Guest Editors
Sachi Nandan Mohanty
School of Computer Science & Engineering, VIT-AP University
<p><span style="background-color: transparent;">Dr. Sachi Nandan Mohanty received his PhD from the Indian Institute of Technology Kharagpur in 2015 (with an MHRD scholarship) and completed his postdoctoral research at the Indian Institute of Technology Kanpur in 2019. He has authored or edited 42 books published by IEEE-Wiley, Springer, Wiley, CRC Press, NOVA, and DeGruyter. His research interests include data mining, big data analysis, cognitive science, fuzzy decision-making, brain-computer interfaces, cognition, and computational intelligence.</span></p><p><br></p><p><span style="background-color: transparent;">Dr. Mohanty has received numerous honors, including four Best Paper Awards during his PhD, the Best Thesis Award from the Computer Society of India, and the Prof. Ganesh Mishra Memorial Award at the 61st Annual Technical Session. He has guided nine PhD scholars and 23 postgraduate students and published over 120 articles in reputed international journals. He has received funding and travel awards from the Department of Science and Technology (DST) and the Science and Engineering Research Board (SERB), Government of India.</span></p><p><br></p><p><span style="background-color: transparent;">He is a Fellow of the Institute of Engineers, a Senior Member of IEEE, an Ambassador to the European Alliance for Innovation (EAI), and a member of IETE and CSI. Dr. Mohanty reviews for Elsevier and Springer journals such as </span><em style="background-color: transparent;">Robotics and Autonomous Systems</em><span style="background-color: transparent;">, </span><em style="background-color: transparent;">Computational and Structural Biotechnology Journal</em><span style="background-color: transparent;">, </span><em style="background-color: transparent;">Artificial Intelligence Review,</em><span style="background-color: transparent;"> and </span><em style="background-color: transparent;">Spatial Information Research</em><span style="background-color: transparent;">. He serves as general chair for the ICISML and AIHC conferences and is the editor-in-chief of </span><em style="background-color: transparent;">Intelligent Systems and Machine Learning Applications</em><span style="background-color: transparent;">. He has delivered keynote talks and chaired sessions internationally, including in the USA, Paris, Slovakia, Singapore, Abu Dhabi, Dubai, Malaysia, and Germany.</span></p>
Suneeta Satpathy
Center for Cyber Security, SOA Deemed to be University
<p><span style="background-color: transparent;">Dr. Suneeta Satpathy is an associate professor at the Center for AI & ML, SOA University, Odisha, India. She received her PhD in Digital Forensics and Cyber Security from Utkal University, Odisha, in 2015, supported by a scholarship from the Directorate of Forensic Sciences, Ministry of Home Affairs, Government of India. From December 2002 to December 2005, Dr. Satpathy was a research fellow in the Computer Forensic Research and Development Division at GEQD, CFSL, Hyderabad. She holds a postgraduate degree in Computer Science from O.U.A.T, Odisha (1998).</span></p><p><br></p><p><span style="background-color: transparent;">Her research interests span computer and digital forensics, cybersecurity, data fusion, data mining, big data analysis, decision mining, and machine learning. Dr. Satpathy has supervised numerous graduate and postgraduate students and published extensively in reputable international journals (Scopus and SCI-indexed) and conferences. She has also edited nine research books with publishers such as Springer, Wiley, CRC Press, and Apple Academic Press.</span></p><p><br></p><p><span style="background-color: transparent;">Dr. Satpathy serves on editorial boards and as a reviewer for several journals, including the </span><em style="background-color: transparent;">Journal of Engineering Science</em><span style="background-color: transparent;">, </span><em style="background-color: transparent;">Advancement of Computer Technology and Applications</em><span style="background-color: transparent;">, </span><em style="background-color: transparent;">Robotics and Autonomous Systems</em><span style="background-color: transparent;"> (Elsevier), and </span><em style="background-color: transparent;">Computational and Structural Biotechnology Journal</em><span style="background-color: transparent;"> (Elsevier).</span></p>
Collection Overview
In the face of mounting environmental, economic, and societal challenges, the integration of artificial intelligence (AI) and machine learning (ML) for sustainability efforts has emerged as a transformative approach. This Methods Collection aims to spotlight the latest advancements and practical applications of AI and ML that drive sustainable development across domains such as energy efficiency, climate modeling, smart agriculture, environmental monitoring, healthcare management, waste management, and sustainable urban planning.
