Location

NTUST, Taipei

Paper Submission

Sept 22Oct 20, 2024

Author's Registration

Nov 25, 2024

Conference Dates

Jan 09-10, 2025

About ICADCML-2025ICADCML2025

::Notification of Acceptance has been sent to Accepted Authors::

:: Journal Support from SCOPUS-indexed and SCI journals: Security and Privacy Journal, Wiley, and International Journal of Communication Systems, Wiley(Confirmed)::

The 6th International Conference on Advances in Distributed Computing and Machine Learning (ICADCML)-2025 will be organized by Department of Computer Science and Information Engineering , National Taiwan University of Science and Technology (NTUST), Taiwan, during January 9-10, 2025. ICADCML-2025 continues the legacy of its predecessors as a premier global platform for researchers and practitioners to share groundbreaking research findings, innovative ideas, and practical experiences in the fields of distributed computing and machine learning. In an era where these technologies are shaping the future of various industries and societal interactions, ICADCML-2025 aims to foster collaboration and knowledge exchange that will drive advancements and applications in these domains. Prospective authors are invited to submit manuscripts reporting original unpublished research and recent developments in the topics related to the conference.

About University

ICADCML2025

National Taiwan University of Science and Technology (NTUST, also known as Taiwan Tech) is a technological university located in the heart of Taiwan’s capital Taipei. Renowned for its commitment to academic excellence and cutting-edge research, NTUST has a rich history dating back to its establishment in 1974 as the National Taiwan Institute of Technology. NTUST stands as a beacon of academic excellence and innovation, committed to providing a dynamic learning environment that fosters creativity, critical thinking, and interdisciplinary collaboration. With a focus on research-driven education and industry partnerships, NTUST is dedicated to addressing global challenges and continues to push the boundaries of knowledge and innovation across various disciplines in engineering and science.

Publication

The Proceedings of ICADCML 2025 will be published in Springer "Lecture Notes in Networks and Systems (LNNS)" Book series [Confirmed]. The books of this series are indexed by SCOPUS, INSPEC, WTI Frankfurt eG, zbMATH, SCImago. All books published in the series are submitted for consideration in Web of Science. All Selected and presented papers will be included in the conference proceedings.

Springer And Inderscience

Journal Support

Extended versions of selected papers presented in ICADCML 2025 are invited and recomended by the conference for submission to the following SCI, SCOPUS, DBLP, ACM Digital Library indexed journals [Confirmed]:

Call for Papers

ICADCML-2025 solicits original research papers contributing to the foundations and applications of Distributed Computing and Machine Learning in the following broad areas, but are not limited to:

Cloud and Edge Computing Applications
Scalability in Serverless Architecture
Distributed and Federated Systems
Blockchain and Smart Contracts
Green Computing and Energy-Efficient Systems
Swarm Intelligence in Decentralized Systems
Deep Learning for NLP and Computer Vision
Federated Learning and Transfer Learning
Privacy-Preserving in Machine Learning
Generative AI and Large Language Models
Model Optimization and Explainable AI
Ethical Considerations in AI and ML
Cloud, Edge, and IoT Security
5G and 6G Security
Zero Trust Architecture (ZTA)
Blockchain and Cybersecurity
AI and ML in Cybersecurity
Intrusion Detection and Prevention
Quantum Networking
Quantum Cryptography
Beyond Quantum Key Distribution (QKD)
Performance Evaluation of Quantum Algorithms
Quantum Techniques in Machine Learning
Hybrid Quantum-Classical Systems

Paper Submission

Author Guidelines



Prospective authors are invited to submit manuscript reporting original unpublished research and recent developments in the topics related to the conference. The manuscripts should follow the standard Springer camera-ready format.


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Important Dates


Submission of Full Paper
Sept 22Oct 20, 2024(FIRM deadline)
Notification of Acceptance
Nov 1, 2024 onwards
Author’s Registration Deadline
Nov 25, 2024
Submission of Camera Ready Papers
Nov 30, 2024
Conference Dates
Jan 09-10, 2025

Submit Paper(CMT)

Registration


Once the manuscript submission deadline is over, the scientific committee will initiate the review process and further intimate the final outcome to the authors on time. To ensure publication of a paper in the Proceedings, at least one author has to register online by submitting a normal registration fee within deadline.

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Keynote Speakers

Yu-Chee Tseng

Yu-Chee Tseng

IEEE Fellow and Lifetime Chair Professor,
College of AI, National Yang Ming Chiao Tung University (NYCU), Taiwan.

