Special Sessions


Advances in Multi-Criteria Decision Making (MCDM) for Smart Society 5.0: Challenges and Opportunities

With the emergence of Society 5.0, decision-making is becoming increasing complex day by day, as it involves not only human judgement but also the analysis of large amounts of data being generated by various smart systems. MCDM has the potential to provide a systematic way to integrate multiple criteria, objectives, and stakeholders in decision-making processes in complex and uncertain environments, so it is increasingly relevant in this digital age. This special session is devoted explore the challenges, advances and opportunities of MCDM in the context of Society 5.0, and discuss how MCDM can contribute to the development of smart, sustainable, and human-centric societies.

Key topics to be covered in the session may include the theory and applications of MCDM methods in context to Society 5.0:

  • Decision making in the era of Society 5.0.
  • Classical MCDM for decision making in the digital age.
  • Advanced/hybrid MCDM for Society 5.0.
  • Challenges and risks associated with MCDM
  • Strategies ensuring the responsible use of MCDM in decision-making
  • Sustainability and social equity issues MCDM.
  • Case studies of smart decision-making in different domains.

Session Chairs:

  1. Dr. Meenu Singh, Post Doctoral Researcher, Department of Computer Science
    VŠB – Technical University of Ostrava, Ostrava, Czech Republic, Email : meenu.singh@vsb.cz
  2. Dr. Maryam Olfati, Research Assistant, Department of Computer Science
    VŠB – Technical University of Ostrava, Ostrava, Czech Republic , Email : maryam.olfati@vsb.cz

NOTE: During this session, a Best Paper Award will be given to the paper that is deemed to have made the most significant contribution to the field of MCDM. The winner will be announced at the end of the session. We encourage all participants to submit their best work!

Metaheuristics for efficient and effective logistics and supply chains

Since the advent of globalisation, international trade has steadily increased, as has demand for transportation services. Traditional unimodal road transportation has given way to multimodal transportation. Transportation applications have always been challenging but stimulating, and the increase in the volume of goods transported annually around the world has increased interest in and utility of operational research methodologies, which are required to manage complex transportation systems effectively. This special session aims to provide a forum for the most recent advances in multimodal transportation issues in the context of logistics and supply chains, with new challenges and objectives implied by multimodal transportation for efficient and cost-effective logistic service, urban logistics, first-mile collection and last-mile delivery, sustainability issues, metaheuristics, and nature-inspired algorithms. This issue could include, among other things, the following topics:

  • Sustainable multimodal transport for logistics problems and metaheuristics optimization techniques,
  • The concept of multimodal transport in container logistics
  • Multimodal transport in e-commerce logistics and supply chains
  • Robust optimization and stochastic programming in multimodal city logistics,
  • Social issues in multimodal transportation during urban/city logistics, last-mile distribution, first-mile collection
  • Energy concerns and environmental issues in the design of multimodal transportation in the logistics and supply chain networks,
  • Corporate social responsibility (CSR) and human factors in the design of multimodal transport systems,
  • Multimodal transport for the circular economy,

Session Chairs:

  1. Saurabh Pratap, Assistant Professor, Indian Institute of Technology (IIT BHU), Varanasi, India (Email id: saurabh.mec@iitbhu.ac.in)
  2. Sunil Kumar Jauhar, Assistant Professor, Indian Institute of Management Kashipur, India (Email id: sunil.jauhar@iimkashipur.ac.in)


Softness in AI Computing Techniques for not so Easy Computational Problems


We solicit novel research papers (including review papers) for a special Track on Softness in AI Computing Techniques for not so Easy Computational Problems in SocProS -2023.  Soft computing strategies in the field of AI have been in picture since 1980s, and has proven their effectiveness for providing acceptable solutions to innumerable number of computationally intensive problems by applying simple nature based randomness and approximations. The softness in these soft computing strategies, though scrutinized extensively in varied fields of applications, yet their refinement continues through parametric as well as strategic variations. It won’t be untrue to say that as nature always keep on surprising us by continuously providing better solutions through its innovative, naïve and random selections in real life. This inspires the researchers also to further evolve these already existing soft computing strategies in different unexplored dimensions so as to keep on moving towards attaining betterment in efficacies of already existing solutions or generating new applications. The soft strategies therefore are being applied in almost all sub spaces of AI now a days such as Robotics, Mathematical Optimization, Machine Learning, Nature Inspired Computing, Algorithms, Networks, Data Science and many more interdisciplinary area. With the current world, society is moving towards many more unseen and wide applications, making way for this area to be explored at much wider scale for new applications or improving previous applications. Hence, we invite papers of Interest for this special track to focus around the above theme in order to strengthen research in this promising area.

Submissions in and around following areas of research (not exhaustive) revolving around special track are invited. Papers that do not necessarily fall into one of these categories but have a coverage of proposed track will also be considered.

