Edited by
Pramod Singh Rathore, Manipal University Jaipur, India.
Abhishek Kumar, Chandigarh University, India.
Priya Batta, Amity University Punjab - Mohali, India.
Inam Ul Haq, CGC University Mohali - Punjab, India.
ISBN : 9781836691624
Publication Date : October 2026
Hardcover 308 pp
170 USD
Co-publisher
Practical Graph Intelligence 2 delivers a comprehensive and application-driven exploration of graph-based methods for understanding complex, interconnected data.
This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems.
Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in today’s data-intensive environments.
1. Convolutional Neural Networks with Recurrent Layers for Network Intrusion Classification Using NSL-KDD Dataset, Ch. Srinivasa Rao, P. Tejaswini, Shaik Maheen, R. Likitha, R. Sahithya and Pranathi Uradi Reddy.
2. Spectral Graph Convolutional Networks for IoT Device Clustering and Anomalous Node Detection in Complex Network Topologies, R. Vanaja, L. Manjula, K. Ramachandran, T.R.K. Kumar, S. Leoni Sharmila and R. Balapriya.
3. Graph Intelligence-enhanced Quantum-Inspired Hybrid Algorithms for Black–Litterman Portfolio Optimization with Value-at-Risk Constraints, Srinivas Yadlapati, G. Shrinitha, G. Akshaya, G. Nandini, Erukulla Sathwika and A. Vedha Priya.
4. Graph Intelligence-Assisted Variational Autoencoders and Monte Carlo Simulations for Financial Risk Assessment in the Quantum Computing Era, Ekbal Rashid, B. Meghana, D. Sri Varshini, Dasari Harini, Chede Rethasvi and Cherala Harshini.
5. Auto-Regressive Integrated Moving Average (ARIMA) with Exogenous Variables and Fourier Features for Stock Volatility Prediction in Graph-Based Financial Networks, Mamilla Maheswari, Jerripothula Chaithanya, Gangadhari Swetha, Kucharlapati Varshitha, G. Navya Anjali and Maridi Harshini.
6. Geometric Brownian Motion and Cox–Ingersoll–Ross Models: Jump-Diffusion Processes in Graph-based Queueing Theory for Network Performance Analysis, Shivani S. Bhasgi, G. Meghana, G. Abhinaya, G. Manvitha, Chinta Samatha and A. Sandhya.
7. Enhancing Financial Fraud Detection by Leveraging Llama2 NLP and Neo4j Graph Database for Contextual Analysis and Relationship Modeling, Sakthitharan Subramanian, Karan Veer Bhandari and Mayank Kamboj.
8. Digital Finance and Financial Inclusion in India: Opportunities and Challenges, D. Gnyaneswer, Kasaram Manasa and B. Mohan Kumar.
9. Graph Intelligence-driven Early Risk Prediction in Autistic Children Using Multimodal Neuroimaging (fMRI, sMRI and EEG), P.M.G. Jegathambal and P. Sheela Gowr.
10. Susceptible–Infected–Recovered (SIR) Models with Stochastic Differential Equations: Parameter Estimation via Kalman Filtering for Graph-based Epidemic Spread Analysis, Sumaiya Samreen, Dodda Vishali, Elakoti Vaishnavi, A. Srihtiha, Gogulamudi Renu and A. Silvia Jasmine.
11. Distributed MapReduce and RDD Abstractions in Apache Spark: Scalable Graph Processing for Petabyte-Scale Datasets, D. Mahitha, Paloju Abhinaya, Thotla Manisha, Swarna Sreemayi, T. Varshitha and Thippani Harpitha.
12. Beam Processing with Watermarking and Windowing Strategies in Apache Flink for Unbounded Stream Analysis, Manish Kumar Sinha, Rishita Ganoliya, Yadlapalli Snehitha, Yarram Neha, Suma Sri Paloji and Shetti Nithisha.
13. PageRank Algorithm Enhanced with Spectral Graph Theory for Multi-Layer Network Optimization in 5G Infrastructure, Shivani S. Bhasgi, Dodle Akshaya, Bhuvana Sri Addagatla, Harsha Vardhani Adula, Christina Charis Rentapalla and D. Keerthana.
14. Graph Intelligence-enabled AI-driven Multiscale Computational Fluid Dynamics Framework for Predicting Heat and Mass Transfer in Microfluidic Channels Using Hybrid Nano-enhanced Fluids Under Transient Flow Conditions, K. Ramachandran, T.R.K. Kumar, S. Leoni Sharmila, R. Balapriya, R. Vanaja and L. Manjula.
15. AI-enabled Prediction and Inverse Design of Micro-Nano Scale Convective Heat and Mass Transfer Using Physics-informed Neural Networks Integrated with High-Fidelity Nanofluid CFD Simulations, T.R.K. Kumar, S. Leoni Sharmila, R. Balapriya, R. Vanaja, L. Manjula and K. Ramachandran.
16. Intelligent CFD–AI Hybrid Modeling of Multiphase Nanofluid Dynamics in Microfluidic Devices for Ultra-efficient Thermal Management, Energy Harvesting and Advanced Bio-thermal Applications, R. Balapriya, R. Vanaja, L. Manjula, K. Ramachandran, T.R.K. Kumar and S. Leoni Sharmila.
17. Graph Intelligence-enabled Precision Agriculture: Advanced Disease Detection System for Sugarcane Crops Using Intelligent Image Processing, Deepak Kumar Pant, Sameer Dev Sharma, Deepak Kumar and Aagman Kaparwan.
Pramod Singh Rathore is an Assistant Professor at Manipal University Jaipur, India. His expertise includes NS2, networks, data mining and DBMS.
Abhishek Kumar is a Professor at Chandigarh University, India. His expertise includes AI, renewable energy and image processing.
Priya Batta is an Associate Professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her expertise includes AI,
blockchain and IoT.
Inam Ul Haq is an Assistant Professor at the School of Engineering and Technology (SET), CGC University Mohali, Punjab, India. His expertise
includes AI, machine learning and quantum computing.
