Organizer
Sponsor
12nd IEEE Special Session on Privacy and Security of Big Data(PSBD
2025)
Aim and Scope
The 12nd IEEE Special Session "Privacy and Security of Big Data" (PSBD 2025) of the 2025 IEEE
International
Conference on Big Data (IEEE BigData 2025) follows the great success of eleven previous editions
co-located with
the IEEE BigData and ACM CIKM conference series and focuses the attention on privacy and security
research
issues in the context of Big Data, a vibrant and challenging research context which is playing a leading
role in
the Database research community. Indeed, while Big Data is gaining the attention from the research
community,
also driven by some relevant technological innovations (like Clouds) as well as novel paradigms (like
social
networks), the issues of privacy and security of Big Data represent a fundamental problem in this
research
context, due to the fact Big Data are typically published online for supporting knowledge management and
fruition processes and, in addition to this, such data are usually handled by multiple owners, with
possible
secure multi-part computation issues. Some of the hot topics in the context privacy and security of Big
Data
include: (i) privacy and security of Big Data integration and exchange; (ii) privacy and security of Big
Data in
data-intensive Cloud computing; (iii) system architectures in support of privacy and security of Big
Data, e.g.,
GPUs: (iv) privacy and security issues of Big Data querying and analysis.
The PSBD 2025 special session focuses on all the research aspects of privacy and security of Big Data.
Among
these, an unrestricted list is the following one:
The 12nd IEEE Special Session "Privacy and Security of Big Data" (PSBD 2025) of the 2025 IEEE
International
Conference on Big Data (IEEE BigData 2025) will be held in Macau, China, during December 8-11, 2025, and
it aims
to
synergistically connect the research community and industry practitioners. It provides an international
forum
where
scientific domain experts and Privacy and Security researchers, practitioners and developers can share
their
findings in theoretical foundations, current methodologies, and practical experiences on Privacy and
Security of
Big
Data. PSBD 2025 will provide a stimulating environment to encourage discussion, fellowship, and exchange
of
ideas in
all aspects of research related to Privacy and Security of Big Data. This includes both original
research
contributions and insights from practical system design, implementation and evaluation, along with new
research
directions and emerging application domains in the target area. An expected outcome from PSBD 2025 is
the
identification of new problems in the main topics, and moves to achieve consolidated solutions to
already-known
problems. Other goals are to help in creating a focused community of scientists who create and drive
interest in
the
area of Privacy and Security of Big Data, and additionally to continue on the success of the event
across future
years.
Special Session Location
Macau, China
Submission Guidelines and Instructions
Contributions are invited from prospective authors with interests in the indicated session topics and
related
areas
of application. All contributions should be high quality, original and not published elsewhere or
submitted for
publication during the review period.
Submitted papers should strictly follow the IEEE official template. Maximum paper length allowed is:
Submitted papers will be thoroughly reviewed by members of the Special Session Program Committee for
quality,
correctness, originality and relevance. All accepted papers must be presented by one of the authors, who
must
register.
Papers must be submitted via the CyberChair System by selecting the track "Special Session on
Privacy and
Security of Big Data".
Paper Publication
Accepted papers will appear in the official IEEE Big Data 2025 main conference proceedings, published by
IEEE.
