IC 2023 Calls for Papers
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2023 BenchCouncil International Symposium on Intelligent Computers, Algorithms, and Applications (IC 2023)
In conjunction with Federated Intelligent Computing and Chip Conference (FICC 2023)
Web: https://www.benchcouncil.org/ic2023/

Paper Submission Due (full and short papers): Aug 31, 2023, 11:59 PM AoE
Notification: September 30, 2023, at 11:59 PM AoE
Final Papers Due: October 31, 2023, at 11:59 PM AoE
Conference Date: December 4-6, 2023
Venue: Sanya, Hainan Province, People’s Republic of China.

Please note that citizens from up to 59 nations can visit Sanya, Hainan without a Visa from the Chinese Government. Sanya is a beautiful seaside city, well known as Hawaii in China.

Submission website: https://ic2023.hotcrp.com/
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Introduction
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The mission of IC 2023 is to provide a pioneering technology map through searching and advancing state-of-the-art and state-of-the-practice in processors, systems, algorithms, and applications for machine learning, deep learning, spiking neural network and other AI techniques across multidisciplinary and interdisciplinary areas. The BenchCouncil staff will invite worldwide contributors to showcase their superior chips, systems, algorithms and applications. IC 2023 also solicits manuscripts describing original work in the above areas.

IC 2023 invites manuscripts describing original work in the above areas and topics (Call for Papers). All accepted papers will be presented at the IC 2023 conference and published by Springer CCIS (Indexed by EI).
With generous support from BenchCouncil, IC 2023 will offer travel grants for students to defray a portion of their travel cost. The size and number of these grants will vary depending on funding availability, the number of student applicants, and their respective priority. Grant awards will be made before the early registration deadline; expenses will be reimbursed after the conference; grant recipients will be asked to submit original receipts to verify their expenditures as well as a 1-page summary of their involvement during the conference. While we encourage all in need of a travel grant to apply, the selection process will give higher priority to students who would otherwise not be able to attend the conference. We strongly encourage applications from students that belong to under-represented groups.

Call for papers
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The IC conference encompasses a wide range of topics in intelligent computers, algorithms, and applications in computer science, civil aviation, medicine, finance, education, etc. IC’s multidisciplinary and interdisciplinary emphasis provides an ideal environment for developers and researchers from different areas and communities to discuss practical and theoretical work. The topics of interest include, but are not limited to the following:

-- AI Algorithms
machine learning (deep learning, statistical learning, etc)
natural language processing
computer vision
data mining
multi-agent systems
knowledge representation
robotics
search, planning, and reasoning

-- AI Systems
Scalable and distributed AI systems
High-performance computing for AI
System-level optimization for deep learning
Efficient hardware architectures for AI
Model compression and acceleration techniques
Memory management and resource allocation in AI systems
Real-time and edge AI systems
AutoML and automated system design
Benchmarking and evaluation of AI systems
Observability of AI systems
Edge computing for AI systems
Reliability of AI systems
GPU sharing
Intelligent Operations of AI systems
Graph computing systems
Domain specific AI systems
Server-less architecture for AI systems

-- AI for Ocean Science and Engineering
Ocean Front Detection
Mesoscale Eddy Recognition
Underwater Image Enhancement
Underwater Image Super-Resolution
Underwater Object Recognition, Detection and Tracking
Sea Surface Height Estimation
Sea Surface Temperature Estimation
Internal Wave Identification
Wave Height Estimation

-- AI in Finance
Applications of AI in finance: such as capital markets, investment and financing in real economy, risk management, investment decision-making, transaction execution, etc.
Impact of AI on the financial industry: discuss the influence of AI in the financial industry, such as improving efficiency, reducing risks, and optimizing customer experience.
Challenges and opportunities for AI: Explore the technical, ethical, regulatory, and other challenges faced by AI in the financial field, and how to overcome them.
Sustainable development of intelligent finance: explore how to promote the development of finance industry with extensive AI application while maintaining the principles of sustainable development.
Ethics and transparency: explore the ethical and transparency issues raised by AI in the financial field.

