Innovations and Applications of Time Series Processing
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 March 2026 | Viewed by 70
Special Issue Editors
Interests: deep learning; time-series data; self-supervised learning; domain adaptation
Interests: deep learning; transfer learning; domain adaptation; time-series data; predictive maintenance
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Time series data permeates critical domains, including finance, healthcare, climate science, engineering, and cybersecurity. With the exponential growth of sensing technologies and large-scale data infrastructures, extracting actionable insights from temporal data has become both crucial and challenging.
This Special Issue seeks contributions that address key challenges in modeling, forecasting, representation learning, anomaly detection, and pattern discovery in time series data. We particularly encourage work that combines deep learning, probabilistic reasoning, signal processing, or hybrid methods to advance both theoretical understanding and practical performance. Contributions tackling real-world complexities—such as multivariate, irregular, or incomplete time series—are especially welcome.
We invite researchers, practitioners, and industry experts to submit original research, review articles, or case studies that advance the field. This Issue aims to serve as a comprehensive resource connecting foundational research with domain-specific applications and fostering innovation and dialogue within the global time series community.
Dr. Emadeldeen Eldele
Dr. Mohamed Ragab
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- time series analysis
- deep learning for time series
- time series forecasting
- anomaly detection
- representation learning
- signal processing
- multivariate time series
- irregular time series
- interpretable models
- domain applications (finance, healthcare, climate)
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