Important Dates
Paper submission: September 29, 2025
Notification of acceptance: October 31, 2025
Camera-ready paper due: November 14, 2025
Special Session: December 8-11, 2025
Program Committee Chair
Alfredo Cuzzocrea, University of Calabria, Italy
Program Committee
Maurizio Atzori, University of Cagliari, Italy
Roberto Baldoni, University of Rome "Sapienza", Italy
Elisa Bertino, CERIAS and Purdue University, USA
Pietro Colombo, University of Insubria, Italy
Alfredo Cuzzocrea, University of Calabria, Italy
Rinku Dewri, University of Denver, USA
Katerina Doka, NTUA, Greece
Josep Domingo-Ferrer, Universitat Rovira i Virgili, Spain
Yucheng Dong, Sichuan University, China
Murat Kantarcioglu, University of Texas at Dallas, USA
Thorsten Strufe, Technische Universitat Darmstadt, Germany
Vicenc Torra, IIIA-CSIC, Spain
Traian Marius Truta, Northern Kentucky University, USA
Xiaokui Xiao, Nanyang Technological University, Singapore
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11th Special Session on Intelligent Data Mining
After the successes of the first, second, third, fourth, fifth, sixth, seventh, eighth, ninth and tenth
editions
of Special Session on Intelligent Data Mining in Santa Clara, CA (2015); Washington, DC (2016); Boston,
MA
(2017); Seattle, WA, (2018); Los Angeles, CA, (2019); Online Pandemic Session (2020), Online Pandemic
Session
(2021); Osaka, JAPAN (2022); Sorrento, ITALY (2023); Washington DC, USA (2024) and the 11th Special
Session on
Intelligent Data Mining in Macau SAR, CHINA will continue promoting and disseminating the knowledge
concerning
several topics and technologies related to data mining science.
Artificial Intelligence (AI) & Machine Learning (ML) & Deep Learning (DL) fields are interdisciplinary,
including computer science, mathematics, psychology, linguistics, philosophy, neuroscience etc. This
interdisciplinary special session seeks scientific understanding on data and intelligence.
This session may help to create scientific evolution to propose robust and powerful schemes between
human nature
and data processing.
Intelligent Data Mining session open to every researcher as well as industrial partners,
The aims of this Special Session on Intelligent Data Mining are to:
in the fields of theory and applications of data mining, artificial intelligence, computer science,
mathematics,
psychology, linguistics, philosophy, neuroscience and other disciplines to discuss better understanding
of big
data and intelligence.
The papers submitted to this special session might be in a large range of topics that include theory,
application and implementation of artificial intelligence, machine learning and data mining including
but not
limited to the topics given below,
Use of Artificial Intelligence || Machine Learning || Deep Learning in
Papers should be submitted for this special session by Sept 28,
2025
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can
be found
at the conference website. Accepted papers will be published in the conference proceedings. All accepted
papers
must be presented by one of the author/s in the conference to include the article in the proceedings.
If you have any question about this special session, please do not hesitate to direct your question to
the
special session organizer Asst. Prof. Dr. Uraz YAVANOGLU
(urazyavanoglu@gmail.com, uraz@gazi.edu.tr)
Special Session Organizer:
Asst. Prof. Dr. Uraz YAVANOGLU,
Department of Computer Engineering (CS)
Gazi University, Turkey
The important dates for this special session are:
Full Paper Submission Deadline: Sept 28, 2025 11:59 pm PST
Notification of Acceptance: Nov 2, 2025
Camera-ready papers & Pre-registration: Nov 14, 2025, 11:59pm
PST
Conference Dates: Dec 8-11, 2025
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10th IEEE Special Session on Machine Learning on Big Data (MLBD
2025)
Aim and Scope
The 10th IEEE Special Session "Machine Learning on Big Data" (MLBD 2025) of the 2025 IEEE
International
Conference on Big Data (IEEE BigData 2025) follows the great success of nine previous editions
co-located with
the IEEE BigData and IEEE ICMLA conference series and focuses on machine learning models, techniques and
algorithms related to Big Data, a vibrant and challenging research context playing a leading role in the
Machine
Learning and Data Mining research communities. Big data is gaining attention from researchers, being
driven
among others by technological innovations (such as cloud interfaces) and novel paradigms (such as social
networks). Devising and developing machine learning models, techniques and algorithms for big data
represent a
fundamental problem stirred-up by the tremendous range of critical applications incorporating machine
learning
tools in their core platforms. For example, in application settings where big data arise and machine is
useful,
we recognize, among other things: (i) machine-learning-based processing (e.g., acquisition, knowledge
discovery,
and so forth) over large-scale sensor networks introduces important advantages over classical
data-management-based approaches; similarly, (ii) medical and e-heath information systems usually
include
successful machine learning tools for processing and mining very large graphs modelling
patient-to-disease,
patient-to-doctor, and patient-to-therapy networks; (iii) genome data management and mining can gain
important
benefits from machine learning algorithms. Some hot topics in machine learning on big data include: (i)
machine
learning on unconventional big data sources (e.g., large-scale graphs in scientific applications,
strongly-unstructured social networks, and so forth); (ii) machine learning over massive big data in
distributed
settings; (iii) scalable machine learning algorithms; (iv) deep learning models, principles, issues; (v)
machine-learning-based predictive approaches; (vi) machine-learning-based big data analytics; (vii)
privacy-preserving machine learning on big data; (viii) temporal analysis and spatial analysis on big
data; (ix)
heterogeneous machine learning on big data; (x) novel applications of machine learning on big data
(e.g.,
healthcare, cybersecurity, smart cities, and so forth).
