets and entities, question answering and
dialogue systems, retrieval models, query processing, personalization,
recommender systems)
●
Users and interfaces for
information and data systems (e.g., user behavior analysis, user interface
design, perception of biases, personalization, interactive information
retrieval, interactive analysis, conversational interfaces)
●
Evaluation, performance studies,
and benchmarks (e.g., online and offline evaluation, best practices, user
studies)
●
Crowdsourcing (e.g., task
assignment, worker reliability, optimization, trustworthiness, transparency,
best practices)
●
Understanding multi-modal content
(e.g., natural language processing, speech recognition, computer vision,
content understanding, knowledge extraction, knowledge graphs, and knowledge
representations)
●
Data presentation (e.g.,
visualization, summarization, readability, VR, speech input/output)
●
Applications (e.g., urban systems,
biomedical and health informatics, legal informatics, crisis informatics,
computational social science, data-enabled discovery, social media)
●
Fairness, accountability, transparency,
and ethics (e.g., sociotechnical nature of information access systems,
algorithmic fairness, transparency and explainability, misinformation and
disinformation)
All submissions will be reviewed by the PhD Symposium Program Committee composed of experienced researchers, who can provide feedback and suggest future research directions.
All accepted PhD Symposium papers (excluding the appendix) will be included in the main proceedings and made available through the ACM Digital Library. If accepted, it is mandatory to present the results at the PhD Symposium.
Important Dates
Submission deadline: July 7, 2023
Acceptance notification: August 4, 2023
Camera-ready version due: August 18, 2023
Doctoral Consortium: between October 21-25, 2023
PhD Symposium Chairs
● Christine Bauer (Paris Lodron University Salzburg, AT)
● Haiming Liu (University of Southampton, UK)