重要日期和地点
截稿日期: 2024年8月6日 20点（北京时间）
通知日期: 2024年10月1日 20点（北京时间）
终稿日期: 2024年11月1日 20点（北京时间）
会议日期: 2024年12月4-6日
会议地点: 广东广州·华工大学城中心酒店
提交网址: https://ic2024.hotcrp.com/
大会亮点
（1）论文双盲评审，全英文投稿。会议论文集由Springer Nature（CCIS，EI索引）出版。优秀论文扩展版将推荐到BenchCouncil Transactions on Benchmarks, Standards and Evaluation (TBench)期刊上发表。TBench 2023年CiteScore分值为4.8分，24年8月份实时CiteScore分值为9.5分。
严格依据BenchCouncil科学技术评价学，
（2）通过Top 500计划在全球范围内遴选500个系统、算法、应用项目，并邀请团队代表在现场报告、展示。
（3）颁发BenchCouncil AI成就大奖和BenchCoucil China杰出青年学者奖（限10人）。
（4）和国际测试基准与标准大会(Bench 2024)联合举办（12月4日-6日）。
会议简介
IC 2024遵循已经建立的传统，负有两个重要使命。首先，强调在多学科和跨学科领域中应用最先进的机器学习、深度学习、脉冲神经网络和其他人工智能技术。IC 2024着重于先进人工智能技术实际应用，在理论进展和实际应用之间架起桥梁。
其次，IC 2024利用Top500计划提供先导性的技术路线图。通过探索和推进处理器、系统、算法和应用领域中的机器学习、深度学习、脉冲神经网络和其他人工智能技术的最新进展和最佳实践。该会议促进创新并推动各个领域的进步。这种全面的方法确保IC 2024处于技术进展的前沿，使参与者能够获得有关人工智能领域的最新发展的宝贵见解。
IC 2024欢迎提交原创研究论文，涵盖上述领域。该会议还邀请来自世界各地的贡献者展示他们出色的芯片、系统、算法和应用。这种包容性的方法促进了研究人员和从业人员之间的合作和知识共享，使他们能够交流思想并探索人工智能领域的新可能性。
IC 2024接受的论文将在会议上进行展示，并由Springer Nature出版（CCIS, EI索引）。已发表的IC会议论文有: https://link.springer.com/book/10.1007/978-981-16-1160-5 和https://link.springer.com/book/10.1007/978-981-97-0065-3
会议网址：https://www.benchcouncil.org/ic2024/
长按识别下方二维码访问IC 2024官网
论文征稿
IC会议涵盖了智能计算机、算法及在计算机科学、民航、医疗、金融、教育、管理等领域的广泛主题。主题包括但不限于以下内容。
AI Algorithms
△Machine learning (deep learning, statistical learning, etc)
△Natural language processing
△Computer vision
△Data mining
△Multiagent systems
△Knowledge representation
△Robotics
△Search, planning, and reasoning
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
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 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 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 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 design
△AI for property prediction
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 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 for Science
△Learning from acoustics
△Learning physical dynamics from data
△Speeding up physical simulators, samplers, and solvers
△Molecular modeling and de novo generation
△Modeling biological systems, genomics, protein, RNA
△Accelerating cosmological simulations
△Improving crop yields through precision agriculture
△Optimizing aerospace product design and development
△Benchmarking related or new tasks (i.e. datasets, sota models, etc.)
△Building tools/infrastructures/platforms for scientific discovery
Study of science of science/scientific methods
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 in Finance
△Applications of AI in finance: such as capital markets, investment and financing in the real economy, risk management, investment decision-making, transaction execution, etc.
