ICMLCN'24 Doctoral Forum CFP - Deadline Nov 15
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Carolina Fortuna
Oct 21, 2023, 5:09:12 PM10/21/23
to ml-...@googlegroups.com, José Mairton Barros da Silva Júnior
Dear all,
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We apologize if you receive multiple copies of this CFPs.
We appreciate your help to contribute & forward this CFPs to your friends.
========================================================
IEEE ICMLCN 2024 solicits proposals from students for the first IEEE ComSoc flagship conference dedicated to machine learning and communications networks.
IEEE ICMLCN includes a Doctoral Forum with the aim to provide an environment for junior PhD students to exchange ideas and experiences with peers in an interactive atmosphere and to get valuable feedback from senior researchers on the topics of the conference. The Doctoral Forum is a great occasion to expand on the horizon of current research trends and challenges, and to exchange experience with distinguished engineers and scholars.
The focus of discussions at the Forum will be the work in progress of early-stage PhD students, who will present posters related to their ongoing research towards the dissertation, and participate in several student activities, such as discussions on insights from industry and academia, and sessions from academics on how to be a better scientist.
Eligibility
Ph.D. Students: Applicants must be currently enrolled as full-time Ph.D. students at any accredited university at the time of proposal submission. We encourage Ph.D. students with a research problem and initial technical approach/results to apply, as they are more likely to benefit from the feedback provided during the doctoral forum.
B.Sc. (Bachelor) and M.Sc. (Master) Students: While our primary focus is on Ph.D. students, we also welcome applications from exceptional B.Sc. and M.Sc. students who have developed a research project and achieved significant results. If you fall into this category, we encourage you to apply and contribute your insights to our doctoral forum.
Submission Guidelines
The submitted student proposals should follow the following guidelines:
● Title of the proposed poster with names, affiliations, contact information. The student must be the first and highest contributing author.
● As a guideline, we recommend that the submission is structured to explain 1) what the problem is, 2) why it is important, 3) why existing solutions in the literature are insufficient, 4) how your approach works, and 5) optionally some preliminary results.
● The proposal should not exceed 2 pages double-column, including references, in IEEE conference paper template format.
● The accepted extended abstracts will appear in the conference proceedings.
● Students of each accepted abstract are required to register and present at the conference.
● Proposals must be submitted as PDF via EDAS at https://edas.info/N31625.
Doctoral Forum Details
Review Process: All submissions will undergo a thorough single-blind review process. If your proposal is accepted, the primary student author will have the opportunity to present the accepted paper as a poster. This presentation will be made to both fellow researchers at the conference and a distinguished evaluation committee.
Attendance Policy: Please note that no-shows without prior approval from the conference chairs will not be permitted. Failure to attend and present your accepted submission as a poster will result in the withdrawal of your paper from the proceedings.
Publication: Accepted submissions will be featured in the IEEE Xplore proceedings as 2-page extended abstracts.
Best Poster Award: One exceptional poster will be recognized with the Best Student Poster Award. The winner will be determined based on feedback received from the evaluation committee, highlighting the quality and impact of your presentation.
Student Program Co-Chairs
● José Mairton Barros da Silva Júnior, Uppsala University, mairton...@it.uu.se
● Carolina Fortuna, Jozef Stefan Institute, carolina...@ijs.si
Important Dates
● Submission Deadline: 15 November 2023
● Acceptance Notification: 15 December 2023
● Registration Deadline: 15 January 2024
========================================================
We apologize if you receive multiple copies of this CFPs.
We appreciate your help to contribute & forward this CFPs to your friends.
========================================================
IEEE ICMLCN 2024 solicits proposals from students for the first IEEE ComSoc flagship conference dedicated to machine learning and communications networks.
IEEE ICMLCN includes a Doctoral Forum with the aim to provide an environment for junior PhD students to exchange ideas and experiences with peers in an interactive atmosphere and to get valuable feedback from senior researchers on the topics of the conference. The Doctoral Forum is a great occasion to expand on the horizon of current research trends and challenges, and to exchange experience with distinguished engineers and scholars.
The focus of discussions at the Forum will be the work in progress of early-stage PhD students, who will present posters related to their ongoing research towards the dissertation, and participate in several student activities, such as discussions on insights from industry and academia, and sessions from academics on how to be a better scientist.
Eligibility
Ph.D. Students: Applicants must be currently enrolled as full-time Ph.D. students at any accredited university at the time of proposal submission. We encourage Ph.D. students with a research problem and initial technical approach/results to apply, as they are more likely to benefit from the feedback provided during the doctoral forum.