-- AI for Education
Position papers on AI for education
Large language models for education
AI models of teaching and learning
AI-assisted education
Innovative applications of AI technologies in education
Evaluation of AI technologies in education
Intelligent tutoring systems
Human-computer collaborative education systems
Ethics and AI in education
Impacts of AI technologies on education

-- AI for Law
Argument mining on legal texts
Automatic classification and summarization of legal text
Computational methods for negotiation and contract formation
Computer-assisted dispute resolution
Computable representations of legal rules and domain specific languages for the law
Decision support systems in the legal domain
Deep learning on data and text from the legal domain
E-discovery, e-disclosure, e-government, e-democracy and e-justice
Ethical, legal, fairness, accountability, and transparency subjects arising from the use of AI systems in legal practice, access to justice, compliance, and public administration
Explainable AI for legal practice, data, and text analytics
Formal and computational models of legal reasoning (e.g., argumentation, case-based reasoning), including deontic logics)
Formal and computational models of evidential reasoning
Formal models of norms and norm-governed systems
Information extraction from legal databases and texts
Information retrieval, question answering, and literature recommendation in the legal domain
Intelligent support systems for forensics
Interdisciplinary applications of legal informatics methods and systems
Knowledge representation, knowledge engineering, and ontologies in the legal domain
Legal design involving AI techniques
Machine learning and data analytics applied to the legal domain
Normative reasoning by autonomous agents
Open and linked data in the legal domain
Smart contracts and application of blockchain in the legal domain
Visualization techniques for legal information and data

-- AI for Materials Science and Engineering
AI for materials chemistry
AI for materials physics
AI for materials characterization
AI for materials design
AI for materials manufacturing and processing
AI for materials in industry

-- AI for Science
Applications of machine learning in scientific research: Explore the application of machine learning algorithms in scientific data analysis, pattern recognition, classification, and prediction. This includes innovative research in emerging fields such as quantum computing, materials science, climate change, drug discovery, genomics, physics simulation, environmental protection, sustainable energy, and healthcare. For example, using AI techniques to construct complex models and simulate the behavior of natural systems, exploring scientific questions related to climate simulation, cosmological simulation, molecular dynamics simulation, and more.
Assisting experiment design and optimization: Utilize AI to optimize experiment design and parameter optimization, improving experiment efficiency. For example, rapidly determining optimal experimental conditions and reducing the time and cost of experiments.
Natural language processing and scientific literature mining: Explore the application of natural language processing techniques in scientific literature analysis, knowledge graph construction, text summarization, and information extraction, accelerating the dissemination and discovery of scientific knowledge.
Data visualization and scientific communication: Discuss the latest methods and tools for visualizing scientific data and presenting scientific results using AI technology, promoting the communication and sharing of scientific research findings. AI plays a critical role in scientific data analysis. Machine learning and statistical methods can extract useful information and patterns from large-scale scientific datasets, assisting scientists in data mining, feature extraction, data dimensionality reduction, and other tasks.

-- AI for Civil Aviation
AI in Aircraft Maintenance, Repair and Overhaul (MRO)
AI in Operations Management and Revenue Optimization against safety control
AI in Customer Service and Engagement
AI in Aircraft Design Optimization
AI in Identification of Passengers
Pitfalls of using AI in Aviation
The integrity, Metadata integration architecture, effectiveness, consistency, standardization, openness and sharing management of the civil aviation data
Digital Business of civil aviation, quality management of Civil Aviation data
Digital Air-Control Management and Digital Surveillance Management of Civil Aviation

-- AI for Medicine
Medical AI and Interpretable Medical Models
AI, Block Chain, Cloud, and Data Techniques for Medicine
Big Medical data and Privacy Protection
Artificial Intelligence and Medical Image Analysis
Internet-based Medical Diagnosis
Medical Robot
Drug discovery and Computer-aided Design
Artificial Intelligence in Medical Diagnosis
Medical Data and AI Practice and Case Study