The importance of this topic lies in the urgent global need to achieve sustainability goals while managing limited resources and mitigating the impacts of climate change. AI and ML offer unparalleled capabilities to analyze complex data, optimize resource usage, and support predictive decision-making in real-time, enabling more adaptive and intelligent solutions to sustainability challenges.
This Methods Collection seeks to serve as a comprehensive platform for researchers, practitioners, and policymakers by presenting innovative methodologies, frameworks, tools, and case studies that leverage AI and ML for sustainability. It will also encourage interdisciplinary contributions that bridge computer science, environmental studies, engineering, and public policy. By showcasing cutting-edge approaches and highlighting reproducible methods, this collection will support the research community in advancing scalable and ethical AI solutions. Ultimately, it aims to foster collaboration and knowledge exchange, accelerating progress toward a more sustainable and resilient future.
Articles
Utilizing Transfer Learning Approach for Epidemiological Study of Region-Specific Post-Acute Sequelae of SARS-COV-2
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2025
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Sabbar Rashid Lateef1, Shaymaa Ahmed Saleh2, Vikas B3, Venkateswara Rao Bolla4, Sirisha Potluri5, Yerragudipadu Subbarayudu5, P. Pavan Kumar6, G. Sucharitha7
1College of Medicine, Branch of Clinical Chemistry, Al-Iraqia University, 22Department of chemistry, College of Education for Pure Sciences, Tikrit University, 3Department of Computer Science and Engineering, Sreenidhi University, 4Department of CSE (AI & ML), St. Martin's Engineering College, 5Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, 6Department of Artificial Intelligence and Data Science, Faculty of Science and Technology, The ICFAI Foundation for Higher Education, 7Department of Computer Science and Engineering, Anurag University
Ensemble of Temporal Weighting, Causal Inference, and Hierarchical Attribution towards SHAP Optimization
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2025
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Archana Salaria1, Manik Rakhra1, Nonita Sharma2, Monika Mangla3, Fernando Moreira4, Nishan Singh Bala5
1School of Computer Science Engineering, Lovely Professional University, 2Department of Information Technology, Indira Gandhi Delhi Technical University for Women, 3Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, 4REMIT, IJP, Universidade Portucalense, 5Oakville Trafalgar High School, Halton District School Board
Machine Learning-Based Multimodal Molecular Biomarkers for Predictive Health Analytics
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2026
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1Department of CSE, Vidya Jyothi Institute of Technology, 2Department of Artificial Intelligence and Data Science, JB Institute of Engineering and Technology, 3Department of CSE, Sri Chaitanya Institute of Technology and Research, 4Department of CSE, Saveetha Engineering College, 5Department of Artificial Intelligence and Data Science, Rajalakshmi Engineering College, 6Department of CSE, B. S. Abdur Rahman Crescent Institute of Science and Technology
Abstracts
Machine Learning Models for Soil Moisture Forecasting and Smart Irrigation in Arid Regions: Insights from Morocco’s Draa Valley
Abdessamad ELMOTAWAKKIL*1
1Department of Computer Science Faculty of Sciences, University Ibn Tofail Kenitra, Morocco
Leveraging Artificial Intelligence in HR Analytics: Transforming Talent Management and Organizational Decision-Making
Niranchana Shri Viswanathan*1
1Assistant Professor
EFFICIENT OVARIAN CANCER CLASSIFICATION USING MACHINE LEARNING MODELS
Hemalatha B1,
Karthik B1,
Vijayaragavan S P1,
Deepa Jose Jose*2
1Bharath Institute of Higher Education and Research,
2KCG College of Technology
A ROBUST EXPLAINABLE RECURRENT DEEP Q LEARNING FOR DETECTING MULTICLASS INTRUSIONS IN IOT
Padmasri Turaka1,
Saroj Panigrahy*1
1VIT-AP University
BRAIN TUMOUR DETECTION BASED ON DEEP LEARNING AND PERFORMANCE ANALYSIS WITH MULTIPLE OPTIMIZERS