Yu-Chee Tseng received his Ph.D. in Computer and Information Science from the Ohio State University in January of 1994. He served as Chairman (2005-2009) and as Dean (2011-2017) for College of Computer Science, National Yang Ming Chiao Tung University (NYCU), Taiwan. He is founding Dean of College of AI, NYCU. Currently, he is Director of Pervasive AI Research Labs, NYCU. Dr. Tseng has been awarded as NYCU Chair Professor (2011-present) and Y. Z. Hsu Scientific Chair Professor (2012-2013). He received Outstanding Research Award (National Science Council, 2001, 2003, and 2009), Academic Award (Ministry of Education), Elite I. T. Award (2004), and Distinguished Alumnus Award (Ohio State University, 2005), Y. Z. Hsu Scientific Paper Award (2009), TWAS Prize (2018), and National Chair Professorship (2020-2023). His research interests include mobile computing, wireless communication, and AI. Dr. Tseng is an IEEE Fellow. He served on the editorial boards of IEEE Trans. on Vehicular Technology, IEEE Trans. on Mobile Computing, IEEE Trans. on Parallel and Distributed Systems, and IEEE Internet of Things Journal. His citation h-index is 68.

Title: Exploring Modalities in Machine Learning
Abstract:A multi-modal deep learning model can process and interpret multiple types of data, such as text, images, audio, and video. These models are significantly closer to human cognition capability when perceiving the world. Let A, B, and C be three modalities. They may interact with each other during model training. Recent researches have made success in several types of modality interactions: (1) alignment of modality A and modality B, denoted as A~B, (2) conversion from modality A to modality B, denoted as AB, (3) merging a model of A and a model of B into a larger model C, denoted as AUB=C, (4) inject a new modality C into two existing modalities A and B, denoted as A+BC, (5) transferring the calculus on modality A to modality B, denoted as A(+, -, *, /)B, (6) producing a secondary modality A’ from A, denoted as AA’, and (7) stacking two modalities A and B, denoted as A//B. We will illustrate several examples for the above interaction types. Understanding these may help develop new researches.


Ai-Chun Pang

Ai-Chun Pang

IEEE Fellow, Director, CITI, Academia Sinica,
Professor, National Taiwan University, Taiwan.

Ai-Chun Pang (逄愛君) received B.S., M.S., and Ph.D. degrees in Computer Science and Information Engineering from National Chiao Tung University (now National Yang Ming Chiao Tung University), Taiwan, in 1996, 1998, and 2002, respectively. Dr. Pang is the Director and Distinguished Research Fellow of the Research Center of Information Technology Innovation, Academia Sinica. She is also the Distinguished Professor of the Department of Computer Science and Information Engineering at National Taiwan University. Her research interests include wireless and mobile networking, edge computing, and IoT. She is a Fellow of the IEEE.

Title: Toward 6G-Enabled Mobile Edge Intelligence
Abstract:With the explosive development of AI, edge intelligence has been considered a must in developing future 6G mobile communications systems to provide timely responses to emerging applications on mobile devices. In 6G, the computation-intensive AI tasks will be distributed at the network edge, and the communications paradigm will shift from conventional symbol transmission to semantic information delivery. This lecture will overview key features of 6G mobile networks and elaborate on distributed AI learning driven by edge intelligence. We will present the effects of limited labeled and non-IID data in the edge-intelligence environment. We will also discuss the vulnerability of the edge-intelligence framework and defense methods against privacy leakage and security threats. Finally, we will introduce the GenAI-based semantic encoder to prioritize task-oriented communication, with the concept of understanding before transmitting and delivering the intended meaning of messages, to achieve the goal of pervasive computing for connected intelligence.


Mohammad S. Obaidat

Mohammad S. Obaidat

Life Fellow of IEEE, Fellow of AAIA and Fellow of SCS. Distinguished/Honorary Professor,
King Abdullah II School of Information Technology, (KASIT), The University of Jordan, Amman, Jordan.

Professor Mohammad S. Obaidat is an internationally known academic/researcher/scientist/ scholar. He received his Ph.D. degree in Computer Engineering with a minor in Computer Science from The Ohio State University, Columbus, USA. He has received extensive research funding and published To Date (2023) over One Thousand and Two Hundred (1,200) refereed technical articles-About half of them are journal articles, over 100 books, and 70 Book Chapters. He is Editor-in-Chief of 3 scholarly journals and an editor of many other international journals. He is the founding Editor-in Chief of Wiley Security and Privacy Journal. Moreover, he is the founder or co-founder of 5 International Conferences. Among his previous positions are Advisor to the President of Philadelphia University for Research, Development and Information Technology, President and Chair of Board of Directors of the Society for Molding and Simulation International (SCS), Senior Vice President of SCS, SCS VP for Membership and SCS VP for Conferences, Dean of the College of Engineering at Prince Sultan University, Founding Dean of the College of Computing and Informatics at the University of Sharjah, Chair and tenured Professor at the Department of Computer and Information Science and Director of the MS Graduate Program in Data Analytics at Fordham University, Chair and tenured Professor of the Department of Computer Science and Director of the Graduate Program at Monmouth University, Chair and Professor of Computer Science Department at University of Texas-Permian Basin, Distinguished Professor at Indian Institute of Technology (IIT)-Dhanbad.