-- AI for Space Science and Engineering
Space science target prediction, detection and feature extraction based on AI technology
Uncertain analysis of AI models in space science
Physics-informed machine learning in space science
AI surrogate of the physics models
How to gain new knowledge from the space science AI models
Foundation models in space science
Use AI technology to assist in space mission planning and scheduling
AI-assisted space satellite anomaly detection and emergency decision-making

-- AI for High Energy Physics
Machine learning methods or models for HEP, including event triggering, particle identification, fast simulation, event reconstruction, noise filtering, detector monitoring, and experimental control.
Utilizing high-performance computing for implementing machine learning methods in HEP, such as feature detection, feature engineering, usability, interpretability, robustness, and uncertainty quantification.
Optimizing machine learning models on large-scale HEP simulation or experimental datasets.
Deepening the modeling and simulation of HEP scientific problems using machine learning techniques.
Harnessing emerging hardware (e.g., GPUs, NPUs, FPGAs) to accelerate machine learning processes for HEP data.
Applications of large-scale language models in machine learning for HEP.
Applications of quantum machine learning in machine learning for HEP.

-- AI and Security
Security and Privacy of AI
Fairness, interpretability, and explainability for AI
AI Regulations
Adversarial learning
Membership inference attacks
Data poisoning & backdoor attacks
Security of deep learning systems
Robust statistics
Differential privacy & privacy-preserving data mining
AI for security and privacy
Computer forensics
Spam detection
Phishing detection and prevention
Botnet detection
Intrusion detection and response
Malware identification and analysis
Intelligent vulnerability fuzzing
Automatic security policy management & evaluation
Big data analytics for security


Paper Submissions
Papers must be submitted in PDF. For a full paper, the page limit is 15 pages in the CCIS format, not including references. For a short paper, the page limit is 8 pages in the CCIS format, not including references. Authors are also encouraged to submit a 4-page extended abstract and make an extension after acceptance.

The review process follows a strict double-blind policy. The submissions will be judged based on the merit of the ideas rather than the length. After the conference, the proceeding will be published by Springer CCIS (Indexed by EI). Please note that the CCIS format is the final one for publishing.
At least one author must pre-register for the conference, and at least one author must attend the conference to present the paper. Papers for which no author is pre-registered will be removed from the proceedings.


Formatting Instructions
Please make sure your submission satisfies ALL of the following requirements:
· All authors and affiliation information must be anonymized.
· Paper must be submitted in printable PDF format.
· Please number the pages of your submission.
· The submission must be formatted for black-and-white printers. Please make sure your figures are readable when printed in black and white.
· The submission must describe unpublished work that is not currently under review of any other conference or journal venues.
LNCS latex template: https://www.benchcouncil.org/file/llncs2e.zip


Organization Committee
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General Co-Chairs
Weiping Li, Civil Aviation Flight University of China, China
Tao Tang, BNU-HKBU United International College, China
Frank Werner, Institute of Mathematical Optimization, Otto-von-Guericke-University, German

Program Co-Chairs
Christophe Cruz, Université de Bourgogne, France
Yanchun Zhang, Victoria University, Australia
Wanling Gao, ICT, Chinese Academy of Sciences, China

Program Vice-Chairs
Jungang Xu, University of Chinese Academy of Sciences, China
Yucong Duan, Hainan University, China

Area Chairs
AI Algorithms
Hideyuki Takahashi, Department of Data Science, Faculty of Informatics, Tohoku Gakuin University, Japan
Faraz Hussain, Clarkson University, USA
Chunjie Luo, University of Chinese Academy of Science, China

AI Systems
Pengfei Chen, SUN YAT-SEN UNIVERSITY, China
Jason Jia, Amazon, USA
Xiaoguang Wang, University of Illinois Chicago, USA

AI for Ocean Science and Engineering
Guoqiang Zhong, Ocean University of China, China
Hui Yu, University of Portsmouth, UK

AI in Finance Co-chairs
Changyun Wang, Renmin University of China, China
Michael Guo, Durham University, UK

AI in Finance Program Co-Chairs
Zhigang Qiu, Renmin University of China, China
Shinan Cao, University of International Business and Economics, China

