ICIC 2022 Workshop


The purpose of workshops at ICIC 2022 is to provide a comprehensive forum on topics that will not be fully explored during the main conference and to encourage in-depth discussions of future technical and application issues in Intelligent Computing Community. The workshop will also provide a platform for researchers of Intelligent Computing Community to set an agenda and lay the foundation for future development in Intelligent Computing Community. The number of accepted papers at each Workshop should be not less than 8 ones.

All the authors for each Workshop must follow the guidelines in CALL FOR PAPERS to prepare your submitted papers.

Proposals for Workshop should be submitted in ELECTRONIC FORMAT by http://www.ic-icc.cn/icg/index.asp at Workshop Session.


orders
Title
Organizers
Nationality
The 3rdInternational Workshop on Recent advances in deep learning methods and techniques for medical image analysis
Yu-Dong Zhang, Chenxi Huang
China
The 2ndInternational Workshop on Advanced Intelligent Modeling Technologies for Smart Cities
Pengjiang Qian, Yuanpeng Zhang
China
The 2ndInternational Workshop on Theoretical Computational Intelligence and Applications in 2022
Wenzheng Bao, Bin Yang
China
The 2ndInternational Workshop on Mathematical Methods for Analyzing Biological Data
Tatsuya Akutsu, Hongmin Cai, Xiaoqing Cheng
Japan, China
The 1stInternational Workshop on Intelligent Simulation Optimization and Scheduling
Yongquan Zhou, Huajuan Huang, Xiuxi Wei
China
The 1stInternational Workshop on Information Security
Yunxia Liu
China
The 1stInternational Workshop on Data Mining and Modeling Methods for Biological Big Data
Xinguo Lu
China
The 1stInternational Workshop on AI in Biomedicine
Kyungsook Han, Byungkyu Park, Wook Lee
Korea
The 1stInternational Workshop on Data Mining and Computing for Biomedicine
De-Shuang Huang, Da-Ming Zhu, Bin Liu, Yi Zhao, Chun-Hou Zheng
China

1. The 3rd International Workshop on Recent advances in deep learning methods and techniques for medical image analysis

Organizers:
Yu-Dong Zhang, UK
University of Leicester
Email:yudongzhang@ieee.org

Chenxi Huang, China
Xiamen University
Email: supermonkeyxi@xmu.edu.cn

Scope and Topics:
With the advancement in biomedical imaging, the amount of data generated is increasing in biomedical engineering. For example, data can be generated by multimodality image techniques, e.g., ranging from Computed Tomography (CT), Magnetic Resonance Imaging (MR), Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), to Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, etc. This poses a great challenge to develop new advanced imaging methods and computational models for efficient data processing, analysis, and modeling in clinical applications and understanding the underlying biological process. In recent years, deep learning is a rapidly advancing field in terms of both methodological development and practical applications. It allows computational models of multiple processing layers to learn and represent data with multiple levels of abstraction. It can implicitly capture intricate structures of large-scale data and is ideally suited to some of the hardware architectures currently available. The focus of this workshop is to carry out the research article, which could be more focused on the latest medical image analysis techniques based on Deep learning. In recent years, researchers have widely used the Deep Learning method and its variants. This Issue intends to bring new DL algorithms with some Innovative Ideas and find out the core problems in medical image analysis. Recommended topics include (but are not limited to) the following:

  • Application of deep learning in biomedical engineering
  • Transfer learning and multi-task learning
  • Joint semantic segmentation, object detection, and scene recognition on biomedical images
  • Improvising on the computation of a deep network; exploiting parallel computation techniques and GPU programming
  • New models or new structures of the convolutional neural network
  • Visualization and explainable deep neural network

2. The 2nd International Workshop on Advanced Intelligent Modeling Technologies for Smart Cities

Organizers:
Pengjiang Qian, China
Jiangnan University
Email:qianpjiang@jiangnan.edu.cn

