Workshop on Machine learning, Deep learning and Computational Intelligence for wireless communication (MDCWC2020)
22nd - 24th October 2020
Due to the outbreak of COVID19, the workshop is postponed to 22nd - 24th October 2020 and the submission portals are reopened. The submissions are subjected to Double blind review process and the selected papers will be published as the book series Lecture Notes in Electrical Engineering, Springer publication (Confirmed). https://www.springer.com/series/7818
Indexing: The books of this series are submitted to ISI Proceedings, EI-Compendex, SCOPUS, MetaPress, Web of Science and Springerlink
Extended deadline for Regular Paper Submission
10th September 2020 (Hard deadline) (Closed)
Acceptance notification: Will be sent immediately after the review process
Last date for submission of camera ready paper and registration : 07th October 2020
Note: Author registration needs to be done within 10 days after getting the notification along with the revised paper and copyright form.
About virtual participation: Authors are allowed to present the paper as the recorded audio slides. The slides will be played during the corresponding session, followed by interactions through video conferencing.
Dr. E.S. Gopi, Convener, MDCWC2020
Co-ordinator and Head,
Pattern recognition and the computational intelligence laboratory
Department of Electronics and Communication Engineering
National Institute of Technology Tiruchirappalli
Objective of the workshop
Due to the feasibility of collecting huge data from mobile and wireless networks, there are many possibilities of using Machine learning, Deep-learning and the Computational Intelligence to interpret and to hunt knowledge from the collected data. The workshop aims in consolidating the experimental results integrating the Machine learning, Deep learning and Computational intelligence for wireless communication. The workshopfocus on the following applications.
Mobile data analysis, Mobility analysis, Network control and security, Wireless sensor networks, User localization, Mobile Network and Signal processing. Also those applications are implemented using one or more of the following ML, DL and Computational intelligence algorithms like the following.
Machine learning: Multiple input Multiple output regression, Probabilistic discriminative approach, Multi-class logistic regression, Probabilistic generative model, Support Vector Machine, Dimensionality reduction techniques. Deep learning: Multilayer perceptron, Boltzmann Machine, Auto-Encoders, Convolutional Neural Network, Recurrent Neural Network, Generative Adversarial Network, Deep Reinforcement Learning. Computational Intelligence: Particle Swarm Optimization, Bacterial Foraging, Simulated Annealing, Ant colony technique, Genetic algorithm, Social Emotional Optimization Algorithm (SEOA), Social Evolutionary Learning Algorithm (SELA).
The papers are expected in the following data driven Wireless Communication Applications (Not limited to)
Network prediction, Traffic classification, Call detail record mining.
Mobile health care, Mobile pattern recognition, Natural language processing, Automatic Speech Processing
Mobility analysis, Indoor localization
Wireless Sensor Networks (WSN)
Energy minimization, Routing, Scheduling, Resource allocation, Multiple access, Power control
Malware detection, Cyber security , Flooding attacks detection, Mobile apps sniffing
MIMO detection, Signal detection in MIMO-OFDM, Modulation recognition, Channel estimation, MIMO nonlinear equalization, Super -resolution channel and direction-of-arrival estimation, NOMA, mm-wave channel model,Full duplex,OFDM/FBMC,NB-IOT
Scope of the workshop: The workshop acts as the platform to disseminate the new discovery to reach the world through high quality publications for the research scholars. This also helps to see others contribution, which in further helps in finding new directions in their research.
Who should submit and present?
Beginner research scholars those who are doing research in Machine Learning, Deep learning and Computational intelligence for wireless communication
Post Graduate students who are doing project as the part of the curriculum.
Registration details for the participants
Who should participate?
All UG, PG, research scholars and faculty who are interested in machine learning, deep learning, computational intelligence and their applications in wireless communications can register for this workshop as the participants.
Participants will be allowed to attend all the following sessions of the workshop.
- Guest lectures
- Invited talks
- Paper presentation by the authors
- Machine learning, Deep learning and Computational intelligence Tutorial on 23rd October 2020 .
About the Tutorial
The tutorial consists of series of lectures on Machine learning, Deep learning and Computational intelligence. All UG, PG, research scholars and faculty who are interested in machine learning, deep learning, computational intelligence and their applications will be benefited by this tutorial. The lectures will be based on the book titled "Pattern Recognition and Computational Intelligence Techniques Using Matlab" 2019, Transactions on computational Science and intelligence, Springer publications authored by the Co-ordinator for the event MDCWC 2020. He is also the Guest speaker for the IEEE Training School on Machine Learning for Wireless Communication during 20 to 23rd September 2020.
- Last date for Participation registration: 7th October 2020
- Maximum number of participants=50 FCFS basis Hurry!
- Participation certificate will be provided.
Link to the Brochure for participants
Note: Enquiries regarding invited paper can be mailed to firstname.lastname@example.org with the subject mentioning Invited paper
Dr E S Gopi,
Coordinator and Head of Pattern Recognitin and Computational Intelligence Laboratory,
Dept of Electronics and Communication Engineering,
National Institute of Technology Tiruchirappalli -620015
Phone: (+91) 431 2503314
Mail ID: email@example.com
For further details,
Rajasekharreddy - firstname.lastname@example.org
JayaBrindha - email@example.com
Vinodha - firstname.lastname@example.org
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