AI for Education
John Impagliazzo, Hofstra University, USA
Xuesong Lu, East China Normal University, China
Stéphane Bressan, National University of Singapore, Singapore

AI for Law
Minghui Xiong, ZJU Law & AI Laboratory, Zhejiang University, China
Bart Verheij, Department of Artificial Intelligence, University of Groningen, the Netherlands

AI for Materials Science and Engineering
Siqi Shi, School of Materials Science and Engineering, Shanghai University, China
Turab Lookma, AiMaterials Research LLC, Santa Fe, USA
Yue Liu，School of Computer Engineering and Science, Shanghai University, China

AI for Sciences
Tao Zhou, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, China
Weile Jia, Institute of Computing Technology, Chinese Academy of Sciences, China

AI for Civil Aviation
Lin Zou, Civil Aviation Flight University of China, China

AI for Medicine
Zhenchang Wang, Beijing Friendship Hospital, Capital Medical University, China
Jie Lu, Xuanwu Hospital, Capital Medical University, China
Jinlyu Sun, Peking Union Medical College Hospital, China

AI for Medicine Vice-Chair
Zhifei Zhang, Capital Medical University, China

AI for Space Science and Engineering
Ziming Zou, National Space Science Center, Chinese Academy of Sciences, China
Liming Song, Institute of High Energy Physics, Chinese Academy of Sciences, China

AI for High Energy Physics Co-Chairs
Yaodong Cheng, Institute of High Energy Physics, Chinese Academy of Sciences, China
Yaquan Fang, Institute of High Energy Physics, Chinese Academy of Sciences, China

AI for High Energy Physics Program Co-Chairs
Xinchou Lou, University of Texas at Dallas, Dallas & Institute of High Energy Physics (IHEP), China

AI and Security
Bo Luo, University of Kansas, US
Yu Wen, Institute of Information Engineering, Chinese Academy of Sciences, China

Publicity Chairs
Fei Teng, Southwest Jiaotong University, China
Jianyuan Sun, University of Surrey, UK
Yaxin Shi, The Agency for Science, Technology and Research (A*STAR), Singapore
Yuchen Zheng, Shihezi University, China
Zheng Yuan, King’s College London, UK
Roy Lee, Singapore University of Technology and Design, Singapore
Ming Gao, East China Normal University, China
Yuan Cheng, Fudan University, China
Jingyuan Chen, Zhejiang University
Juan Li, Central South University, China
Tianwen Xu, Zhejiang University, China
Yicheng Liao, Zhejiang University, China
Xiao Chi, Zhejiang University, China
Zhengwei Yang, School of Computer Engineering and Science, Shanghai University, China
Xiao-Bing Hu, Civil Aviation University of China
Wei Cong, Feeyo Technology Co., Ltd., China
Han Lv, Beijing Friendship Hospital, Capital Medical University, China
Xiaoyan Hu, National Space Science Center, Chinese Academy of Sciences, China
Yanjie Fu, University of Central Florida, USA
Weiwei Tang, National Space Science Center, Chinese Academy of Sciences, China
Pengyang Wang, University of Macau, China
Yingbo Lyu, Shandong University, China
Haijun Yang, Shanghai Jiao Tong University (SJTU), Shanghai, China
Xingtao Huang, Shandong University (SDU), Qingdao, China
Huilin Qu, the European Organization for Nuclear Research (CERN), Geneva


TPC Members
AI Algorithms
Diego Oliva, University of Guadalajara, Guadalajara, Mexico
Yogendra Arya, J.C. Bose University of Science and Technology, India
Nazar Khan, Punjab University, Pakistan
Yingjie Shi, Beijing Institute of Fashion Technology, China
Sansanee Auephanwiriyakul, Chiang Mai University, Thailand
Xiexue Zhou, Max Planck Institute of Biochemistry, Germany
Zihan Jiang, Huawei, China