B.Sc. (Bachelor) and M.Sc. (Master) Students: While our primary focus is on Ph.D. students, we also welcome applications from exceptional B.Sc. and M.Sc. students who have developed a research project and achieved significant results. If you fall into this category, we encourage you to apply and contribute your insights to our doctoral forum.
Submission Guidelines
The submitted student proposals should follow the following guidelines:
● Title of the proposed poster with names, affiliations, contact information. The student must be the first and highest contributing author.
● As a guideline, we recommend that the submission is structured to explain 1) what the problem is, 2) why it is important, 3) why existing solutions in the literature are insufficient, 4) how your approach works, and 5) optionally some preliminary results.
● The proposal should not exceed 2 pages double-column, including references, in IEEE conference paper template format.
● The accepted extended abstracts will appear in the conference proceedings.
● Students of each accepted abstract are required to register and present at the conference.
● Proposals must be submitted as PDF via EDAS at https://edas.info/N31625.
Doctoral Forum Details
Review Process: All submissions will undergo a thorough single-blind review process. If your proposal is accepted, the primary student author will have the opportunity to present the accepted paper as a poster. This presentation will be made to both fellow researchers at the conference and a distinguished evaluation committee.
Attendance Policy: Please note that no-shows without prior approval from the conference chairs will not be permitted. Failure to attend and present your accepted submission as a poster will result in the withdrawal of your paper from the proceedings.
Publication: Accepted submissions will be featured in the IEEE Xplore proceedings as 2-page extended abstracts.
Best Poster Award: One exceptional poster will be recognized with the Best Student Poster Award. The winner will be determined based on feedback received from the evaluation committee, highlighting the quality and impact of your presentation.
Student Program Co-Chairs
● José Mairton Barros da Silva Júnior, Uppsala University, mairton...@it.uu.se
● Carolina Fortuna, Jozef Stefan Institute, carolina...@ijs.si
Important Dates
● Submission Deadline: 15 November 2023
● Acceptance Notification: 15 December 2023
● Registration Deadline: 15 January 2024
● Conference dates: 5 May - 8 May 2024
Contributions are sought, but not limited to, in the following areas:
• ML and Networking for Intelligent Transport Systems
• ML and Networking for Smart Grids
• ML for Signal Processing in Communication and Networking
• ML for the MAC layer
• ML for the Physical Layer
• ML for the Transport layer
• Communication Efficient Distributed ML
• Distributed ML over communication networks
• Federated Learning and communications
• Learn to Transmit and Receive
• Resource Management and Network Optimization
• Semantic Communications and ML
• Wireless Communication to Support ML Services
• Wireless Networking to Support ML Services
• ML and IoT
• ML and Molecular Networks
• ML and Optical Networks
• ML in Intelligent Reflecting Surfaces
• ML and Networking in Smart Cities
• Decentralized Transmission Optimization for Edge Learning
• Distributed Multi-Agent Reinforcement Learning
• Edge Learning in Wireless Networks
• Experiments and Testbeds
• Integrated Distributed Optimization with Edge Learning
• Integrated Sensing and Communication via ML
• Network Architectures and Protocols for Edge Learning
• Over-the-Air Computation for Edge Learning
• Privacy and Security Issues with ML over Networks
• ML and Networking for Intelligent Transport Systems
• ML and Networking for Smart Grids
• ML for Signal Processing in Communication and Networking
• ML for the MAC layer
• ML for the Physical Layer
• ML for the Transport layer
• Communication Efficient Distributed ML
• Distributed ML over communication networks
• Federated Learning and communications
• Learn to Transmit and Receive
• Resource Management and Network Optimization
• Semantic Communications and ML
• Wireless Communication to Support ML Services
• Wireless Networking to Support ML Services
• ML and IoT
• ML and Molecular Networks
• ML and Optical Networks
• ML in Intelligent Reflecting Surfaces
• ML and Networking in Smart Cities
• Decentralized Transmission Optimization for Edge Learning
• Distributed Multi-Agent Reinforcement Learning
• Edge Learning in Wireless Networks
• Experiments and Testbeds
• Integrated Distributed Optimization with Edge Learning
• Integrated Sensing and Communication via ML
• Network Architectures and Protocols for Edge Learning
• Over-the-Air Computation for Edge Learning
• Privacy and Security Issues with ML over Networks
With kind regards,
Carolina and Mairton
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