Keynote Speakers
Keynote Speaker I
Prof. Latif Ladid, University of Luxembourg, Luxembourg
Founder &
President, IPv6 FORUM (www.ipv6forum.org )
Member of 3GPP PCG (Board) (www.3gpp.org)
Founding Chair, 5G World Alliance
(http://www.5gworldalliance.org/ )
Chair, ETSI IPv6 Industry Specification Group :
https://portal.etsi.org/tb.aspx?tbid=827&SubTB=827
IEEE Steering Committee Member: 5G, IoT
Chair, IEEE ComSoC IoT subcommittee
(http://cms.comsoc.org/eprise/main/SiteGen/TC_IOT/Content/Home.html/
)
Chair, IEEE ComSoC 5G subcommittee
(http://cms.comsoc.org/eprise/main/SiteGen/TC_5GMWI/Content/Home.html?refer=18312&Site_Name=TC_5GMWI
Vice Chair, IEEE ComSoC SDN-NFV subcommittee:
http://cms.comsoc.org/eprise/main/SiteGen/TC_SDN_NFV/Content/Home.html
Emeritus Trustee, Internet Society - ISOC (www.isoc.org)
IPv6 Ready & Enabled Logos Program Board
(www.ipv6ready.org)
World summit Award Board Member (www.wsis-award.org )
Research Fellow @ University of Luxembourg on multiple
European Commission Next Generation Technologies IST
Projects
Member of 3GPP2 PCG (www.3gpp2.org)
Member of UN Strategy Council
Member of Future Internet Forum EU Member States
(representing Luxembourg) Luxembourg, June 2017.
Keynote Speaker II
Prof. Dimitrios Georgakopoulos, Swinburne University
of Technology, Australia
Prof. Georgakopoulos is the Director of the Key IoT Lab at the Digital Innovation Platform of Swinburne University of Technology. Before that was Research Director at CSIRO’s ICT Centre and Executive Director of the Information Engineering Laboratory, which was the largest Computer Science program in Australia. Before CSIRO, he held research and management positions in several industrial laboratories in the US, including Telcordia Technologies (where he helped found two of Telcordia’s Research Centers in Austin, Texas, and Poznan, Poland); Microelectronics and Computer Corporation (MCC) in Austin, Texas; GTE (currently Verizon) Laboratories in Boston, Massachusetts; and Bell Communications Research in Piscataway, New Jersey. He was also a full Professor at RMIT University, and he is currently an Adjunct Prof. at the Australian National University and a CSIRO Adjunct Fellow. Prof. Georgakopoulos is an internationally known expert in IoT, process management, and data management. He has received 20+ industry and academic awards. His 170+ journal and conference publications, which include three seminal papers in the areas Service Computing, Workflow Management, Context Management for the Internet of Things (IoT), have received 12,400+ citations. Dimitrios’ research has attracted significant external research funding ($35M+) from various industry and government research funding agencies, ranging from DARPA and ARDA in the USA, to the Framework Program in the EU, to the Department of Human Services and 50+ industry partners in Australia.
Invited Speakers
Invited Speaker I
Assoc. Prof. Danilo Pelusi,
University of Teramo, Italy
Danilo Pelusi received the degree in Physics from
the University of Bologna (Italy) and the Ph.D.
degree in Computational Astrophysics from the
University of Teramo (Italy). Currently, he is an
Associate Professor of Computer Science at the
Department of Communication Sciences, University of
Teramo. Editor of Springer, Elsevier and CRS books,
and Associate Editor of IEEE Transactions on
Emerging Topics in Computational Intelligence
(2017-2020), IEEE Access (2018-present), IEEE
Transactions on Neural Networks and Learning Systems
(2022-present) and IEEE Transactions on Intelligent
Transportation Systems (2022-present), he is Guest
Editor for Elsevier, Springer, MDPI and Hindawi
journals. Keynote speaker, Guest of Honor and Chair
of IEEE conferences, he is inventor of international
patents on Artificial Intelligence. World’s 2% Top
Scientist 2021 and 2022, his research interests
include Fuzzy Logic, Neural Networks, Information
Theory, Machine Learning and Evolutionary
Algorithms.
Invited Speaker II
Dr. Jia Uddin, Woosong University, South Korea
Dr. Jia Uddin is an Assistant Professor
in Artificial Intelligence and Big Data Department, at
Endicott College, Woosong University, South Korea, and
an Associate Professor (On Leave), Computer Science and
Engineering Department at Brac University, Dhaka,
Bangladesh. He received Ph.D. in Computer Engineering
from the University of Ulsan, Korea, in January 2015 and
M.Sc. in Telecommunications from Blekinge Institute of
Technology, Sweden in June 2010. He was an Assistant
Professor in the CSE department at BRAC University and
the CCE department at International Islamic University
Chittagong, Bangladesh. He was invited as a visiting
faculty member at the School of Computing, Staffordshire
University, Stoke-on-Trent, United Kingdom funded by a
European Union Grant in April 2017, was invited as a
Professor at Telkom University, Indonesia in Summer
2021, and University of Foggia, Italy in April 2023.
Dr. Jia received the Best Research Faculty award in the
2016 academic year at BRACU for his outstanding research
contributions in the area of multimedia signal
processing. He is supervising several undergraduate and
graduate thesis students and his research students’
papers won Best paper awards in several international
conferences: ICEEICT-2016, ICCIT-2016, IEEE ICAEE- 2017,
ICERIE-2017, ICMIP2019, IHCI2020, and IVIC2021. Dr. Jia
is the author of 3 books related to Data Science and
Computer Vision published by Woosong publisher and has
50 SCI/Scopus indexed Journal publications. Dr. Jia is
involved with different research communities at home and
abroad by serving as a member of the organizing
committee, technical committee, technical Session Chair,
and reviewers in different peer-reviewed journals: IEEE
Access, Multimedia Tools and Applications (Springer),
Journal of Supercomputing (Springer), Wireless Personal
Communication, SAI Journal, Neural Computing and
Applications (Springer), Journal of Information
Processing Systems, etc. His research interests include
fault diagnosis, computer vision, and multimedia signal
processing.
Speech Title: Industry 4.0 Smart
Factory: Industrial Fault Diagnosis using Deep Learning
Architectures
Abstract: In industry 4.0, artificial
intelligence (AI) based smart devices are widely used in
various applications such as Smart-Governance,
Smart-healthcare, Smart-city, Smart-home, Smart-factory,
etc. Different sensors are using to collect real-time
data from the environment and then the processed data
are used in the AI models. Earlier AI models are mostly
machine learning-based models where feature engineering
plays a vital role in the diagnosis (detection and
prediction). However, the features are environment
dependent and the optimal features change with the
environments. With the advancement of AI, deep learning
models are used nowadays, where deep features are
automatically extracted for diagnosis. The major
concerns of deep learning architectures are
computational complexity and the models are data hungry.
However, limited datasets are available in industrial
environments. To address, the issues, nowadays, to
deploy the deep learning-based diagnosis models in
portable devices different key techniques like transfer
learning (cross domain, domain specific),
self-supervised learning, few shot-learning, etc. are
playing a vital role in the smart diagnosis in
industrial environments.