AI Systems
Xiaoguang Wang, University of Illinois Chicago, USA
Pengfei Zheng, Huawei Ltd., China
Yushan Su, Princetion University, USA
Runan Wang, Imperial College London, UK
Jindal, Anshul, Technical University of Munich, Germany
Hui Dou, Anhui University, China
Saiyu Qi, Xi’an Jiaotong University, China
Wuxia Jin, Xi’an Jiaotong University, China
Chuan Chen, Sun Yat-sen University, China
Shajulin Benedict, Indian Institute of Information Technology, India
Vishvak Murahari, Princeton University, USA

AI for Ocean Science and Engineering
Partha Pratim Roy, Institute of Technology Roorkee, India
Rachid Hedjam, Sultan Qaboos University, Oman
Xin Li, China University of Petroleum (East China), China
Zhimin Wang, Ocean University of China, China
Chi Zhang, Ocean University of China, China

AI in Finance
George Alexandridis，Reading University, UK
Haoyu Gao, Renmin University of China, China
Yi Huang, Fudan University, China
Fuwei Jiang, Central University of Finance and Economics, China
Dimitris Petmezas，Durham University, UK
Georgios, Sermpinis，Glasgow University, UK
Yanmei Sun, University of International Business and Economics, China
Evangelos, Vagenas-Nanos, Glasgow University, UK
Quan Wen, Georgetown University, USA
Ke Wu, Renmin University of China, China
Teng Zhong, University of International Business and Economics, China
Dexin Zhou, CUNY Baruch College, USA
Xiaoneng Zhu, Shanghai University of Finance and Economics, China
Yifeng Zhu, Central University of Finance and Economics, China

AI for Education
Yunshi Lan, East China Normal University, China
Shenggen Ju, Sichuan University, China
Zhenya Huang, University of Science and Technology of China, China
Tiancheng Zhang, Northeastern University, China
Zheng Yuan, King’s College London, UK
Thomas Heinis, Imperial College London, UK
Roy Lee, Singapore University of Technology and Design, Singapore
Sadegh Nobari, Chief Information Officer, Startbahn, Japan
Alison Clear, Eastern Institute of Technology, New Zealand
Tony Clear, Auckland University of Technology, New Zealand
Judith Gal-Ezer, Open University of Israel, Israel
Natalie Kiesler, Scientific Associate, DIPF | Leibniz-Institute, Germany

AI for Law
Michal Araszkiewiz, Jagiellonian University, Poland
Wenjing Du, East China University of Political Science and Law, China
Juan Li, Central South University, China
Reka Markovich, University of Luxemburg, Luxemburg
Matthias Grabmair, Technical University of Munich, Germany
Monica Palmirani, University of Bologna, Italy
Bin Wei, Zhejiang University, China
Heng Zheng, University of Illinois Urbana-Champaign, USA

AI for Materials Science and Engineering
Dezhen Xue, State Key Laboratory for Mechanical Behavior of Materials, Xi’an Jiaotong University, China
Jinjin Li, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, China
Lei Li, Department of Materials Science and Engineering, Southern University of Science and Technology, China
Maxim Avdeev, Australian Nuclear Science and Technology Organization, School of Chemistry, The University of Sydney, Australia
Yanjing Su, Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, China
Zhi Wei Seh, Institute of Materials Research and Engineering, A*STAR, Singapore
Zhijun Fang, School of Computer Science and Technology, Donghua University, China
Zijian Hong, School of Materials Science and Engineering, Zhejiang University, China

AI for Science
Guihua Shan, Computer Network Information Center, Chinese Academy of Sciences, China
Zhiqin Xu, Shanghai Jiao Tong University, China
Chi Zhou, Shenzhen University, China
Lijun Liu, Osaka University, Osaka, Japan
Di Fang, University of California, Berkeley, US
Xiaojie Wu, Bytedance Inc. US
Tong Zhao, Institute of Computing Technology, Chinese Academy of Sciences, China

