当前位置:首页

【EI检索】2023年人工智能与统计学前沿国际会议(CFAIS 2023)

2023年人工智能与统计学前沿国际会议(CFAIS 2023)


重要信息

会议网址:www.cfais.org

会议时间:20238月18-20

召开地点:中国南京

截稿时间:2023年8月16日

录用通知:投稿后1

收录检索:EI,Scopus

主办单位:南京大学


Committee


Conference Chairs







Sanyang Liu

Xidian University, China


Wanyang Dai

Nanjing University, China


Fary Ghassemlooy

Northumbria University, UK





Patrick Siarry

Université Paris-Est Créteil, France






Conference Co-Chair









Qiwei Zhan

Zhejiang University, China






Program Chairs







Abdul Ghani Albaali

Princess Sumaya University for Technology, Jordan          


Zaixing He

Zhejiang University, China


Can Wan

Zhejiang University, China


Program Committee







Ran Gao

Beijing Institute of Technology, China


Liguo Wang

Harbin Engineering University, China


Dariusz Jacek Jakóbczak

Koszalin University of Technology, 

Poland




Riadh Robbana

Carthage University, Tunisia


Jinwei Liu

University of Central Florida, USA


Michael N. Vrahatis

University of Patras, Greece


Local Chair

Wanyang Dai

Nanjing University, China






会议简介

★2023年人工智能与统计学前沿国际会议(CFAIS 2023)---Ei Compendex&Scopus-Call for papers

|2023年8月18-20日,中国南京|网址: www.cfais.org 

 

★CFAIS 2023将围绕“人工智能与统计学”的研究领域而展开,为研究人员,工程师和学者,以及行业专业人士提供一个平台并介绍他们新的研究成果以及今后开发的活动,为参会人员们交流新的思想和应用经验建立业务或研究关系。本次会议将于8月18-20日在中国南京召开,在会议期间您将有机会聆听到前沿的学术报告,见证该领域的成果与进步。

 

关于出版和索引

会议收录的稿件都将出版会议论文集, 并提交Ei Compendex, Scopus, CPCI, Google Scholar, Cambridge Scientific Abstracts (CSA), Inspec, SCImago Journal & Country Rank (SJR), EBSCO, CrossRef, Thomson Reuters (WoS)等数据库检索。

入选的优秀论文将被推荐发表在 International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems特刊上(影响因子:1.286),并提交Science Citation Index Expanded(SCIE), ISI Alerting Services, CompuMath Citation Index, Current Contents/Engineering, Computing & Technology, ACM Guide to Computing Literature, Mathematical Reviews, Inspec, Zentralblatt MATH and Compen, de, x&, nbsp;等检索机构检索。


Speakers 2023

Keynote Speaker Ⅰ

Prof. Wang Han

Fellow of SCAAST, Senior Member IEEE

Xiamen University Malaysia, China

Biography: Prof Wang Han is a Fellow of the Singapore-China Association for Advancement of Science and Technology (SCAAST), Senior Member IEEE, and Dean of the School of Electrical Engineering & Artificial Intelligence, Xiamen University Malaysia. He served as chair and finace chair for the IEEE Robotics&Automation chapter. He received the bachelor's degree in computer science in 1982 from Northeast Heavy Machinery Institute, Qinhuangdao, China, and the Ph.D. degree in computer vision in 1990 from the University of Leeds, Leeds, U.K. He has been teaching in Nanyang Tech. Univ. Singapore for 30 years. He organized and served as the General Chair for many conferences, such as the 10th Pacific-Rim Symposium on Image and Video Technology on 26th Nov 2022, Future Smart City IEREK on 18th Nov 2022, and as a Co-Chair for the upcoming 10th IEEE International Conferences on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics (CIS-RAM) 2023. He has authored or co-authored more than 300 top-quality international conference and journal papers. His research interests include computer vision, artificial intelligence, and robotics.

Speech Title: Towards Vision Guided Unmanned Bus

Abstract: The talk is about unmanned bus using vision. The modules include:

? The objective  is to develop and implement a high speed, high accuracy stereo vision system and apply it onto an Unmanned Ground Vehicle (UGV).

? Currently UGV mainly uses expensive active sensors such as Lidar and Radar to provide ranging sensing.

? This project aims to deploy obstacle detection, recognition and tracking system, road feature detection, self-localization and mapping system into the all weather, all terrain unmanned autonomous vehicles with the help of stereo camera and graphics processing unit (GPU), so that it can run at speed from 15 km/h to 60 km/h.

