Conference Information

DSAA 2026: International Conference on Data Science and Advanced Analytics

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Submission Date:
2026-05-30 Extended
Notification Date:
2026-08-10
Conference Date:
2026-10-06
Location:
New Delhi, India
Years:
13
CCF: C   ICORE: B   Viewed: 54225   Tracked: 86   Attend: 29

Conference Partner Index (CP-I)

61.5 / 100
Ranked #537 of 5,655 conferences · Top 10%

#29 of 337 in Data Mining & Databases

Academic recognition (35%)
72
Submission selectivity (20%) No data - scored at the neutral baseline of 50
Editions held (20%)
71
Community attention (10%)
68
Public record completeness (15%)
35

Inputs used: Listed as CCF C, ICORE B · Editions on record: 13 · Researchers following it here: 86 · Researchers who opened this page in the past 24 months: 28

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-09

Call For Papers

DSAA 2026 (International Conference on Data Science and Advanced Analytics) is a CCF C / ICORE B conference held in New Delhi, India on 2026-10-06. The paper submission deadline is 2026-05-30 (extended). Acceptance notifications are sent on 2026-08-10.

The DSAA'2026 Research Track solicits high-quality, original papers presenting novel issues of Data Science and Advanced Analytics across various disciplines and domains, including statistics, informatics, and computing, alongside shallow to deep representation, processing, analytics, learning, inference, optimization, visualization, and presentation. Topics of interests include but are not limited to: Data science foundations and theories Mathematics and statistics for data science and analytics Understanding data characteristics and complexities Machine/deep/statistical learning-based algorithms Advanced analytics and knowledge discovery methods Computer vision and pattern recognition Optimization theories and methods Large-scale databases, big-data processing, distributed processing, and analytics Model, analytics and learning actionability, reproducibility and provenance Theories and methods for evaluation, explanation, visualization, and presentation Ethical, trustworthy and responsible data analytics Submissions for the DSAA'2026 Research Track should very clearly specify the problem being solved, what methodologies were used to solve the problem, what data was used, how the results were evaluated, and how the solution is being used.
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