★2025 4th International Conference on Frontiers of Artificial Intelligence and Machine Learning(FAIML 2025)- Ei Compendex & Scopus—Call for paper
April 25-27, 2025｜Shenyang, China｜Website: https://www.faiml.org/

★Researchers, scientists, engineers and industry professionals will join together this year at FAIML 2025, where the latest research will be unveiled and groundbreaking research projects will be presented. The field of Frontiers of Artificial Intelligence and Machine Learning is entering an era of unprecedented change and innovation. FAIML 2025 presents one of 2025’s premiere opportunities to hear from and network with an international array of experts on the ever evolving state of the field.

★Publication and Indexing
All submitted papers will be sent to 2-3 peer reviewers for reviewing. And accepted and presented papers will be included in FAIML 2025 Digital Conference Proceedings, which will be submitted for indexing by major citation databases such as Ei Compendex, Scopus etc.

★Keynote Speakers
Prof. Qing Li(Fellow of IEEE, AAIA, and IET/IEE)——Hong Kong Polytechnic University, China
Prof. Tie Qiu——Tianjin University, China
Prof. Vladan Devedzic——University of Belgrade, Serbia

★Program Preview/ Program at a glance
April 25: Registration + Icebreaker Reception
April 26: Opening Ceremony+ KN Speech+ Technical Sessions
April 27: Technical Sessions+ Half day tour/Lab tours

★Paper Submission
Submit Via CMT: https://cmt3.research.microsoft.com/FAIML2025

★CONTACT US
Ms. Riva Huang
Email: email@faiml.org
Website: www.faiml.org

★Topics of Interest
Automated reasoning
Automation, Mechatronics and Robotics
Autonomous vehicles
Bioinformatics
Business Intelligence
Business Intelligence in Health Care
Business Process Intelligence
Cognitive robotics
Prudent Financial Management
Real-time reactivity
Robot behavior engineering
Robot learning and adaptation
Robotic surveillance
Robotics and Related Fields
Secure Software Systems
Sensor fusion
Fuzzy Computing with Words
Fuzzy Control
Fuzzy Logic
Fuzzy Optimisation
Genomic data