Wei-Chao Chen

Wei-Chao Chen

Chief Digital Officer and Senior Vice President,
Inventec Corp.,Taipei, Taiwan.

Wei-Chao Chen is the Chief Digital Officer at Inventec Corporation and the Chairman at Skywatch Innovation. His research interests include graphics hardware, computational photography, augmented reality, and computer vision. Dr. Chen was the Chief AI Advisor at Inventec (2018-2020), an adjunct faculty at the National Taiwan University (2009-2018), a senior research scientist in Nokia Research Center at Palo Alto (2007-2009), and a 3D Graphics Architect in NVIDIA (2002-2006). Dr. Chen received his MS in Electrical Engineering from National Taiwan University (1996) and Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2002).

Wei Bin Lee

Wei Bin Lee

CEO, Information Security Center,
HonHai Research Institute,Taipei, Taiwan.

Wei-Bin Lee is the CEO of the Information Security Center at HonHai Research Institute. He has previously served as the Commissioner of the Department of Information Technology for the Taipei City Government, Chief Digital Officer at Taipei Fubon Bank, and Director of the Innovation and Technology Office at Fubon Financial Holding. Additionally, he has served as Chairman of the Artificial Intelligence Foundation. He has also been a Professor in the Department of Information Engineering and Computer Science at Feng Chia University. Dr. Lee's expertise lies in network security, cryptography, digital watermarking, and information security management. With his extensive experience, he is poised to lead HonHai Research Institute in making significant contributions to both industry and society. Dr. Lee holds a Ph.D. in Computer Science and Information Engineering from National Chung Cheng University, Taiwan.

Committees

Honorary General Chairs

Jia-Yush Yen, President, NTUST, Taiwan.

General Co-Chairs

Ying-Dar Lin, NYCU, Taiwan.
Wei-Chung Teng, NTUST, Taiwan.

Advisory Committee Chairs

Shyi-Ming Chen, Asia University, Taiwan.
Kai-Lung Hua, NTUST, Taiwan.
Huei-Wen Ferng, NTUST, Taiwan.
Yuan-Cheng Lai, NTUST, Taiwan.
Jen-Wei Hsieh, NTUST, Taiwan.
Mahasweta Sarkar, San Diego State University.
Hung-Yu Wei, National Taiwan University, Taiwan.
Krishna Moorthy Sivalingam, IIT Madras, India
Winston Seah,Victoria University of Wellington, New Zealand
Prasan Kumar Sahoo, Chang Gung University, Taiwan
Mohammed Atiquzzaman, University of Oklahoma, USA
Surya Nepal, CSIRO Data61, AUSTRALIA
Ren-Hung Hwang, NYCU, Taiwan
Brij Bhooshan Gupta, Asia University, Taiwan

Convener

Binayak Kar, NTUST, Taiwan.

Finance Chair

Shih-Fan Chou, NTUST, Taiwan.

Organizing Committee Chairs

Tai-Lin Chin, NTUST, Taiwan.
Yi-Leh Wu, NTUST, Taiwan.
Shan-Hsiang Shen, NTUST, Taiwan.
Yi-Yu Liu , NTUST, Taiwan

Publication Chairs

Asis Kumar Tripathy, VIT Vellore
Jyoti Prakash Sahoo , SOA Deemed to be University

TPC Chairs

Fuxiang Chen, University of Leicester,UK
ABM Rezbaul Islam, Sam Houston State University, USA
Ahmed Mohamed Abdelmoniem Sayed, QMUL,UK
Dimitris Chatzopoulos, UC Dublin, Ireland
Manoranjan Mohanty, UTS, Australia
Mukesh Prasad, UTS, Australia
Madhusanka Liyanage, University College Dublin, Ireland
Suvendu Mohapatra, Foxconn, Taiwan
Jerry (Chi-Yuan) Chou, National Tsing Hua University, Taiwan
CIZA THOMAS, Karunya Institute of Technology and Sciences, Tamil Nadu, India
Vishal Krishna Singh, University of Essex, UK
Peter Shaojui Wang, NTUST, Taiwan
Hung-Yu Kao, National Cheng Kung University, Taiwan
Chia-Mu Yu , NYCU, Taiwan
Neel Kanth Kundu , IIT Delhi
Chinmaya Kumar Dehury , University of Tartu, Estonia