AI for Civil Aviation
Michael Schultz, Institute of Flight Systems, Bundeswehr University Munich, Germany
Paolo Tortora, Dipartimento di Ingegneria Industriale, Alma Mater Studiorum Università di Bologna, Italy
Carlos E.S. Cesnik, Department of Mechanical Engineering and Materials Science, Duke University, USA
Michael I. Friswell, Faculty of Science and Engineering, Swansea University, UK
Song Fu, School of Aerospace Engineering, Tsinghua University, China
Jae-Hung Han, Department of Aerospace Engineering, KAIST, Korea
Jacques Periaux , Full Research Professor on Numerical Methods in Engineering at CIMNE/UPC, Spain
Domenico Accardo, DII—Department of Industrial Engineering, University of Naples Federico II, Piazzale Vincenzo Tecchio, Italy
Rafic M. Ajaj, Department of Aerospace Engineering, Khalifa University, United Arab Emirate
Gang Chen, State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi'an Jiaotong University, China
Mou Chen, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, China
Wing Chiu, Department of Mechanical and Aerospace Engineering, Monash University, Australia

AI for Medicine
Han Lv, Beijing Friendship Hospital, Capital Medical University, China
Peng Wang, Beijing Ditan Hospital, Capital Medical University, China
Chaodong Wang, Xuanwu Hospital, Capital Medical University, China
Longxin Xiong, Nanchang Ninth Hospital, China
Mingzhu Zhang, Beijing Tongren Hospital, Capital Medical University, China
Yi Li, Peking Union Medical College Hospital, China
Shenhai Wei, The First Hospital of Tsinghua University, China
Hongxu Yang, GE Healthcare, Netherlands
Xiaohong Liu, Shanghai Jiao Tong University, China
Bingbin Yu, German Research Center for Artificial Intelligence-Robotic Innovation Center, Germany
Menghan Hu, East China Normal University, China
Shuo Li, Case Western Reserve University, USA
Tao Tan, Faculty of Applied Sciences, Macao Polytechnic University
Yue Wu, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, China
Siuly Siuly, Victoria University, Australia
Dr Enamul Kabir, University of Southern Queensland, Australia
Muhammad Tariq Sadiq, University of Brighton, UK
Smith K. Khare, Aarhus University, Denmark
Mohammed Diykh, University of Thi-Qar, College of Education for Pure Science, Iraq
Supriya Angra, Torrens University, Australia
Abdulkadir ŞENGÜR, Firat University, Turkey
Varun Bajaj, PDPM-Indian Institute of Technology, Design and Manufacturing, India
Ömer Faruk ALÇİN, Malatya Turgut Ozal University, Turkey
K. Venkatachalam, University of Hradec Králové, Hradec Králové, Czech Republic
Ivan Lee, The University of South Australia, Australia
Feng Xia, RMIT University, Australia
Zhiguo Gong, The University of Macau, China
A/Hong Yang, Guangzhou University, China
Qian Zhou, Nanjing University of Posts and Telecommunications, China
Wenjun Tan, Northeastern University, China

AI for Space Science and Engineering
Zongcheng Ling, Shandong University, China
Yanjie Fu, University of Central Florida, USA
Jiajia Liu, University of Science and Technology of China, China
Xiaoxi He, University of Macau, China

AI for High Energy Physics
Xinchou Lou, University of Texas at Dallas, Dallas & Institute of High Energy Physics (IHEP), Beijing, China
Haijun Yang, Shanghai Jiao Tong University (SJTU), Shanghai, China
Xingtao Huang, Shandong University (SDU), Qingdao, China
Huilin Qu, the European Organization for Nuclear Research (CERN), Geneva
Bruce Mellado, University of the Witwatersrand (WIS), Johannesburg
Fabio Hernandez, Computing Centre, National institute of nuclear and particle physics (IN2P3), Lyon

AI and Security
Yanwei Liu, Institute of Information Engineering, Chinese Academy of Sciences, China
Hongjia Li, Institute of Information Engineering, Chinese Academy of Sciences, China
Zhiqiang Xu, Jiangxi University of Science and Technology, China
Liwei Chen, Institute of Information Engineering, Chinese Academy of Sciences, China
Yanni Han, Institute of Information Engineering, Chinese Academy of Sciences, China
Duohe Ma, Institute of Information Engineering, Chinese Academy of Sciences, China