The MLBD 2025 special session focuses on all the research aspects of machine learning on Big Data. Among
these,
an unrestricted list includes:
The 10th IEEE Special Session "Machine Learning on Big Data" (MLBD 2025) of the 2025 IEEE
International
Conference on Big Data (IEEE BigData 2025) will be held in Macau, China, during December 8-11, 2025, and
it aims
to synergistically connect the research community and industry practitioners. It provides an
international forum
where scientific domain experts and Machine Learning and Data Mining researchers, practitioners and
developers
can share their findings in theoretical foundations, current methodologies, and practical experiences on
Machine
Learning on Big Data. MLBD 2025 will provide a stimulating environment to encourage discussion,
fellowship, and
exchange of ideas in all aspects of research related to Machine Learning on Big Data. This includes both
original research contributions and insights from practical system design, implementation and
evaluation, along
with new research directions and emerging application domains in the target area. An expected outcome
from MLBD
2025 is the identification of new problems in the main topics, and moves to achieve consolidated
solutions to
already-known problems. Other goals are to help in creating a focused community of scientists who create
and
drive interest in the area of Machine Learning on Big Data, and additionally to continue on the success
of the
event across future years.
Special Session Location
Macau, China
Submission Guidelines and Instructions
Contributions are invited from prospective authors with interests in the indicated session topics and
related
areas of application. All contributions should be high quality, original and not published elsewhere or
submitted for publication during the review period.
Submitted papers should strictly follow the IEEE official template. Maximum paper length allowed is:
Submitted papers will be thoroughly reviewed by members of the Special Session Program Committee for
quality,
correctness, originality and relevance. All accepted papers must be presented by one of the authors, who
must
register.
Papers must be submitted via the CyberChair System by selecting the track "Special Session on
Machine
Learning
on Big Data".
Paper Publication
Accepted papers will appear in the official IEEE Big Data 2025 main conference proceedings, published by
IEEE.
Important Dates
Paper submission: September 29, 2025
Notification of acceptance: October 31, 2025
Camera-ready paper due: November 14, 2025
Special Session: December 8-11, 2025
Program Committee Chair
Alfredo Cuzzocrea, University of Calabria, Italy
Program Committee
Michelangelo Ceci, University of Bari, Italy
Alfredo Cuzzocrea, University of Calabria, Italy
Joao Gama, University of Porto, Portugal
Marwan Hassani, TU Eindhoven, The Netherlands
Mark Last, Ben-Gurion University of the Negev, Israel
Rocco Langone, Deloitte, Belgium
Carson K. Leung, University of Manitoba, Canada
Sofian Maabout, LABRI, Bordeaux University, France
Anirban Mondal, Shiv Nadar University, India
Enzo Mumolo, University of Trieste, Italy
Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece
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8th Special Session on HealthCare Data in IEEE Big Data 2025
Health data differs from other industries' data in terms of structure, context, importance,
volatility,
availability, traceability, liquidity, change speed, usage and sources from which it is collected. As
medicine
is a constantly developing science, healthcare sector also. In this new emerging research area which
stands at
the intersection of several different discipline such as Medicine, Behavioral Science, Supply Chain
Management
or Big Data Analytics, techniques, methods, applications and devices are continuously developed to be
used for
the acquisition, storage, processing, analysis, standardization and optimization of every process in the
health
sector. As the healthcare sector is so challenging and related data are consistently explosive,
healthcare
organizations are focusing to become smarter in order to overcome the industry' s inefficiencies to
improve
quality of care. "To become smarter" requires impeccable data analytics. All stakeholders in
the
sector should
reveal the deep value of this valuable data in order to apply insights to improve quality of care,
clinical
outcomes and deliver personalized healthcare value, while reducing medical costs, collaborate across
care
settings to deliver integrated, personalized care experiences, prevent disease, promote wellness and
manage
care, build flexibility into operations to support cost reduction and excellence in clinical and
business
performance and practices.