Yuanpeng Zhang, China
Hong Kong Polytechnic University
Email: y.p.zhang@polyu.edu.hk

Scope and Topics:
Smart cities constitute a new generation of information technology, considering Internet of Things (IoT), cloud computing, big data, and artificial intelligence (AI), which are fully used in all fields of life in the city. Based on comprehensive and thorough perception, wide-band ubiquitous interconnection, and intelligent integration of advanced forms of urban informationization, the deep integration of informationization, industrialisation, and urbanisation can be achieved. This can then alleviate the "big city disease" by improving the quality of urbanisation, realising fine and dynamic management, improving the effectiveness of urban management, and improving the quality of life of citizens. However, in the process of promoting smart cities, there are many challenges and opportunities to be solved urgently. In particular, advanced intelligent technologies, such as transfer learning, deep learning and multi-view learning, have found numerous successful applications in diverse fields, including infrastructure deployment and control, garbage sorting and recycling, traffic congestion prediction and dredging, smart medical and health monitoring, emergency disaster and first aid, smart city communication, and smart power transmission. This workshop consists of invited talks and contributed talks, and welcomes submission of both papers and short abstracts, where all submissions will be subject to peer review. Potential topics include but are not limited to the following:

  • Data management, data storage, data transmission, data integration for smart cities
  • Real-time capability and optimization under smart cities
  • Clouds computing for smart cities
  • Industrial IoT platforms under smart cities
  • Learning methods for user interaction prediction in smart cities
  • Deep model interpretability for smart cities
  • Virtualization for smart cities

3. The 2nd International Workshop on Theoretical Computational Intelligence and Applications in 2022

Organizers:
Wenzheng Bao, China
Xuzhou University of Technology
Email:baowz55555@126.com

Bin Yang, China
Zaozhuang University
Email: batsi@126.com

Scope and Topics:
Since the birth of artificial intelligence, the theory and technology are increasingly mature. The application field is also expanding. According to some laws and mechanisms in the process of natural evolution, and researchers deal with problems though imitation. That is where theoretical computational intelligence comes in. Theoretical computational intelligence is the successor of artificial intelligence. In addition, it turns into one of the most active researches in the field of intelligent information science. Theoretical computational intelligence has been successfully used to solve the critical problems in pattern recognition, data mining, image processing and so on. Nowadays, there is some representative algorithms in the field such as fuzzy systems, neural networks, evolutionary computation, group intelligence and immune system, etc. Recently, theoretical computational intelligence is at rapid development, in the case of both methodological development and practical applications. Computational intelligence plays pivotal roles in finding the stable convergence of the optimal solution or approximate optimal solution through multiple iterative calculation. Especially in practical applications, it has been widely implemented by researchers. Computational intelligence is an essential combination of learning, adaptation and evolution used to intelligent and innovative applications. Similar to other scientific domains, there is no doubt that computational intelligence has a great research space both in theory and in applications. This workshop consists of invited talks and contributed talks, and welcomes submission of both papers and short abstracts, where all submissions will be subject to peer review. The topics of interest include but are not limited to the following:

  • Applications of theoretical Computational Intelligence in bioinformatics
  • Applications of theoretical Computational Intelligence in traffics
  • Applications of theoretical Computational Intelligence in pharmaceutics
  • Applications of theoretical Computational Intelligence in pharmacology
  • Applications of theoretical Computational Intelligence in Computational chemistry
  • Applications of theoretical Computational Intelligence in Microbiomics
  • Applications of theoretical Computational Intelligence in image processing
  • Applications of theoretical Computational Intelligence in natural language processing
  • Applications of theoretical Computational Intelligence in financial Other related topics

4. The 2nd International Workshop on Mathematical Methods for Analyzing Biological Data

Organizers:
Tatsuya Akutsu, Japan
Kyoto University
Email:takutsu@kuicr.kyoto-u.ac.jp

