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Hybrid Event

30th - 1st July 2026 | Geneva, Switzerland

International Conference on Time Series Analysis and Machine Learning (ICTSAML - 26)

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4

Days

4

Hrs

07

Min

02

Sec

Call For Paper

The (ICTSAML) is dedicated to advancing research excellence by bringing together leading scholars, scientists, and professionals from across the globe. It provides a platform for the dissemination of high-quality research and innovative methodologies.

With a strong focus on Machine Learning, the conference promotes research that contributes to academic depth, practical insights, and interdisciplinary knowledge integration.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Time series forecasting with machine learning
02
Anomaly detection in time series data
03
Applications of time series analysis
04
Feature extraction techniques for time series
05
Real-time time series processing methods
06
Seasonal decomposition of time series
07
Machine learning for financial time series
08
Time series data visualization techniques
09
Predictive modeling for time series data
10
Challenges in time series forecasting
11
Time series classification methods
12
Machine learning for sensor time series
13
Temporal data mining techniques
14
Time series analysis in healthcare
15
Machine learning for climate data
16
Data preprocessing for time series analysis
17
Future trends in time series research
18
Machine learning for energy time series
19
Time series data integration methods
20
Collaborative time series analysis

Peer Review Process

All submissions evaluated through structured peer-review to ensure academic rigor. Accepted papers may be considered for high-quality journals.

Registration Details

Secure your participation early. Limited slots are allocated on a first-come, first-served basis.

Publication Opportunities

High-quality submissions prioritized for publication in recognized journals and proceedings.

Submit Your Paper Today Register Early
2026 UPDATE

Consistent Academic Support

Science Net ensures that research activities continue without interruption in the current global situation. Participants can engage through digital and hybrid conference formats.