The general purpose of this special session in IEEE BigData 2025 conference is to bring together
researchers,
academicians and sector employees from different fields and disciplines and provide them an independent
platform
to exchange information on their researches, ideas and findings about healthcare data and its analytics.
It is
also aimed to encourage debate on how big data can effectively support healthcare in terms of diagnosis,
treatment and population health, and to develop a common understanding for research conducted in this
multidisciplinary field.
Topics of interest include, but are not limited to, the following:
4th Special Session on Dataspaces and DFFT (Data Free Flow with Trust)
Information Page
http://www.koshizuka-lab.org/SSDD-IEEE-BIGDATA2025/
Abstract
In today's digital era, data is the cornerstone of innovation and digital transformation.
With the
advancement of information and communication technologies, we can now generate, store, replicate,
transfer,
process, and analyze data at an unprecedentedly low cost. This paves the way for the democratization of
innovation – enabling people across the globe to participate in and benefit from innovation.
Data is now being harnessed to tackle a wide spectrum of challenges – from global issues such as
climate
change
and pandemics to the everyday problems of individuals and communities. In a truly data–driven
society,
economic growth and the resolution of social issues can go hand in hand. By connecting people and
things,
sharing diverse knowledge, and creating new value, we can foster sustainable and inclusive development.
Globally, this contributes to harmonious economic progress; domestically, it helps address critical
social
challenges including aging populations, regional depopulation, economic inequality, and disaster
resilience.
To realize this vision, vast volumes of Big Data–spanning both cyberspace and physical space must
be
linked
across regions and sectors. This is the foundation of emerging concepts like
"Dataspaces" and
"Data Free Flow with Trust (DFFT)", where data can be shared and utilized securely and
responsibly across borders. In this context, trust and interoperability are essential. Trust
ensures that
stakeholders feel confident in sharing and using data, while interoperability enables seamless
integration
across diverse systems, platforms, and sectors&ndashensuring that data retains its utility and value
throughout
the
ecosystem.
Importantly, Dataspaces are not limited to data sharing alone–they also provide the
infrastructure
for sharing AI models, services, and capabilities, allowing for distributed, collaborative, and
responsible use of artificial intelligence. As AI systems increasingly rely on rich and diverse data,
and as
data ecosystems increasingly depend on intelligent processing, the co–evolution and integration
of
Dataspaces and AI becomes a critical topic for both research and practice.
This Special Session at IEEE BigData 2025 aims to bring together researchers, practitioners, and
professionals from various fields and disciplines to share their experiences, research outcomes, and
insights
related to dataspaces and platforms enabling DFFT. We particularly welcome contributions exploring how
Dataspaces support not only data sharing but also AI sharing, coordination, and governance, as
well as
discussions on how global platforms can facilitate trustworthy and interoperable data and AI
ecosystems–from
infrastructure and technology to governance, business models, and societal impact.
We invite contributions that advance a common understanding of this multidisciplinary domain and help
shape the
future of data and AI ecosystems worldwide.
Topics of interest include, but are not limited to, the following:
Important Dates
Paper submission: September 29, 2025
Notification of acceptance: October 31, 2025
Camera-ready paper due: November 14, 2025
Special Session: December 8-11, 2025
Program Organizers
Noboru Koshizuka, The University of Tokyo, Japan (Chair)
Lars Nagal, International Data Spaces Association, Germany
(Co-Chair)
Yukio Ohsawa, The University of Tokyo, Japan (Co-Chair)
Masaru Dobashi, NTT Data Inc., Japan
Stephan Haller, Bern University of Applied Sciences, Switzerland
Shinji Shimojo, Aomori University, Japan
Hideaki Takeda, National Institute of Informatics, Japan
Hirotsugu Seike, The University of Tokyo, Japan
Paper Submission
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can
be found
at the conference website. Accepted papers will be published in the conference proceedings. All accepted
papers
must be presented by one of the author/s in the conference to include the article in the proceedings.