△Impact of AI on the financial industry: Discuss the influence of AI on 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 the 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 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
△Serverless architecture for AI systems
论文提交
Springer LNCS 格式，full paper限15页（不包括参考文献），short paper限8页（不包括参考文献）。也鼓励提交4页的摘要，接受后进行扩展。
双盲评审（采用HotCRP投稿系统）。论文审稿强调研究的价值，而非论文页数。
论文经录用后，至少一名作者注册会议并进行报告，未注册的论文将无法发表。
请确保论文提交版本符合以下所有条件:
• 所有作者和附属信息必须匿名。
• 论文必须为可打印的 PDF 格式。
• 论文包含页码编号。
• 论文支持黑白打印，确保论文图表使用黑白打印之后的可读性。
• 论文必须描述未在其他刊物上发表，且未在其他会议或期刊评审中的工作。
• 参考文献必须包括所有作者（例如，不要使用et al.）。
LNCS latex template: https://www.benchcouncil.org/file/llncs2e.zip
组织结构
大会主席
Jianfeng Zhan, International Open Benchmark Council
程序委员会共同主席
Weiping Li, Oklahoma State University, USA
Chunjie Luo, Institute of Computing Technology, Chinese Academy of Sciences, China
宣传委员会主席
Shaopeng Dai, Institute of Computing Technology, Chinese Academic of Science, China
宣传委员会副主席
Han Yin, East China University of Political Science and Law, China
Yicheng Liao, Guanghua Law School, Zhejiang University, China
技术程序委员会成员
Bin Wang, Nankai University, China
Biwei Xie, Institute of Computing Technology, Chinese Academic of Science, China
Bibo Tu, Institute of Information Engineering, Chinese Academy of Sciences, China
Bin Wang, Northeastern University, China
Chunhua Xiao, Chongqing University, China
Chunying Li, Guangdong Polytechnic Normal University, China
Cheng Qian, Guangdong Institute of Intelligence Science and Technology, China
Chengwen Zhang, Beijing University of Posts and Telecommunications, China
Congfeng Jiang, Hangzhou Dianzi University, China
Dexin Zhou, CUNY Baruch College, USA
Diego Oliva, University of Guadalajara, Mexico
Duohe Ma, State Key Laboratory of Information Security, Institute of Information Engineering, CAS, China
Di Zhao, Institute of Computing Technology, Chinese Academy of Sciences, China
Dejin Yang, Beijing Jishuitan Hospital, China
Di Hou, Xi'an Jiaotong University, China
Dan Huang, Sun YAT-SEN University, China
Di Zhang, Xi'an Jiaotong-Liverpool University, China
Fanda Fan, Institute of Computing Technology, Chinese Academy of Sciences, China
Fuwei Jiang, Central University of Finance and Economics, China
Guihua Shan, Computer Network Information Center, Chinese Academy of Sciences, China
Guan Gui, Nanjing University of Posts and Telecommunications, China
Guoqiang Zhong, Ocean University of China, China
Haoyu Gao, Renmin University of China, China
Hongjia Li, Chinese academy of sciences, China
Hui Sun, Anhui University, China
Hongliang Liang, Beijing University of Posts and Telecommunications, China
Huaxi Gu, Xidian University, China
Hideyuki Takahashi, Tohoku Gakuin University, Japan
Juan Fang, Beijing University of Technology, China
Jungang Xu, University of Chinese Academy of Sciences, China
Jialiang Tan, Lehigh University, USA
Jing Qiu, Guangzhou University, China
Jiaquan Gao, Nanjing Normal University, China
Jianwu Wang, University of Maryland, Baltimore County, USA
Jian Wu, Anqing Normal University, China
Kai Wu, South China University of Technology, China
Kejiang Ye, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
Kun Yang, National Institute of Metrology of China, China
Kelu Yao, Zhejiang Lab, China
Lei Wang, Institute of Computing Technology, Chinese Academy of Sciences, China
Lanju Kong, Shandong University, China
Lin Cui, Jinan University, China
Liqiu Yang, University of Southern California, USA
Lu Leng, Nanchang Hangkong University, China
Lei Wang, Institute of Physics, Chinese Academy of Sciences, China
Linping Wu, China Academy of Engineering Physics, China
Li Gao, University of Shanghai for Science and Technology, China