Technical Program Committee

Van-Linh Nguyen, National Chung Cheng University, Taiwan
Yi-Ting Huang , NTUST, Taiwan
Arijit Karati , National Sun Yat-sen University, Taiwan
Rafael Kaliski, National Sun Yat-sen University, Taiwan
Asad Ali, National Institute of Cyber Security (NICS), Taiwan
Widhi Yahya, Universitas Brawijaya, Indonesia
Satyajit Padhy, Micron Technology, Taiwan
Shalini Sarma, Applied Materials, Taiwan
Sachidananda Dash, Micron Technology, Taiwan
Alekha Kumar Mishra, NIT Jamshedpur, India
Anshul Verma, IIT-BHU, Banaras, India
Suchismita Chinara, NIT Rourkela, India
Kuldeep Singh, MNIT Jaipur, India
Sarthak Singhal, MNIT Jaipur, India
Subasish Mohapatra, OUTR Bhubaneswar, India
Aman Kumar, NIT Hamirpur, India
Abhijit Bhattacharyya, NIT Hamirpur, India
Anup Kumar, NIT Silcher, India
Ashish Kumar,NIT Raipur, India
Arun Kumar, IIIT Kota, India
Amit Garg, IIIT Kota, India
Sanjay Ku Panda, NIT Warangal, India
Pankaj Kumar Sa, NIT Rourkela, India
Pabitra Mohan Khilar, NIT Rourkela, India
Pradeep Kumar Roy, IIIT Surat, India
U. A. Deshpande, VNIT Nagpur, India
Aakanksha Sharaff, NIT Raipur, India
Priya Ranjan Muduli, IIT (BHU) Varanasi, India
Karthick Seshadri, NIT AP, India
Pranesh Das, NIT Calicut, India
Jyoti Prakash Singh, NIT Patna, India
Chandrasekaran, NIT Surathkal, India
Lalatendu Behera, NIT Jalandhar, India
Sangram Ray, NIT Sikkim, India
Padmalochan Bera, IIT Bhubaneswar, India
Sanjeet Kumar Nayak, IIITDM Kancheepuram, India
Deepak Ranjan Nayak, NIT Jaipur, India
Ayan Mondal, IIT Indore, India
Vijay Bhaskar Semwal, MANIT Bhopal, India
Sujata Pal, IIT Ropar, India
Rajeswari Sridhar, NIT Tiruchirappalli, India
S. Mary Saira Bhanu, NIT Tiruchirappalli, India
Abdul Nazeer K. A., NIT Calicut, India
K. Muralikrishnan, NIT Calicut, India
Pranesh Das, NIT Calicut, India
Prof. K. Chandrasekaran, NITK Surathkal, India
Prof. P. Santhi Thilagam, NITK Surathkal, India
Biswajit R. Bhowmik, NITK Surathkal, India
Sourav Kanti Addya, NITK Surathkal, India
Mohit P. Tahiliani, NITK Surathkal, India
Damodar Reddy Edla, NIT Goa, India
Pravati Swain, NIT Goa, India
Bibhudatta Sahoo, NIT Rourkela, India
Pabitra Mohan Khilar, NIT Rourkela, India
Aakanksha Sharaff, NIT Raipur, India
Preeti Chandrakar, NIT Raipur, India
Satya Prakash Sahu, NIT Raipur, India

Previous Conferences

Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML-2024)
(5th to 6th January 2024)
VIT-AP University,Amaravati,
Andhra Pradesh, India.
ICADCML 2024
Fourth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML-2023)
(15th to 16th January 2023)
National Institute of Technology, Rourkela,
Odisha, India.
ICADCML 2023

Third International Conference on Advances in Distributed Computing and Machine Learning (ICADCML-2022)
(15th to 16th January 2022)
National Institute of Technology, Warangal,
Telangana, India.
ICADCML 2022

Second International Conference on Advances in Distributed Computing and Machine Learning (ICADCML-2021)
(15th to 16th January 2021)
Siksha ‘O’ Anusandhan (Deemed to be University)
Bhubaneswar, Odisha, India.
ICADCML 2021


First International Conference on Advances in Distributed Computing and Machine Learning (ICADCML-2020)
(30th to 31st January 2020)
VIT Vellore, Tamilnadu, India
ICADCML 2020


Contact Us

National Taiwan University of Science and Technology
國立臺灣科技大學,
No. 43號, Section 4, Keelung Rd,
Da’an District, Taipei City, 106,
Taiwan.

Contact:
Binayak Kar
E-Mail: icadcml6@gmail.com

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