Papers must be submitted via the CyberChair System by selecting the track "Special Session on Dataspaces
and
DFFT (Data Free Flow with Trust)".
If you have any question about this special session, please do not hesitate to direct your question to
the
special session organizer Prof. Dr. Noboru Koshizuka (noboru@koshizuka-lab.org)
Paper Publication
Accepted papers will appear in the official IEEE Big Data 2025 main conference proceedings, published by
IEEE.
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2nd Special Session on Federated Learning on Big Data
Aim and Scope
The "Special Session on Federated Learning on Big Data" aims to bring together researchers,
industry
practitioners, and policymakers to explore cutting-edge advancements and address pressing challenges in
the
application of federated learning to Big Data. Federated learning is revolutionizing the way
organizations
handle machine learning across distributed data sources, enabling collaborative model training without
compromising data privacy. With the proliferation of data from various sources such as healthcare,
finance, IoT,
and multimedia, this session provides an invaluable opportunity to delve into the practical and
theoretical
aspects of federated learning, focusing on its integration with the 5Vs of Big Data: Volume, Velocity,
Variety,
Value, and Veracity.
The session will highlight recent innovations in federated learning algorithms and frameworks designed
to handle
the unique challenges posed by Big Data, such as heterogeneous data distributions and resource
constraints.
Furthermore, it will explore the interplay between federated learning and privacy-preserving mechanisms,
ensuring secure data exchange across institutions and organizations. Special emphasis will be placed on
real-world applications in healthcare, IoT, and finance, where federated learning allows organizations
to
harness the potential of decentralized data while respecting privacy regulations.
We aim to foster cross-disciplinary collaboration and knowledge-sharing that leads to new methods,
architectures, and systems that push the boundaries of federated learning research. This session will
also shed
light on the emerging policy and ethical considerations in the deployment of federated learning models,
providing a comprehensive view of this rapidly evolving field. Ultimately, our goal is to build a
vibrant
community that propels federated learning into a pivotal role in addressing the challenges and
opportunities of
Big Data analytics.
Topics of interest include, but are not limited to, the following:
Special Session Organizers
Prof. Francesco Piccialli, University of Naples Federico II, Italy
Dr. Fabio Giampaolo, University of Naples Federico II, Italy
Prof. David Camacho, Universidad Politecnica de Matrid, Spain
Prof. Antonella Guzzo, University of Calabria, Italy
Important Dates
Full paper submission: Sept 29, 2025
Notification of paper acceptance: Oct 31, 2025
Camera-ready of accepted papers: Nov 14, 2025
Conference: Dec 8-11, 2025
Instructions
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can
be found
at the conference website. Accepted papers will be published in the conference proceedings. All accepted
papers
must be presented by one of the author/s in the conference to include the article in the proceedings.
Accepted papers will be published in conference proceedings. All accepted papers must be presented by
one of the
authors to include the article in the proceedings. If you have any questions about this special session,
please
feel free to contact us: francesco.piccialli@unina.it
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1st Special Session on Cybersecurity and Telecommunication in the Era of
AI
Aim and Scope
Artificial intelligence (AI) is revolutionizing cybersecurity and telecommunications by enabling
advanced
orchestration, automation, and predictive security measures. However, AI also introduces novel
vulnerabilities
and attack vectors that challenge traditional security paradigms. The increasing adoption of AI-driven
automation in network management and cyber defense necessitates new frameworks for ensuring secure,
resilient,
and efficient communication infrastructures.
This special session aims to provide a platform for researchers and practitioners to discuss the dual
role of AI
in enhancing cybersecurity while mitigating emerging threats in telecommunications. Topics of interest
include
AI-powered security orchestration, self-adaptive networks, predictive threat analytics, secure AI-driven
communications, and the regulatory and ethical challenges surrounding AI in cybersecurity and
telecommunications.