Li Xiao, Beijing University of Posts and Telecommunications, China
Luntian Mou, Beijing University of Technology, China
Li Wang, Taiyuan University of Technology, China
Lingjun Fan, Guiyang Big Data Industry Group, China
Luqi Gong, Zhejiang Lab, China
Miao Wang, Academy of Military Sciences, PLA, China
Peng Bao, Beijing Jiaotong University, China
Pengfei Zheng, Huawei, China
Pengfei Chen, Sun YAT-SEN University, China
Pengfei Wang, Computer Network Information Center, Chinese Academy of Sciences, China
Ruixuan Wang, Sun YAT-SEN University, China
Saiqin Long, Jinan University, China
Sadegh Nobari, Chief Information Officer, Startbahn, Japan
Shiyang Yu, Nankai University, China
Shengzhong Feng, Guangdong Institute of Intelligence Science and Technology, China
Shinan Cao, University of International Business and Economics, China
Siqi Shi, Shanghai University, China
Weile Jia, Institute of Computing Technology, Chinese Academy of Sciences, China
Wing Chiu, Department of Mechanical and Aerospace Engineering, Monash University, Australia
Wei Wang, East China Normal University, China
Weihe Gao, Shanghai University of Finance and Economics, China
Weixiang Liu, Shenzhen University, China
Wenyao Zhang, Beijing Institute of Technology, China
Weiqin Tong, Shanghai University, China
Weijun Sun, Guangdong University of Technology, China
Wenzhong Wang, Anhui University, China
Wen Xiong, Yunnan Normal University, China
Wanlin Gao, Institute of Computing Technology, Chinese Academy of Sciences, China
Weiwei Zhan, University of Central Florida, USA
Xiaolan Xie, Guilin University of Technology, China
Xiangdong Wang, Institute of Computing Technology, Chinese Academy of Sciences, China
Xiaoyong Tang, Changsha University of Science & Technology, China
Xiangwen Liao, Fuzhou University, China
Xianjin Fang, Anhui University of Science and Technology, China
Xinchou Lou, University of Texas at Dallas, Dallas & Institute of High Energy Physics (IHEP), China
Xuesong Lu, School of Data Science and Engineering, East China Normal University, China
Xu Chen, Sun YAT-SEN University, China
Yanwu Yang, Huazhong University of Science and Technology, China
Yanni Han, Institute of Information Engineering, Chinese Academy of Sciences, China
Yanwei Liu, Institute of Information Engineering, Chinese Academy of Sciences, China
Yifeng Zhu, Central University of Finance and Economics, China
Yingjie Shi, Beijing Institute of Fashion Technology, China
Yushan Su, Princeton University, USA
Yaoqi Liu, Institute of Computing Technology, Chinese Academy of Sciences, China
Yongkai Fan, Communication University of China, China
Yanwu Xu, South China University of Technology, China
Yanjie Wei, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
Yu Wen, Institute of Information Engineering, Chinese Academy of Sciences, China
Yinliang Yue, Zhongguancun Laboratory, China
Yong Xia, Northwestern Polytechnical University, China
Yongjun Xu, Institute of Computing Technology, Chinese Academy of Sciences, China
Yi Wang, Shenzhen University, China
Ye Li, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
Yue Liu, Shanghai University, China
Yuxin Ding, Harbin Institute of Technology, Shenzhen, China
Yong Tang, South China Normal University, China
Yunyou Huang, Guangxi Normal University, China
Yuhui Deng, Jinan University, China
Yi Jin, Beijing Computing Center, China
Zhihui Lu, Fudan University, China
Zili Zhang, Southwest University, China
Zitao Liu, Jinan University, China
Zhihong Tian, Guangzhou University, China
Zhen Jia, Amazon, USA
Zhujie Ren, Zhejiang Laboratory, China
Zhibin Yu, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
Zheng Yuan, King's College London, United Kingdom
Zhigang Qiu, Renmin University of China, China
