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LLMs in Practice

Real World Applications, Challenges and Success Stories

  • 1st book:metaData.edition - August 1, 2026
  • book:metaData.latestEdition
  • common:contributors.editors Kiran Jot Singh, Shubham Mahajan, Divneet Singh Kapoor, Khushal Thakur
  • publicationLanguages:language

LLMs in Practice: Real World Applications, Challenges and Success Stories offers a deeply applied, interdisciplinary perspective on how Large Language Models (LLMs) are being… seeMoreDescription

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LLMs in Practice: Real World Applications, Challenges and Success Stories offers a deeply applied, interdisciplinary perspective on how Large Language Models (LLMs) are being integrated into the real world—spanning industries, healthcare, education, governance, mental health, creative domains, and intelligent systems. The book presents a blend of technical insights, sector-specific applications, governance frameworks, and ethical considerations. Designed for both academic and professional audiences, it equips readers to responsibly deploy LLMs while fostering innovation, equity, and scalability. LLMs in Practice: Real World Applications, Challenges & Success Stories addresses a significant gap in current literature by offering a focused and practice-oriented examination of how Large Language Models (LLMs) are being applied across diverse real-world domains. While there is widespread academic and public interest in generative AI, there exists no single resource that cohesively captures its deployment frameworks, sector-specific applications, ethical considerations, and pedagogical integration—especially from a multidisciplinary and global perspective. This book provides deployment guidance, prompt optimization, and reliability strategies; governance frameworks, risk mitigation tools, and audit strategies; and offers case studies, instructional models, project templates, career-aligned examples, and skill-building paths.

promoMetaData.keyFeatures

  • Provides a comprehensive understanding of how LLMs are transforming sectors such as healthcare, education, law, and business
  • Serves as a reference for researchers, practitioners, and innovators seeking to design, evaluate, and scale generative AI systems
  • Supports educators and students by offering structured resources for teaching, learning, and project-based engagement with LLMs
  • Promotes responsible innovation by highlighting frameworks for ethical governance, transparency, and inclusive AI adoption across varied socio-economic contexts

promoMetaData.readership

Graduate students, higher undergraduates, and researchers Artificial Intelligence, Large Language Models, and Human Computer Interaction

promoMetaData.tableOfContents

Section I: Foundations of Large Language Models

1. Foundations and Frameworks for Large Language Models: Concepts and Deployment Strategies

2. Mathematical Foundations and Reasoning Capabilities of Large Language Models

Section II: Governance, Ethics, Policy, and Law

3. Responsibility Gaps in Autonomous Agentic AI: Legal and Ethical Blind Spots in Multi-Agent and Multi-Developer Systems

4. Business Transformation and Legal Innovation in the Age of Generative AI

5. Policy, Law, and AI in Healthcare: Addressing Legal Hurdles in the Use of Large Language Models

6. Enhancing Security and Privacy in the Integration of Large Language Models within Learning Management Systems

Section III: Healthcare Systems & Digital Health

7. Transforming Healthcare with Large Language Models: Innovation, Integration, and Impact

8. Revolutionizing Healthcare Systems Through Large Language Models

9. SymptoGuide: Revolutionising Digital Health through Retrieval- Augmented Generation and LLMs

Section IV: Mental Health, Neuroscience & Well-Being

10. Enhancing Mental Health and Cognitive Research with Generative AI

11. Enhancing Mental Health and Cognitive Research with Generative AI: Transformative Applications, Ethical Considerations, and Future Directions

12. Therapeutic LLMs in Mental Health: Evidence, Alignment Engineering, and SAFEE-Based Governance

13. Personalized Music-Based Neuro-Rehabilitation Using Generative AI Models

14. The Role of Generative AI in Shaping the Future of Mental Health Research

Section V: Finance, Risk & Intelligent Markets

15. Financial Services and Risk Intelligence Powered by LLMs

16. LLM-Driven Trading: Enhancing Financial Algorithms with Sentiment and Risk Analysis

17. Leveraging LLMs for marketing of Financial products for multi-lingual Consumers

Section VI: Marketing, Business Intelligence & Consumer Insights

18. LLM-Driven Marketing Strategy & Consumer Insights

Section VII: Smart Cities, Robotics & Urban Intelligence

19. Leveraging Large Language Models for Intelligent Urban Planning and Smart Cities

20. LLMs in Action: Semantic Navigation on TurtleBot4 via MCP-Based Natural Language Interface

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  • productDetails.edition: 1
  • book:metaData.latestEdition
  • productDetails.published: August 1, 2026
  • publicationLanguages:languageTitle: publicationLanguages:en