Cybersecurity and Telecommunication in the Era of AI session open to every researcher as well as
industrial
partners,
The aims of this Special Session on Cybersecurity and Telecommunication in the Era of AI are to:
We invite original research contributions in (but not limited to) the following areas:
AI-Driven Orchestration & Automation in Cybersecurity and Telecom
AI-Powered Cybersecurity Challenges & Defenses
Next-Generation Telecommunications (5G/6G, IoT, and Beyond)
Securing Next-Generation Telecommunications (5G/6G, IoT, and Beyond)
Regulatory, Ethical, and Compliance Challenges
Papers should be submitted for this special session by Sept 28, 2025
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can
be found
at the conference website. Accepted papers will be published in the conference proceedings. All accepted
papers
must be presented by one of the author/s in the conference to include the article in the proceedings.
If you have any question about this special session, please do not hesitate to direct your question to
the
special session organizer Prof. Dr. Kasim OZTOPRAK
(kasim.oztoprak@gmail.com, kasim.oztoprak@gidatarim.edu.tr)
Special Session Organizer
Prof. Dr. Kasim OZTOPRAK
Department of Computer Engineering (CS)
Konya Food and Agriculture University, Turkey
Important Dates
Full Paper Submission Deadline: Sept 28, 2025 11:59 pm PST
Notification of Acceptance: Nov 2, 2025
Camera-ready papers & Pre-registration: Nov 14, 2025, 11:59pm
PST
Conference Dates: Dec 8-11, 2025
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Special Session Organizers
Zhiwei Guo (zwguo@ctbu.edu.cn), School of Artificial
Intelligence,
Chongqing Technology and Business University,
China
Quyuan Wang (qywang@ctbu.edu.cn), School of Artificial
Intelligence,
Chongqing Technology and Business
University, China
Prof. Jerry Chun-Wei Lin (jerrylin@ieee.org), Silesian University
of
Technology, Poland
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This project is partially supported by the HORIZON Research and Innovation Actions with project title: Design and evaluation of technological support tools to empower stakeholders in digital education and project number is: 101060918
Important Dates
Electronic submission of full papers: Sep 29, 2025
Notification of paper acceptance: Oct 24, 2025
Camera-ready of accepted papers: Nov 14, 2025
Conference: Dec 8-11, 2025
Instructions
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can
be found
on the conference website https://conferences.cis.um.edu.mo/ieeebigdata2025/cfp.html
Accepted papers will be published in the conference proceedings. All accepted papers must be presented
by one of
the authors in the conference to include the article in the proceedings.
If you have any questions about the special session, please do not hesitate to contact us. Paper
submission
page: https://wi-lab.com/cyberchair/2025/bigdata25/index.php
TOP
This project is partially supported by the HORIZON Research and Innovation Actions with project title: Design and evaluation of technological support tools to empower stakeholders in digital education and project number is: 101060918
Important Dates
Electronic submission of full papers: Sep 29, 2025
Notification of paper acceptance: Oct 24, 2025
Camera-ready of accepted papers: Nov 14, 2025
Conference: Dec 8-11, 2025
Instructions
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can
be found
on the conference website https://conferences.cis.um.edu.mo/ieeebigdata2025/cfp.html
Accepted papers will be published in the conference proceedings. All accepted papers must be presented
by one of
the authors in the conference to include the article in the proceedings.
If you have any questions about the special session, please do not hesitate to contact us. Paper
submission
page: https://wi-lab.com/cyberchair/2025/bigdata25/index.php
TOP
SMD II: Synergizing Mobility Data for Human Life Evolution in Real
Spaces
See more (visual)
information
December 8-11, 2025, Macau, China
Scope
The mutual interaction - not limited to the liveliness or activeness - of people fosters the cross-over
evolution which enhances the prosperity of the local society which can grow to make a life space
preferable to
live and work in.
Here, succeeding the session of last year "Synergizing Mobility Data for Creating and Discovering
Valuable
Places"dedicated to the open problem to discover such a place, we run the above session to
challenge the
aim to realize an evolving society. The central focus here is the humans – each individual and the
interaction of individuals gather in the real space. For example, we may learn a lot from words of
others
talking behind you and aside you, even when you are reading answers to your question to a generative AI
agent.