Keynote Speaker Ⅱ

 Prof. Albert Bifet

University of Waikato, New Zealand

Biography: Albert Bifet is the Director of the Te Ipu o te Mahara AI Institute at the University of Waikato and Co-chair of the Artificial Intelligence Researchers Association (AIRA). His research focuses on Artificial Intelligence, Big Data Science, and Machine Learning for Data Streams. He is leading the TAIAO Environmental Data Science project and co-leading the open source projects MOA Massive On-line Analysis, StreamDM for Spark Streaming and SAMOA Scalable Advanced Massive Online Analysis. He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He is one of the winners of the best paper award at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023, and he will be the general co-chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2024.

Speech Title: Green AI

Abstract: AI is enhancing problem-solving capabilities in many sectors and augmenting research efficiency. However, as AI continues to grow in prevalence and power, it's crucial that we harness this technology in a manner that aligns with sustainability goals. Our presentation aims to provide a detailed overview of the latest research and future possibilities in Green AI. We will focus in the two main approaches to Green AI, using AI to solve sustainability challenges and using AI more sustainably. For the first approach, we will present the TAIAO research project in New Zealand, that is focused on solving environmental data science problems. The second approach to Green AI involves using AI in a more sustainable way, and we will introduce methods for machine learning for data streams, that are energy efficient.

Keynote Speaker Ⅲ 

 Prof. Weifeng Gao

Xidian University, China

Biography: Weifeng Gao is a Professor at the School of Mathematics and Statistics, Xidian University. He is a National-level young talent. His research direction is optimization, computational intelligence and artificial intelligence algorithm. He is currently the director of Xidan-Jiuzhou Advanced Computing Joint Laboratory. He won the first Prize of Natural Science of Shaanxi Province (twice), Shaanxi Youth Science and Technology Award (independent), Wu Wenjun Artificial Intelligence Natural Science Second Prize (first), Wu Wenjun Artificial Intelligence Excellent Youth Award (independent), etc. He has published more than 50 academic papers in IEEE Transactions and other journals. His papers published as the first author have been cited by SCI for more than 1900 times and Google Scholar for more than 3700 times. Multiple papers were selected as ESI Highly Cited Papers.

更多主旨报告人正在邀请中。。。。 


征稿主题/会议征稿高性能计算的算法和体系结构、流形与嵌入、近似推理、多智能体系统、贝叶斯模与估计、业务流程智能、因果关系、非参数模型、分类、回归、聚类、强化学习、计划、控制、深度学习包括优化、关系学习、密度估算、人工智能与统计软件及其应用、博弈论、征集主题、高斯过程、稀疏性与压缩感知、泛化与体系结构、统计与计算学习理论......

更多征稿主题请访问: http://www.cfais.org/cfp.html

 

参会方式

1.作者参会:一篇会议录用文章允许一名作者参会;

2.主讲嘉宾:申请主题演讲,由会务组审核;

3.口头演讲:申请口头报告,时间为15分钟;

4.海报参会:申请海报参会,根据官网模板准备海报,再录制5分钟视频;

5.听众参会:不投稿仅参会,可参与问答,也可演讲及展示。

 

投稿方式

CMT在线投稿:https://cmt3.research.microsoft.com/CFAIS2023

请作者按照官网模板格式进行排版。排版好的论文全文(word+pdf版)发送至CMT在线系统。

提交摘要:即只参会做报告,不出版文章;

提交全文:即做参会做报告,并且出版文章;

听众:则不需要提交稿件,注册成功的听众可以参加会议的所有分会;

 

投稿要求:

1. 大会官方语言为英语,必须为全英文稿件,且应具有学术或实用价值,未在国内外学术期刊或会议发表过;

2. 保证文章原创性,未在国内外公开刊物或其它学术会议上发表过。

3. 文章篇幅一般在5-12页之间,不少于5页,含公式图表等,超过5页将收取超页费;

4. 作者可通过Turnitin或其他查询系统自费查重,重复率不得超过20%,由文章重复率引起的被拒稿将由作者自行承担责任;

5.文章录用:若您的文章被录用,我们将以邮件形式通知您,您将收到以下文件:录用通知、审稿意见表、中文注册表。


联系我们

会议秘书:黄女士

会议官网:www.cfais.org

会议邮箱: info@cfais.org

微信ID:19136117862

QQ咨询:2011307354

了解更多会议详情扫描下方二维码,关注我们:

         

HKSRA微信公众号         官方微信号



组织单位

主办单位
南京大学

协办单位
香港机器人与自动化协会

支持单位
电子科技大学、浙江大学、北京理工大学
 

联系方式

请点击 注册咨询 完成后 登录 获取联系方式

Copyright © 2012-2024

免责声明:本站信息均为有关第三方学术会议组织研究与交流发布,如涉及版权,如有请联系告之,24小时内删除.