promoMetaData.aboutTheEditors

KS

Kiran Jot Singh

Kiran Jot Singh is currently an Associate Professor and Associate Dean (Academic Affairs) at Chandigarh University, Mohali, India. He has done PhD in the domain of Human Robot Interaction. He has also filed 12 patents with the Indian patent office. He is working on various funded projects, and his research interests include human robot/computer interaction, bio feedback and happiness studies through technology.

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Associate Professor and Associate Dean, Chandigarh University, India

SM

Shubham Mahajan

Dr. Shubham Mahajan is an academic and researcher and a member of IEEE, ACM, and IAENG. He earned B.Tech from Baba Ghulam Shah Badshah University, M.Tech from Chandigarh University, and a PhD from Shri Mata Vaishno Devi University (SMVDU), Katra. He is currently Assistant Professor at Amity University, Haryana. His contributions span AI and image processing, including video compression, image segmentation, fuzzy entropy, nature-inspired optimization, data mining, machine learning, robotics, and optical communications. He holds numerous patents internationally and has published extensively in venues worldwide, with papers in high-impact journals; he has edited several Scopus-indexed books. He has received multiple awards, including Best Research Paper, IEEE travel grants, and excellence in research. He has served as IEEE Campus Ambassador at premier institutes and promoted international research collaborations. He participates in Technical Program Committees and Editorial Boards for conferences and journals, shaping discourse in AI, image processing, and related domains.

Dr. Mahajan has made strong contributions in the fields of artificial intelligence and image processing. He holds nineteen Indian patents, along with one Australian and one German patent. He has published more than 103 research papers in national and international journals and conferences, including 55 in SCIE journals and 48 indexed by Scopus. He has also edited 10 Scopus-indexed books. His research areas include image processing, video compression, image segmentation, fuzzy entropy, nature-inspired algorithms, optimization, data mining, machine learning, robotics, and optical communication. He won the Best Research Paper Award at ICRIC 2019 (Springer LNEE series).

Throughout his career, Dr. Mahajan has received many awards, such as the Best Student Award (2019), IEEE Region-10 Travel Grant (2019), 2nd runner-up in IEEE RAS Hackathon (2019, Bangladesh), IEEE SERCF (2020), Emerging Scientist Award (2021), and the IEEE SPS Professional Development Grant (2021). He also received the Excellence in Research Award in 2023.

Beyond research, Dr. Mahajan has contributed to the academic community in many ways. He has worked as a Campus Ambassador for IEEE at top institutions like IIT Bombay, IIT Kanpur, IIT Varanasi, and IIT Delhi, as well as for several multinational companies. He is active in promoting international research collaborations and serves on Technical Program Committees and Editorial Boards of various international conferences and journals.

promoMetaData.affiliationsAndExpertise
Amity School of Engineering and Technology, Amity University Haryana., India

DK

Divneet Singh Kapoor

Divneet Singh Kapoor is currently an Associate Professor and Associate Dean (Academic Affairs) at Chandigarh University, Mohali, India. He has done PhD in the domain of signal processing and wireless communication. He has filed multiple patents with the Indian patent office and has been granted several, showcasing his innovative contributions to the field. His research interests span embedded systems, Internet of Things (IoT), robotics, and affective computing.

promoMetaData.affiliationsAndExpertise
Associate Professor and Associate Dean, Chandigarh University, India

KT

Khushal Thakur

Dr. Khushal Thakur is Associate Dean – Academic Affairs and Associate Professor at Chandigarh University with over a decade of experience in Electronics & Communication Engineering. He holds a Ph.D. in Massive MIMO systems and has published extensively in reputed journals such as IEEE Access, Springer, and CRC Press. His research spans IoT, embedded systems, wireless networks, and AI, and he holds several Indian patents, including three granted ones. Dr. Thakur has contributed significantly to academic planning, curriculum design, and quality assurance, supporting initiatives aligned with NBA, NAAC, and ABET standards.

promoMetaData.affiliationsAndExpertise
Electronics and Communication Engineering Department, Chandigarh University, Punjab, India