This effect may be influenced by the width of the space, and the howling of the voices in a room, which
are the
features of a life space. As in the last year, we stand on the belief that a valued place is the basis
of the
sustainable prosperity of human society, where a lively society with active markets is created via the
synergetic interaction of individuals, observed as activities involving movements, communication, and
exchange
of values and information.
We would like to have papers and presentations about methods or theories for creating, collecting,
combining, or
utilizing data on the activities of humans and relevant events, so that spaces and communities embracing
the
potential of evolution can be discovered. In comparison with last year, where the target was
"places,"
this year we focus on –human life evolution– and which converts a space into a place and a
place
into a social
environment.
A point we raise is that the information useful for fostering the cross-over and mutation of human lives
and
ideas/styles for human lives, via social interactions in real spaces, can be beyond sheer "mobility
data" which is the digitalization of the log of human movements. We should involve data on the
words,
thoughts, or health of humans, and on social or natural environment such as location, weather, etc.,
which may
work to trigger, change, or sustain the emotions and activities of humans via effects that may have been
invisible or undetected so far. The authors are welcome to show approaches for obtaining or combining
such
useful data and using the data for discovering the signs of evolutions and forecasting or fostering the
evolutions too.
Relevant Areas
We call for presentations relevant to, but not restricted (as far as it is relevant to our interest
above) to
the four scopes below.
[Analysis: Activities and interactions of humans] Analysis of data on mobility, communication,
thoughts,
and all other activities and events relevant to humans; Evaluation of walkability; Explanation of group
activities with running, cycling, talking, eating, etc.; Explanation of infectious disease expansion,
Prediction
of crimes, etc.
[Synthesis: Utility of big data for making places] Place-making strategies with big data;
Participatory
design; Environmental psychology; Smart cities and technologies; Placemaking for creative thinking and
communication; Sustainable design practices; Interventions for improving human-life quality
[Data Science] Fundamental methods and methodologies for data Integration, statistical analysis,
machine
learning, and predictive Modeling; Data visualization for creative systems design; Ethics and privacy;
Chance
(risks and opportunities in an dynamic environment with uncertainty) discovery
[Data Society] Creation and circulation of values from data; Monetization of data on mobility and
other
data to be combined; Product/service development to enhance well-being in places; Partnerships and
collaborations; Regulatory compliance and risk management
Important Dates
Paper submission: September 29, 2025
Notification of acceptance: October 31, 2025
Camera–ready paper due: November 14, 2025
Paper submission
PDF in a 2-column IEEE format. Find instructions on: https://wi-lab.com/cyberchair/2025/bigdata25/scripts/ws_submit.php?subarea=SP
Accepted papers will be published in conference proceedings from IEEE. All accepted papers must be
presented
by one of the authors. If you have any questions, please do not hesitate to contact info@panda.sys.t.u-tokyo.ac.jp
Organizing Committee Members
Ohsawa, Yukio (chair): University of Tokyo, Japan
Kondo, Sae (co-chair: session originator): Mie University,and RCAST in The University of Tokyo,
Japan
Koshizuka, Noboru (co-chair): The Univ. of Tokyo, Japan
Agrawal, Jitendra: Bristol University, UK
Bandini, Stefania: University of Milano-Bicocca, Italy
Bewong, Michael: Charles Sturt University, Australia
Correa da Silva, Flavio:Universidade de Sao Paulo, Brazil
Fruchter, Renate: Stanford University, USA
Jugulum, Rajesh: Northeastern University, USA
Nishinari, Katsuhiro: University of Tokyo, Japan
Sekiguchi, Kaira: University of Tokyo, Japan
Van den Poel, Dirk: Ghent University, Belgium
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Towards an Understanding of Artificial Intelligence: Bridging Theory,
Explainability,
and Practical Applications
Scope
Artificial Intelligence (AI) has evolved rapidly, impacting various fields from healthcare to autonomous
systems. However, as AI models become increasingly complex, understanding their decision-making
processes is
crucial for trust, fairness and applicability in practice. This special session aims to explore
cutting-edge
