MLSP 2026 — 28th IEEE International Workshop on Machine Learning for Signal Processing (MLSP)

This page presents a comprehensive ranking of scientific conferences within the field of Engineering and Technology, meticulously compiled by Research.com. As one of the leading platforms for science research across all major disciplines, including Engineering and Technology, Research.com has been providing trusted and authoritative data on scientific contributions since 2014.

The position of each conference in this ranking is determined using a unique bibliometric score developed by the experts at Research.com. This score is calculated through a combination of the estimated h-index and the number of leading scientists who have participated in each conference during the preceding three years, thereby offering a robust and meaningful measure of conference impact and scientific significance.

The ranking incorporates Impact Score values that were gathered on 2024-11-27. The evaluation process was distinguished by an extensive analysis, involving the examination of over 2,262 carefully selected conferences. This selection followed detailed inspection and rigorous review of more than 26,934 scientific documents published over the last three years by 9,385 well-respected and leading scientists specializing in Engineering and Technology.

This sophisticated and multi-faceted approach underscores Research.com’s commitment to providing high-quality, reliable information to the scientific community. For a detailed explanation of how the bibliometric scores and other ranking criteria were determined, please see our Methodology Page.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing at International Workshop on Machine Learning for Signal Processing (based on the number of publications) are:

• Simo Särkkä (5 papers) published 5 papers at the last edition,
• Vince D. Calhoun (3 papers) published 3 papers at the last edition,
• Jing Sui (3 papers) published 3 papers at the last edition,
• Tianzi Jiang (3 papers) published 3 papers at the last edition,
• Kazuyoshi Yoshii (3 papers) published 3 papers at the last edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at International Workshop on Machine Learning for Signal Processing (based on the number of publications) are:

• National Chiao Tung University (5 papers) published 5 papers at the last edition,
• Aalto University (5 papers) published 5 papers at the last edition,
• Chinese Academy of Sciences (3 papers) published 3 papers at the last edition,
• Technical University of Denmark (3 papers) published 3 papers at the last edition,
• University of Cambridge (3 papers) published 3 papers at the last edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2017 edition, 3.26% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 32.58% were posted by at least one author from the top 10 institutions publishing at the conference. Another 22.47% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 24.72% of all publications and 20.22% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.