2023 International Doctoral Forum

Call for Papers

Hong Kong, China
December 2-4, 2023

The International Doctoral Forum 2023 invites you to experience the incredible city Hong Kong while enjoying the high quality forum programs. The objective of the forum is to bring together top Ph.D. students from all over the world, who contribute to all facets of artificial intelligence (AI), big data, system, networking, web mining, including AI for health Care and Education, Machine Learning, Big Data Analytics, Algorithms and Software, Computer Vision and Speech and Languages etc. This year, we are excited to introduce a special track on AI Foundation Models, showcasing the latest developments and adaptations of rising models such as GPT, LLaMA, BERT, DALL-E, and HuBERT for a diverse range of downstream tasks. And to make the forum even more accessible, The Chinese University of Hong Kong will cover all expenses for attendees, including registration, meals, accommodation, and local transportation fees etc. So you can focus on enjoying the forum and making valuable connections with fellow attendees.

IMPORTANT DATES:

Paper submission due: October 22, 23:59 (UTC+8), 2023
Paper acceptance notification: October 26, 2023
Author registration: October 27-31, 2023
Forum: December 2-4, 2023

EVENT HIGHLIGHTS:

Invited talks
Expert-to-student mentoring
Oral presentations
Social events

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.

PAPER SUBMISSION:

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.

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, transparency, 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

Organizers

Hosts

Sponsor

Call for Papers