advancements in Explainable AI (XAI), Federated Learning, Trustworthy AI, Light-Weighted Edge computing,
and
Multimodal Large Language Models (LLMs), with a focus on time-series analysis, sensor fusion, generative
models,
and cyber-physical systems. Topics are as follows, but not limited to:
This project is partially supported by the European Union's HORIZON TMA MSCA Doctoral Networks,
HORIZON-MSCA-2023-DN-01, grant number: 101168344
Important Dates
Electronic submission of full papers: Sep 29, 2025
Notification of paper acceptance: Oct 24, 2025
Camera-ready of accepted papers: Nov 14, 2025
Conference: Dec 8-11, 2025
Organizers
Rafal Cupek, Silesian University of Technology, Poland
Dariusz Mrozek, Silesian University of Technology, Poland
Jerry Chun-Wei Lin, Silesian University of Technology, Poland
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The 11th Special Session on Information Granulation in Data Science and
Scalable Computing
Background
Granular Computing is a general computation approach for a usage of information granules
such as data blocks, clusters, groups, as well as value intervals, sets, hierarchies, etc.,
to build efficient computational models for complex Big Data applications,
characterized by huge amounts of diverse data and associated domain knowledge.
Information Granulation, under different names, has appeared in many fields,
such as granularity in artificial intelligence, divide and conquer methods
for scaling calculations, approximate computing, knowledge representation,
topological data analysis, image processing and many others related
with human and artificial intelligence. The principles of Granular Computing can be
also helpful to design simplified descriptions of complex data systems and to bridge
the gap between the humans and AI. Herein we may follow the phrase
"Information Granules = Fundamental Pieces of Human and Machine Knowledge"
and treat Granular Computing as one of important meta-mathematical methodologies for Big Data Analytics.
Session Scope
The 11th session in this series continues to address the theory and practice of derivations
and computations based on various types of granular models and structures.
It provides researchers from both academia and industry with the means
to present the state-of-the-art results and methodologies
related to Information Granulation and Granular Computing,
with a special emphasis on applications in Data Science and Scalable Computing.
The session also refers – from the particular viewpoint of Information Granulation
– to currently important research tracks such as social network computing,
cloud computing, cyber-security, data mining, process mining, machine learning,
statistics, knowledge management, AI-based systems, soft computing, e-Intelligence,
business intelligence, bioinformatics, health informatics and IoT.
The papers addressing Information Granulation in the emerging field of XAI
and using its principles to construct interpretable AI models are highly welcome as well.
Particularly, we encourage the papers which deliver experimental results
but in the same time, provide theoretical foundations to justify those results.
Highlights
The session is organized as a part of the IEEE Big Data 2025 conference (December 8-12),
which is a well-established and competitive international event targeted
at modern trends in big data processing and analytics. The session is intended
to be a forum for discussing ideas, issues and methods based on and
inspired by Information Granulation and Granular Computing,
in an atmosphere promoting free exchange of viewpoints and perspectives coming
from different application areas.
Papers accepted to the session will be published in the IEEE Big Data 2025 conference
proceedings, together with papers accepted to the main conference track.
Organizers are planning a special issue in a relevant scientific journal,
such as Big Data Research (Elsevier), Granular Computing (Springer),
Review of Socionetwork Strategies (Springer),
or Big Data Mining and Analytics (Tsinghua University Press).
Organizers particularly encourage papers which deliver experimental results
but in the same time, provide theoretical foundations to justify those results.
Organizers
Shusaku Tsumoto, Shimane University (tsumoto@med.shimane-u.ac.jp)
Dominik Slezak, QED Software & University of Warsaw (dominik.slezak@qedsoftware.com)
Tzung-Pei Hong, University of Kaohsiung (tphong@nuk.edu.tw)
Weiping Ding, Nantong University (dwp9988@hotmail.com)
Important Dates
Full paper submission: October 6, 2025
Notification of paper acceptance: October 21, 2025
Camera-ready of accepted papers: November 8, 2025
Conference: December 8-12, 2025
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