Pattisapu Manikanta Manohar*1
1Dept. of Computer Science and Engineering, GITAM School of Technology, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India
Human-Machine Interaction in Regional Print Newsrooms: Automation of News and its Ethical Challenges
Pulkit Sharma1,
Dr Prabhat Dixit*2
1Centre for Distance and Online Education Manipal University Jaipur Jaipur, 303007, Rajasthan, India,
2Assistant Professor, Department of Journalism and Mass Communication Manipal University Jaipur Jaipur, 303007, Rajasthan, India
Real-Time Cancer Detection: Machine Learning Approach to Multi-Cancer Classification
Dilip Kumar Gokapay*1
1VIT-AP University
IMPROVING THE PERFORMANCE OF LEAF DISEASE DETECTION AND CLASSIFICATION USING BEETLE SWARM OPTIMIZATION TECHNIQUE
Penugonda Seetha Rama Krishna*1
1Research Scholar,Department of Computer Science Engineering,Annamalai University, Chidambaram, Tamilnadu
Reducing Hallucinations in Summarization via Reinforcement Learning with Entity Hallucination Index
Praveen Katwe1,
Rakesh Chandra Balabantaray*2,
Kali Prasad Vittala3,
Muktikanta Sahu2
1IIIT Bhubaneswar and Informatica,
2IIIT Bhubaneswar,
3Informatica
Transfer Learning and UNet Segmentation for Paddy Leaf Disease Classification: A Solution with User-Friendly Interface for Non-Technical Users
Penugonda Seetha Rama Krishna*1
1Research Scholar,Department of Computer Science Engineering,Annamalai University, Chidambaram, Tamilnadu
A NOVEL HYBRID APPROACH FOR BRAIN TUMOR CLASSIFICATION IN MRI:ViT-GRU AND GNet-SVM MODELS
Sital Dash*1
1Department of Computer Engineering, Faculty of Science and Technology, Vishwakarma University, Pune, Maharashtra, India. 411048
UTILIZING TRANSFER LEARNING APPROACH FOR EPIDEMIOLOGICAL STUDY OF REGION-SPECIFIC POST-ACUTE SEQUELAE OF SARS-COV-2
Sirisha Potluri*1
1Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad-500043, Telangana, India.
A Healthcare system based on Deep Learning Techniques for the Identification of Gastric Cancer
Jyoti Garg*1
1Maharishi Markandeshwar(Deemed to be University) Mullana, Ambala
Enhancing Medical Image Quality: An Efficient Deep Learning-Based Denoising Approach
Shwetha Dareshwar1,
Manjula Gururaj Rao*2,
Piyush Parek3
1NITTE (Deemed to be University), NM Institute of Technology Bengaluru,
2NITTE (Deemed to be University), NMAM Institute of Technology Nitte, Karkala,
3 NITTE (Deemed to be University), NMAM Institute of Technology Nitte, Karkala
Neurocognitive Analysis of Problem-Solving Stages: Investigating Cognitive Representations Using Electroencephalography
Kishore Kanna R*1
1Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science & Technology, Chennai, India
Revolutionizing Brain Tumor Diagnosis with Adaptive CNN Models
Kishore Kanna R*1
1Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science & Technology, Chennai, India
Innovative Hybrid Bio-Inspired Deep Learning Models for the Automated Diagnosis of Monkey Pox from Medical Images
Bhawani Sankar Panigrahi 1,
Kishore Kanna R*2
1GITAM School of Technology, GITAM University, Vishakhapatnam, India,
2Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology
TCHSHAP: Ensemble of Temporal Weighting, Causal Inference and Hierarchical Attribution for SHAP Optimization
Monika Mangla*1
1Dwarkadas J. Sanghvi College of Engineering
A SMART APPROACH FOR SANSKRIT SLOKA CLASSIFICATION USING TRANSFORMER-BASED MURIL MODEL
Nagendra Panini Challa*1,
Basaraboina Yohoshiva1
1VIT-AP University, Andhra Pradesh, India
Multi-Modal Accelerated Deep Learning Techniques for Brain Tumor Diagnosis
Dilip Kumar Gokapay*1
1VIT-AP University
Machine Learning-Based Multimodal Molecular Biomarkers for Predictive Health Analytics
Merlin Linda G*1
1Associate Professor, Department of Computer Science and Engineering, Vidya Jyothi Institute of Technology, Hyderabad, 500075
Innovative Framework for Detection of Damaged Road Surface and Probable Mosquito Breeding Sites
Sonali Bhutad*1
1Shah and Anchor Kutchhi Engineering College, Chembur
Ensemble Deep Learning Models for Robust and Interpretable Prediction of Healthcare Fraud.
MJ D Ebineze*1
1 Depament Of CSE, Koneru Lakshmaiah Educationrt Foundation, Vaddeswaram, India.