AI for Decision Intelligence in Critical Systems

Part 1: Introduction

1. Introduction: From Generic AI to Domain-Aware Decision Systems

Shahab Saquib Sohail, Arpita Soni, Satish Mandavalli, Shantanu Kumar, and Gautam Siddharth Kashyap

2. Comparative Analysis of CNN and Quaternion CNN for Image-Based Road Crack Detection in Computer Vision

Parth Saxena

3. Self-Structuring Neural Networks for Optimized Data Analytics Using EMANN-Like Algorithms

Priyam Ganguly and Ramakrishna Garine

4. Scalable Data Science Workflow in the Cloud

Amit Anand and Subrat Prasad

5. Survey of Trustworthy AI Frameworks: Interpretability, Fairness, and Robustness Across Domains

Sahil Tripathi

Part 2: Connecting Foundations to Applied Trustworthy AI

6. AI-based Sustainability Supply Chain Experimental Observations System: A Comprehensive Analysis

Ramakrishna Garine

7. Transforming Supply Chain Management Through AI-Driven Predictive Analytics

Srinivas Raju Gottimukkala

8. Predictive Maintenance in Critical Infrastructure Using Graph Neural Networks

Rafiq Ali

9. AI for Smart Transportation: Road Safety, Traffic Flow, and Accident Prevention

Ebad Shabbir

Part 3: Decision Intelligence for Safer, Greener Infrastructure

10. Securing Critical E-commerce Infrastructure: Unsupervised Learning and LLM-Enhanced Anomaly Detection for Web-Based Attacks

Nipun Joshi

11. Advancing Software Quality with Large Language Models, Deep Learning, and Cloud Infrastructure

Krishna Gandhi, Pankaj Verma, Vijay Govindarajan, and Raj Sonani

12. Enhancing Software Reliability Prediction with Machine Learning: Addressing Data Noise and Model Consensus

John Akkarakaran Jose

13. AI for Cyber-Physical Security in Industrial IoT Systems

Sushant Kr. Ray

14. Trustworthy LLMs for Mission-Critical Applications: Benchmarks and Gaps

Niharika Jain

Part 4: Building Reliable and Secure AI Systems

15. Bridging Theory and Practice: A LangChain-Based Virtual Assistant for Corporate AI Integration

Vijay Govindarajan

16. Uncovering Non-Linear Drivers of Equity Valuation Across Sectors

Srinivas Raju Gottimukkala

17. AI-Driven Risk Modeling and Stress Testing in Financial Services

Mohammad Anas Azeez

18. Decision Intelligence in Healthcare Finance and Insurance Systems

Zohaib Hasan Siddiqui

Part 5: AI-Enhanced Decision-Making in Business and Finance

19. Unleashing Human Potential: Advancing Cognitive Capabilities Through AI-Designed Neural Interfaces

Venu Madhav Aragani

20. Ethical, Legal, and Societal Challenges of AI in High-Stakes Decision Systems

Pushkar Arora

21. Cross-Sector Lessons and Roadmap: Towards Trustworthy and Domain-Aware AI

Abdullah Mohammad

Biography

Dr. Shahab Saquib Sohail is an Assistant Professor in the Department of Computer Science and Engineering at Jamia Hamdard, New Delhi. He previously served as a Senior Assistant Professor at VIT Bhopal University. He holds a Ph.D. in Computer Science from Aligarh Muslim University. He is recognized among the top 5 researchers globally in the Scopus database for work related to ChatGPT and among the top 2% of AI and Computer Vision researchers worldwide (Stanford–Elsevier list). He has authored more than 100 SCI-indexed journal papers, including 70 Q1 and Q2 publications. His research has appeared in high-impact venues such as Nature Machine Intelligence, Information Fusion, IEEE Transactions on Big Data, and WIREs Data Mining and Knowledge Discovery, as well as leading conferences including INTERSPEECH, IJCNN, ICASSP, and ICDM workshops. With over 3,000 Google Scholar citations, his research spans computational intelligence, recommender systems, and computational social science. Dr. Sohail is also an active collaborator with international research groups and a dedicated mentor to emerging scholars in AI and machine learning.  

Arpita Soni is a senior IT professional with over two decades of experience in software engineering, quality assurance, and program management. She specializes in generative AI, automation, and digital transformation across banking, healthcare, and supply chain sectors. A certified Project Management Professional (PMP) and Certified Scrum Master (CSM), she is also a Senior Member of IEEE and a Fellow of the British Computer Society (BCS). Arpita has led large-scale enterprise AI initiatives that enhance operational efficiency, compliance, and reliability. She has authored multiple research papers on AI and machine learning, including work on low-resource chatbots and AI integration into software development lifecycles. She is a frequent keynote speaker, session chair, and reviewer for leading IEEE, Elsevier, IGI Global, and Springer journals and conferences. Arpita is also the author of books such as AI Sustainability and Advanced Statistical Techniques for Data Mining.  

Satish Mandavalli is a Software Engineer at Microsoft with over twenty years of experience across finance, banking, healthcare, and enterprise IT systems. As a Chartered Accountant, he uniquely bridges finance and technology to design intelligent, data-driven solutions. His work focuses on applying AI and machine learning to optimize financial processes, improve risk management, and enable predictive analytics in real-world business environments. Satish is deeply invested in integrating smart, secure, and scalable AI-driven systems into financial operations. He is a strong advocate for innovation and continues to explore emerging technologies that enhance transparency, efficiency, and decision-making in financial and critical systems.  

Shantanu Kumar is a Senior Software Engineer at Amazon, where he has been instrumental in developing and scaling key e-commerce initiatives since 2016. He played a central role in building and expanding Buy with Prime, enabling seamless integrations with Shopify, BigCommerce, Salesforce, and Meta platforms. His expertise spans scalable API design, secure checkout systems, and data-driven orchestration engines that have contributed significantly to Amazon’s global commerce ecosystem. He has also worked on machine learning–based recommendation systems for Prime Video and modernized largescale data ingestion pipelines. Shantanu is a recognized mentor and leader, ranked among the top 1% mentors on ADP List. He has conducted over 50 professional development sessions worldwide and has guided hundreds of professionals in career growth and technical leadership. A graduate of the National Institute of Technology (NIT) Kurukshetra, Shantanu has received multiple performance awards at Amazon and continues to drive innovation in scalable, intelligent systems.

Gautam Siddharth Kashyap is a Ph.D. researcher at Macquarie University, specializing in the alignment of Large Language Models (LLMs) via the HHH framework—Helpfulness, Harmlessness, and Honesty. His doctoral research focuses on developing principled methods to align LLMs with human values, leading to publications at EMNLP, EACL, etc. Beyond his doctoral research, Gautam also contributes to NLP for social good, focusing on the development of ethical, inclusive, and reliable AI systems.