1.     Optimization

2.     Machine learning

3.     Networks

4.     Algorithms

5.     Social Network Analytics

6.     Visualization

7.     Data science

8.     Software Engineering

9.     System Software

10.  Application software

11.  Data Analytics

12.  Security

13.  Cloud Computing

14.  Artificial Intelligence

15.  Interdisciplinary Applications in Physics , Maths and other areas

16.  Nature Inspired Computing

Track Chair(S)

  1. Dr. Shilpa Srivastava, Associate Professor , Christ(Deemed to be University), Delhi NCR, India, Email : shilpa.srivastava@christuniversity.in
  2. Dr. Nidhi Arora , Associate Professor , Department of Computer Science , Kalindi College, University of Delhi, India, Email : nidhiarora@kalindi.du.ac.in


Data Analytics and Visualization


Data analytics is important to understand trends and patterns from the massive amounts of data that are being collected from different resources. It helps to optimize business performance, forecast future results, understand audiences, and reduce costs. At present hundreds of terabyte data is generated every day. Almost all kind of business sector like finance, medical, education, marketing etc. are dependent on data analytics to take the faster and accurate decisions, predictions and forecasting for business growth. To analyze the present the data analysis with the diverse nature of data is a challenge as well as opportunities for industries and academia over the next few years. Data visualization has become a critical part of business analytics and business communications. Data visualization tools and techniques helps to present the analytics impressive, easy, effective, and efficient. Without visualization, the numbers and statistics of analytics are difficult to interpret and drawing knowledge from data. The presence of big data, with the increasing volume, verity, and velocity of data, needs visualization technique to compress large volumes of data into effective presentationswhich help strategic decision-making. Submissions in and around following areas of research (not exhaustive) revolving around special track are invited. Papers that do not necessarily fall into one of these categories but have a coverage of proposed track will also be considered.

1.     Tools, frameworks, and mechanisms for data analytics

2.     Healthcare analytics

3.     Open API for data analytics

4.     Biomedical visualization

5.     Analytics visualization

6.     Exploratory data visualization and analysis

7.     Multi-modal support for data analytics

8.     Geographic visualization

9.     High-performance data analytics

10.  Web Analytics

11.  Business analytics

12.  Graph visualization

13.  Malware analytics

14.  Multi-dimensional or Multivariate data visualization

15.  Cyber-threats analytics

16.  Small-screen visualization

17.  Geology analytics

18.  Glyph-Based Visualization

19.  High-performance computing and visualization

20.  Scientific visualization

21.  Information visualization

22.  Volume and flow visualization

23.  Deep learning for scientific data analysis and visualization


Track Chair(S)

Dr. Aprna Tripathi

Assistant Professor

Department of Data Science and Engineering Manipal University Jaipur, India,


aprna.tripathi@jaipur.manipal.edu, aprnatripathi@gmail.com


Dr. Hemlata Sharma

Sr Lecturer of Digital Analytics and Technology,

Course Leader of Data Analytics with Banking and Finance Sheffield Hallam University, United Kingdom h.sharma@shu.ac.uk


Next-generation technologies

Next-generation technologies are advanced technologies that aim to create engaging and interactive experiences for users. These technologies include Virtual Reality, Augment Reality, Mixed Reality, Artificial Intelligence, Robotics, 3D printing, Mixed reality (MR), Internet of Things, Blockchain, etc.  These innovative and immersive technologies have the potential to transform many industries, including education, entertainment, healthcare, and more. They can provide new ways for people to learn, create, and interact with the world around them. This session will focus on the development of new technologies, the emergence of AI, machine learning, deep learning, AR/VR/Metaverse/IoT, Blockchain, and robotics, and how these technologies are transforming the way businesses and individuals interact with technology. We invite original (un-published) research contributions based on the above-mentioned theme including the following topics but not limited to:

Sub Themes


1.     Augmented Reality/Virtual Reality/ Metaverse

2.     Automation and Robotics

3.     Internet of Things

4.     Library Automation-Issues and Challenges

5.     Artificial Intelligence & Machine Learning

6.     Digital Image Processing

7.     Brain-Computer interface

8.     Quantum Computing

9.     Automation and Robotics

10.  Neural Network

11.  Cyber Security

12.  Cognitive Science/Neuroscience

13.  Edge computing

14.  IoT and Health Care

15.  Digital Image Processing

16.  Health Care during Covid-19

17.  The Work-From-Home  Revolution

18.  Special Child Education

19.  Special Child Education

20.  Innovation and Programming Languages

Session Chairs:

  1. Dr. Bhanu Sharma, Assistant Professor (ECE)
    Email Id: bhanu.sharma@chitkara.edu.in
    Contact Number: 9467758414
  2. Dr. Neha Tuli,  Assistant Professor (CSE)

