2023 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2023)

Top Research Topics at IEEE Symposium Series on Computational Intelligence?

• Artificial intelligence (38.36%)
• Mathematical optimization (15.93%)
• Machine learning (15.45%)

The conference primarily tackles Artificial intelligence, Mathematical optimization, Machine learning, Artificial neural network and Pattern recognition. The Artificial intelligence study featured in IEEE Symposium Series on Computational Intelligence draws parallels with the field of Computer vision. IEEE Symposium Series on Computational Intelligence connects research in Mathematical optimization with the related topic of Benchmark (computing).

The research on Machine learning tackled can also make contributions to studies in the areas of Data modeling and Data mining. The work tackled in the conference goes beyond the discipline of Data mining as it also encompasses Cluster analysis. The research on Evolutionary algorithm discussed in IEEE Symposium Series on Computational Intelligence draws on the closely related field of Evolutionary computation.

What are the most cited papers published at the conference?

• Calibrating Probability with Undersampling for Unbalanced Classification (181 citations)
• Improving Deep Learning with Generic Data Augmentation (158 citations)
• Data clustering and fuzzy neural network for sales forecasting: A case study in printed circuit board industry (98 citations)

Research areas of the most cited articles at IEEE Symposium Series on Computational Intelligence:

The published papers are organized to address concerns in the fields of Artificial intelligence, Machine learning, Artificial neural network, Data mining and Feature extraction. The Artificial intelligence research presented in the conference articles focuses mostly on Pattern recognition and, on occasion, topics in Autoencoder. The study of Artificial neural network in the most cited articles encompasses disciplines such as Cluster analysis, as well as fields such as Segmentation, all of which overlap with one another.

What topics the last edition of the conference is best known for?

• Artificial intelligence
• Statistics
• Machine learning

The previous edition focused in particular on these issues:

IEEE Symposium Series on Computational Intelligence focuses largely on the fields of Artificial intelligence, Machine learning, Artificial neural network, Feature extraction and Mathematical optimization. The overlapping concepts between Data modeling and Time series are the key highlights of Artificial intelligence study. Support vector machine, Decision tree, Classifier (linguistics) and Reinforcement learning are Machine learning topics of special interest in the conference.

The studies on Feature extraction discussed can also contribute to research in the domains of Feature selection and Feature (computer vision). Mathematical optimization study tackled is connected to the field of Benchmark (computing). It covers Task analysis research under the subject of Task (project management).

The most cited articles from the last conference are:

• Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey (15 citations)
• Deep Learning for Screening COVID-19 using Chest X-Ray Images (14 citations)
• Coding and Decoding Speech using a Biologically Inspired Coding System (7 citations)

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 IEEE Symposium Series on Computational Intelligence (based on the number of publications) are:

• Zita Vale (28 papers) absent at the last edition,
• Andries P. Engelbrecht (25 papers) published 4 papers at the last edition, 3 more than at the previous edition,
• Atulya K. Nagar (20 papers) published 3 papers at the last edition,
• Mengjie Zhang (19 papers) published 7 papers at the last edition, 2 more than at the previous edition,
• Thomas Bäck (18 papers) published 6 papers at the last edition, 1 less than at the previous 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 IEEE Symposium Series on Computational Intelligence (based on the number of publications) are:

• Nanyang Technological University (54 papers) published 3 papers at the last edition, 1 less than at the previous edition,
• University of New South Wales (53 papers) published 23 papers at the last edition, 13 more than at the previous edition,
• Chinese Academy of Sciences (36 papers) published 5 papers at the last edition, 8 less than at the previous edition,
• University of Technology, Sydney (34 papers) published 17 papers at the last edition, 16 more than at the previous edition,
• Victoria University of Wellington (28 papers) published 14 papers at the last edition, 8 more than at the previous 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 2020 edition, 4.56% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.10% were posted by at least one author from the top 10 institutions publishing at the conference. Another 6.53% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 7.54% of all publications and 65.83% 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.