Hongmin Cai, China
South China University of Technology
Email: hmcai@scut.edu.cn

Xiaoqing Cheng, China
Xi'an Jiaotong University
Email: xiaoqing9054@xjtu.edu.cn

Scope and Topics:
Analysis of biological data has become one of major application areas of intelligent computing. For example, various mathematical models, statistical methods, and machine learning methods have been developed and successfully applied for analysis of DNA/RNA/protein sequences and structures, gene expression profiles, and biological pathways. To provide a forum for researchers, engineers, and practitioners to present and discuss their ongoing work on mathematical methods for analyzing biological data, the First International Workshop on Mathematical Methods for Analyzing Biological Data (MMABD-2021) was held successfully as a part of ICIC-2021. Following the success of the first workshop, we will organize the Second International Workshop on Mathematical Methods for Analyzing Biological Data (MMABD-2022). This workshop covers wide ranges of mathematical aspects of Bioinformatics, Computational Biology, and Systems Biology. This workshop consists of invited talks and contributed talks, and welcomes submission of both papers and short abstracts, where all submissions will be subject to peer review. The topics of interest include but are not limited to the following:

  • mathematical models of biological networks
  • inference of biological networks
  • pattern discovery from biological sequence and/or structure data
  • classification of tumor cells using gene expression data
  • analysis of biomedical image data
  • application of cutting-edge machine learning techniques to analysis of biological data

5. The 1st International Workshop on Intelligent Simulation Optimization and Scheduling

Organizers:
Yongquan Zhou, China
Guangxi University for Nationalities
Email:yongquanzhou@126.com

Huajuan Huang, China
Guangxi University for Nationalities
Email: hhj@gxun.edu.cn

Xiuxi Wei, China
Guangxi University for Nationalities
Email: wei@gxun.edu.cn

Scope and Topics:
Intelligent simulation and scheduling has achieved great success in recent years. As a core direction of artificial intelligence, it has played a leading role in the development of science and technology. Its application has spread all branches of artificial intelligence, such as intelligent optimization, intelligent scheduling, intelligent scheduling, simulation optimization, intelligent manufacturing, smart grid and so on. Although some excellent achievements have been put forward in the field of intelligent simulation and scheduling, many relevant theories have not yet reached the practical level, and there are still many problems to be solved. In order to realize more optimized algorithms and propose wider applications, we will organize the first International Workshop on intelligent simulation and scheduling. This workshop covers the theory and application of intelligent optimization and generation scheduling. This workshop consists of invited talks and contributed talks, and welcomes submission of both papers and short abstracts, where all submissions will be subject to peer review. The topics of interest include but are not limited to the following:

  • Intelligent optimization
  • Intelligent scheduling
  • Simulation optimization
  • Intelligent manufacturing
  • Intelligent logistics
  • Intelligent Transportation
  • Intelligent medical treatment
  • Intelligent City

6. The 1st International Workshop on Information Security

Organizer:
Yunxia Liu, China
Zhengzhou Normal University
Email:liuyunxia0110@hust.edu.cn

Scope and Topics:
Information security has become a crucial need for almost all information transaction applications due to the large diversity of the hackers and attacks, Traditional techniques such as cryptography, watermarking, and data hiding are basic notions and play an important role in developing information security algorithms and solutions. In spite of the large development in the information security techniques, there are still several challenges that need to be addressed in terms of time, accuracy and reliability. The special session targets the information security research area with respect to trends, advanced techniques and applications, which attracts researchers and practitioners from academia and industry, and provides a discussion environment in order to share their experiences in information security. Authors are encouraged to submit both theoretical and applied papers on their research in information security. Topics of interest include, but are not limited to:

  • Blockchain security
  • Applied cryptography
  • Data protection
  • Formal methods in security
  • Information dissemination control
  • Information hiding and watermarking
  • Network security
  • Privacy
  • Secure group communications
  • Security in social networks
  • Embedded security

