Skip to content

IC conference 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.

Notifications You must be signed in to change notification settings

BenchCouncil/IC-2023

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 

Repository files navigation

IC 2023 Calls for Papers

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/

Important Dates

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/

Introduction

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. 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

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

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

About

IC conference 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.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published