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Paper Submission

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NOTE:

Authors are advised to follow the Author's Kit to format your paper. However, any published paper with its original format is acceptable. There is also no page number limitations.

Author's Kit

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Please download the following sample papers:

• tex sample paper
• word sample paper
• sample file in pdf format
• All of above in .zip file format paper_format.zip

Submission

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Student authors are invited to submit research papers on original work (including recently published work) describing current research and novel ideas related to this forum themes. Papers whose contributions are supported by experimental evaluations are strongly encouraged.

Copyright of the submitted work is held by the author/owner.

Authors should submit a four-page manuscript in double-column IEEE format including authors' names, affiliations, and a short abstract. Only electronic submission written in English will be accepted. Please download the paper format and sample files from the Author's Kit above.

Submissions can be made by sending email enclosed with manuscript to phdforum@se.cuhk.edu.hk. The title of submission email is expected to conform with the format of "[PaperSubmission][FIRST_AUTHOR_NAME_ABBR]-PAPERTITLE" (for example [PaperSubmission][X.Zhou]-An Ensemble DNNs for Object Tracking). The content of email must explicitly designate (1) the topic-subtopic(multiple choices are allowed if any) of this submission, (2) your personal information (name/school/supervisors/contact et al.) and (3) your submitted manuscript's information: brand-new or published (please provide details). For each accepted paper, we assumed that only one of the authers would attend the forum. The organizing committee provides the representative with free registraion.

Papers are solicited in all areas of AI, system and algorithms, including, but not limited to the following topics:

Special track:

• AI Foundation Models

AI and Social Good:

• AI for health care and education
• Ethics of AI - bias, fairness, privacy, and morality
• Safe and robust AI
• Explainablility, transparancy, and evaluation of AI models
• Green computing

AI and Machine Learning:

• Natural language processing
• Speech processing
• Computer vision
• Human-computer interaction
• Recommendation Systems
• Machine learning algorithms
• Embodied AI

Big Data:

• Big data curation and sharing
• Efficient big data storage and processing
• Big data analytics in special domains
• Structuring and visualization of big data
• Security enhancement for big data
• Data mining
• Knowledge representation and reasoning

System:

• Operating systems
• File and storage systems
• Distributed systems
• Cloud and edge computing system
• System management and virtualization
• Machine learning systems
• Computer architecture
• Programming languages
• Databases

Networking:

• Network architectures and algorithms
• Cyber security
• Mobile networking, multimedia networking, and social networking
• Next generation networks
• Datacenter networking
• Green (energy-efficient) communication and networking

Web Mining:

• Web structural, content, and usage mining
• Web information clustering and classification
• Web page search, crawling, and ranking techniques
• Link analysis
• Web metrics and statistics
• Social computing