Sustainable Computing and Intelligent Systems

Dr. Jagdish Chand Bansal is a professor at South Asian University New Delhi and a visiting faculty at Maths and Computer Science, Liverpool Hope University UK. Dr. Bansal has obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi, he has worked as an assistant professor at ABV-Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His Primary area of interest is Swarm Intelligence and Nature Inspired Optimization Techniques. Recently, he proposed a fission-fusion social structure-based optimization algorithm, Spider Monkey Optimization (SMO), which is being applied to various problems from engineering domain. He has published more than 70 research papers in various international journals/conferences. He is the editor in chief of the journal MethodsX published by Elsevier. He is the series editor of the book series Algorithms for Intelligent Systems (AIS) and Studies in Autonomic, Data-driven and Industrial Computing (SADIC) published by Springer. Dr. Hussain is working at University of Canberra as an associate professor of Biomedical Robotics. Prior to that he has worked as a lecturer at University of Wollongong, Australia. Dr. Hussain has obtained his Ph.D. in Mechanical Engineering from the University of Auckland, New Zealand, in 2013. His research interests include assistive and rehabilitation robotics, compliant actuation of robots, robot mechanism design and optimization, non-linear dynamics and control of robotic systems, human-robot interaction, biomechanical modelling, engineering education and micro electro-mechanical systems (MEMS). Dr. Hussain has published more than 65 papers in the prestigious journals of the field.Prof. Prashant K. Jamwal earned Ph.D. degree and a post-doctoral fellowship from the University of Auckland, New Zealand. Earlier, he had obtained M.Tech. from I.I.T., India, securing first position in all the disciplines and B. Tech. from MNREC, Allahabad, India. Presently, he is working as a professor at the school of engineering and design sciences, Nazarbayev University (NU), Astana, Kazakhstan and as adjunct professor at University of Canberra, Australia. He is actively pursuing research in robotics and artificial intelligence, multi-objective evolutionary optimization, biomedical engineering, and Renewable energy. Over the past decade, he has applied his research in the development of medical robots for rehabilitation and surgical applications besides developing improved algorithms for cancer data analytics. Prof. Prashant received three prestigious World Bank Grants and has launched two startup companies and established a Center of Excellence in Medical Research and Robotics.

• Data-Driven Sustainability in Supply Chains: A Review of Analytics for Carbon Footprint Reduction.- Minimizing Return Rates in Online Fashion through Personalized Avatar-based Fitting.- A Comprehensive Analysis on WLAN MAC Layer Speed Estimation using ML based Predictors.- A Lightweight Prototype-Augmented Segmentation Network with Ablation study and Efficiency Analysis.- Energy-Efficient Cloud Computing for Carbon Footprint Reduction: A Scientometric Analysis.- GAN-Enhanced Hybrid Models for Paddy Leaf Disease Detection: Review, Challenges, and Solution Framework.- Beyond the Books: Understanding Student Stress in Modern Education.- Adaptive Waste Collection Routing in Smart Cities using Multi-Agent Systems.- Modified BIRCH-Based Hierarchical Clustering for Color Image Segmentation.- WanderSnap: A Multimodal AI Framework for Personalized and Adaptive Travel Itinerary Generation.- SynergyGrid: An Optimised Embedded IoT Architecture for Sustainable Power Monitoring and Industrial Applications.- MetPhaFrac: Detection of Metacarpophalangeal Fractures using Mask R-CNN Inception v3: An AI-driven Approach.- Decision Flow Tracing and Word Impact Analysis in Hybrid Transformer-Conditioned Diffusion Models for Text-to-Image Generation.- BFS-Net: A Bi-level Feature Selection Network for Fine Grained Sketch-Based Image Retrieval.- Improving Echocardiographic Image Quality through Hybrid Contrast Enhancement using DHE and GAN.