7. The 1st International Workshop on Data Mining and Modeling Methods for Biological Big Data

Organizer:
Xinguo Lu, China
Hunan University
Email:hnluxinguo@126.com

Scope and Topics:
Biological Big Data have been generated with the advance of various researching projects on different molecular levels, including Pan-Cancer analysis project, Pan-cancer analysis of whole genomes (PCAWG) and Human Cell Atlas (HCA). Data mining and modeling methods to exploit the hidden patterns for precision medicine, potential disease mechanism, cancer target and drug discovery have become one of the researching focuses. To provide a forum for researchers, engineers, and practitioners to present anddiscuss their ongoing work on these analysis methods for biological big data, we will organize the First International Workshop on Data Mining and Modeling Methods for Biological Big Data. This workshop covers wide ranges of computational methods about data mining, data analysis, data visualization, modeling methods for Bioinformatics, Computational Biology, and Systems Biology, etc. This workshop consists of invited talks and contributed talks, and welcomes submission of both papers and short abstracts, where all submissions will be subject to peer review. The topics of interest include but are not limited to the following:

  • Application of deep learning in pan-cancer data analysis
  • New models of the graph convolutional neural network
  • Classification and clustering methods for omics data, single cells
  • Pattern discovery and biological networks inference
  • New model for integration methods on multi-omics
  • The model to detect potential associations and discover disease markers
  • Analysis and modelling methods for single cell data

8. The 1st International Workshop on AI in Biomedicine

Organizers:
Kyungsook Han, Korea
Inha University
Email:khan@inha.ac.kr

Byungkyu Park, Korea
Inha University
Email:bpark760914@gmail.com

Wook Lee, Korea
Inha University
Email:wooklee@inha.ac.kr

Scope and Topics:
This workshop consists of invited talks and contributed talks, and welcomes submission of both papers and short abstracts, where all submissions will be subject to peer review. Data in biomedicine is increasing at an exponential rate, and dealing with big data for analysis or prediction is quite challenging. Artificial intelligence (AI) methods have been used for years to solve several problems in bioscience research, often with multidisciplinary collaboration. This workshop encourages anyone who is interested in AI and biomedicine to submit their original work regarding the development of theory, methods, systems, and application of AI approaches. TOPICS: The topics of interest include but are not limited to the following:

  • Bio Big Data Analysis
  • AI methods in Biomedicine
  • Machine Learning
  • Knowledge Discovery and Data Mining in Biomedicine
  • Cancer Genomics and Informatics
  • Precision Medicine with AI
  • Biomedical Ontologies
  • Biomedical Knowledge Acquisition and Knowledge Management

9. The 1st International Workshop on Data Mining and Computing for Biomedicine

Organizers:
De-Shuang Huang, China
Tongji University
Email:dshuang@gxas.cn

Da-Ming Zhu,China
Shandong University
Email:dmzhu@sdu.edu.cn

Bin Liu,China
Beijing Institute of Technology
Email:bliu@bliulab.net

Yi Zhao, China
Institution of computing technology, CAS, China
Email:zhaoyi@ict.ac.cn

Chun-Hou Zheng, China
Anhui University
Email:zhengch99@126.com

Scope and Topics:
The increasing availability of large and complex biomedical data sets to the research community, triggers the need to develop more advanced and sophisticated data mining and computing techniques to exploit and manage these big data. To provide a forum for data miners, data scientists, and clinical researchers to share their latest investigations in applying data mining and computing techniques to biomedical data, we will organize the first international workshop on data mining and computing for biomedicine. This workshop covers the theory and application of data mining and computing techniques to analyze a wide variety of biomedical data sets that can potentially lead to significant advances in the field. The topics of interest include but are not limited to the following:

  • Computational genetics, genomics and proteomics
  • Pharmacogenomics data mining
  • Medical image data mining
  • Application of machine learning and deep learning methods to clinical data
  • Biological and clinical data analysis and integration for translational research
  • Classifying and clustering big data in electronic health records
  • Algorithms to speed up the analysis of big biomedical data
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