World's Best Scientists 2026 revealed!
ACM

17th International Conference on Machine Learning and Computing (ICMLC)

Location: Guangzhou , China

Conference dates: 2/14/2025 - 2/17/2025

Research H-index
5

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 658 29 30 5

Call for Papers

We are pleased to welcome you to 2025 17th International Conference on Machine Learning and Computing, which will be held in Guangzhou, China during February 14-17, 2025. The International Conference on Machine Learning and Computing (ICMLC) is grand annual conference on machine learning algorithms, computational statistics, mathematical optimization, computer engineering, computer science and other related subject since 2009. It will provide opportunities for researchers in this field to share their ideas and reinforce collaboration. As such, the conference has achieved a remarkable number participants while also enable profuse exchanges among academic and industrial researchers over the years.
The focus of the conference is to establish an effective platform for institutions and industries to share ideas and to present the works of scientists, engineers, educators and students from all over the world. ICMLC conference committees are pleased to invite authors with specialized knowledge and novel innovative thinking to meeting in Shenzhen, China.
ICMLC 2025 is co-sponsored by National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, and technical supported by Metropolitan State University of Denver, Southwest Jiaotong University, University of Strathclyde and University of Macau, University of Reading and so on.

Overview

This ranking presents a comprehensive evaluation of scientific conferences in the field of Computer Science. The list has been meticulously prepared by Research.com, a leading authority in the provision of trusted data on scientific contributions across all major fields, with a particular emphasis on Computer Science since 2014. Conferences are ranked according to a proprietary bibliometric score developed by Research.com, which combines the estimated h-index with the number of distinguished scientists who have participated in each conference over the last three years.

Impact Score values for this ranking were collected as of 2024-11-27, ensuring a current and authoritative reflection of conference influence. The ranking process encompassed the rigorous evaluation of more than 2,742 conferences, each selected following detailed inspection and systematic examination of over 148,739 scientific documents published within the past three years by 13,184 leading and highly respected scientists in Computer Science. This multi-layered analysis underscores the depth of research and the high standards employed by our team of experts.

To better understand how the bibliometric scores and overall rankings were calculated, we invite you to review the complete details of our methodology on 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.

The top authors publishing at International Conference Machine Learning and Computing (based on the number of publications) are:

  • Guangzhong Sun (3 papers) published 3 papers at the last edition,
  • Umar Farooq (2 papers) absent at the last edition,
  • K. R. Venugopal (2 papers) absent at the last edition,
  • Muhammad Amar (2 papers) absent at the last edition,
  • Weiwen Zhang (2 papers) published 2 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.

Only papers with recognized affiliations are considered

The top affiliations publishing at International Conference Machine Learning and Computing (based on the number of publications) are:

  • Wuhan University of Technology (6 papers) published 6 papers at the last edition,
  • University of Science and Technology of China (5 papers) published 5 papers at the last edition,
  • Guangdong University of Technology (4 papers) published 4 papers at the last edition,
  • Chongqing University (3 papers) published 3 papers at the last edition,
  • University of Electronic Science and Technology of China (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 2021 edition, 7.69% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 30.95% were posted by at least one author from the top 10 institutions publishing at the conference. Another 9.52% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.05% of all publications and 40.48% 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.

Related Online Degrees & Career Pathways

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Creative professionals may explore game design degrees, linking software development with interactive media and entertainment, while security-conscious students can choose from top cybersecurity programs to protect digital assets and infrastructure.

Overall, integrating these related fields with computer science expands career prospects in today’s dynamic tech landscape.

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