    Email Id : neha.tuli@chitkara.edu.in

    Contact Number:07888868524

eLegalls: Moving Towards AI-enabled Improved Civil Justice System

The evolution of Computer Science (CS) and Information Technology (IT) has helped to advance several other fields, and lately, it has begun to expand into the domain of Law as well, where their blending and cohesiveness is being dubbed Legal Informatics (LI). Currently, LI is rapidly emerging as a new, interesting research area at the confluence of CS, IT, and Law. More recently, LI has drawn attention from the computational and legal communities because of the growing popularity, increasing acceptability, broadening usage, and extensive benefits of Artificial Intelligence (AI) and its allied techniques and technologies, such as Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). The goal is to apply and utilize these modern computational technologies—AI, ML, DL, NLP—to advance and improve the existing jurisprudence/legal procedure/legal justice system/civil justice system. More and more legal scholars and practitioners and computer and data scientists and engineers are teaming up to combine their expertise and knowledge to transform the existing jurisprudence into a smart and intelligent justice system, which is faster, fair, and economically feasible for every last person of marginalized and underprivileged societies, “the poor”. This Special Session invites original, unpublished scholarly work related to information technology applied in emerging legal informatics and other areas.


The topics of interest include but are not limited to:

  • Algorithms and applications;
  • AI, ML, and DL in jurisprudence;
  • NLP and text processing;
  • Ontology and knowledge representation;
  • Legal data;
  • Generative AI in Legal space
  • Legal information retrieval;
  • Blockchain technology;
  • Learning deep from legal data;
  • Data visualization and analyses;
  • Smart contracts;
  • Legal expert systems;
  • Legal predictive systems;
  • Robo Lawyers;
  • Robo Judges
  • Automated dispute resolution systems.



Dr. Sugam Sharma, Iowa State University, USA; eLegalls.com, USA

Email: sugamsha@iastate.edu; info@elegalls.com

Homepage: https://www.cssm.iastate.edu/people/sugam-sharma, https://elegalls.com/


Dr. (Prof.) Samia Chehbi Gamoura, Strasbourg University, France

Email: samia.gamoura@em-strasbourg.eu

Homepage: https://www.em-strasbourg.com/en/researcher/lecturer/chehbi-gamoura-samia


Dr. (Prof.) Ritu Shandilya, Mount Mercy University, USA

Email: rshandilya@mtmercy.edu

Homepage: https://www.linkedin.com/in/ritu-shandilya-354ab3191/


Dr. (Prof.) Deva Prasad M (Professor of Law), Indian Institute of Management, Kozhikode, India

Email: devaprasad@iimk.ac.in

Homepage: https://iimk.ac.in/faculty-profiles/DEVA-PRASAD-M


Dr. (Prof.) Arti Aneja, Faculty of Law, University of Delhi, India

Email: artianeja@clc.du.ac.in

Homepage: http://clc.du.ac.in/community/faculty/dr-arti-aneja/


Prof. Divya Dwivedi, Advocate, Supreme Court of India

Email: divyadwivedi04@gmail.com

Homepage: https://www.linkedin.com/in/divyadwivedi04/


Aim: This special session aim to provide an international forum where researchers and practitioners in the fields of Information Technology, Communications, Data Analytics, Machine Learning and their applications can interact, exchange ideas and disseminate their accomplishments and visions. The objectives of this session can be illustrated as: To provide conceptual understanding of emerging trends in Information Technology and Communication. To develop quality software skills using innovations in software testing, software reliability and quality assurance. It will also discuss the theory behind the data analytics, information technologies. To describe machine learning applications. To explore the implementation of IT-security and ethical and social challenges related issues.


Areas of Coverage (sub-themes)

  • Machine Learning  Soft Computing
  • Deep Learning
  • Artificial Neural Network
  • Big Data analytics
  • Social Media Analytics
  • Software Engineering
  • Software Reliability
  • Data warehousing and mining
  • Artificial Intelligence System
  • IT-security, Ethical and societal Challenges
  • Other related topics

Program Committee

  • Prof. (Dr.) P K Kapur, AUUP, Noida
  • Prof. (Dr.) Daniel Okunbor, FSU, USA
  • Prof. (Dr.) D K Sharma, University of Maryland, Eastern Shore, USA
  • Dr. S. P. Singh, Birla Institute of Technology, Mesra (Noida Campus)
  • Dr. Peeyush Tewari , Birla Institute of Technology, Mesra (Noida Campus)
  • Dr. B. B. Sagar, Birla Institute of Technology, Mesra (Noida Campus)
  • Dr. Munesh Trivedi, NIT, Itanagar

Submit your research paper (in pdf format) at http://www.socpros2023.iitr.ac.in/  in paper submission link with a copy of the paper to deepakgupta_du@rediffmail.com  with “Sustainable Development in Artificial Intelligence, Machine Learning and Information Technology” mentioned in the subject line.