Journals

1.P K Rath, R Samantaray, S Mahato, S Mishra, S K Patro, Himansu Das, "Feature selection using war strategy optimization algorithm for software fault prediction", Int. J. of Computational Science and Engineering, Inder Science

2.Kumar, H., & Himansu Das (2025). Cost-Effective Prediction Model for Optimal Selection of Software Faults Using Coati Optimization Algorithm. SN Computer Science, 6(5), 420.

3.Mishra, S., Himansu Das, Mohapatra, S. K., Khan, S. B., Alojail, M., & Saraee, M. (2025). A hybrid fused-KNN based intelligent model to access melanoma disease risk using indoor positioning system. Scientific Reports, 15(1), 7438.

4.Anand, K., Jena, A. K., Himansu Das, Askar, S. S., & Abouhawwash, M. (2025). Software defect prediction using wrapper-based dynamic arithmetic optimization for feature selection. Connection Science, CRC Press, 37(1), 2461080.

5.Anand, K., Jena, A. K., & Himansu Das (2024). Implementation of Chernobyl disaster optimizer based feature selection approach to predict software defects. F1000Research, CRC Press, 13, 844.

6.Himansu Das, S Das, M K Gourisaria, S B Khan, A Almusharraf, A I Alharbi, and T R Mahesh, Enhancing Software Fault Prediction through Feature Selection with Spider Wasp Optimization Algorithm, IEEE Access.

7.Pethe, Y. S., Gourisaria, M. K., Singh, P. K., & Himansu Das. (2024). FSBOA: feature selection using bat optimization algorithm for software fault detection. Discover Internet of Things, 4(1), 6. 

8.P K Rath, S Ghosh, M K Gourisaria, S Mahato, and Himansu Das, A Wrapper based Feature Selection Approach using Osprey optimization for Software Fault Detection, Int. J. of Embedded Systems, Inder Science 

9.Himansu Das, Muskan, & H Kumar, Feature Selection using Tasmanian Devil Optimization Algorithm for Software Fault Prediction, Int. J. of Computational Science and Engineering, Inder Science 

10.J K Rout, C Thaokar, Himansu Das, & M Rout, Fake content detection on benchmark dataset using various deep learning models, Int. J. of Computational Science and Engineering, Inder Science

11.Ghosh, S., Gourisaria, M.K., Sahoo, B, & Himansu Das, A pragmatic ensemble learning approach for rainfall prediction. Discover Internet of Things, Springer 3, 13 (2023). https://doi.org/10.1007/s43926-023-00044-3

12.Prajapati, S., Himansu Das, & Gourisaria, M.K. Feature selection using differential evolution for microarray data classification. Discover Internet of Things, Springer 3, 12 (2023). https://doi.org/10.1007/s43926-023-00042-5

13.Panigrahi, S.K.; Goswami, V.; Apat, H.K.; Mund, G.B.; Himansu Das; Barik, R.K. PQ-Mist: Priority Queueing-Assisted Mist–Cloud–Fog System for Geospatial Web Services. Mathematics 2023, 11, 3562. https://doi.org/10.3390/math11163562

14.Mallick, S. R., Lenka, R. K., Goswami, V., Sharma, S., Dalai, A. K., Himansu Das, & Barik, R. K. (2023). BCGeo: Blockchain-assisted geospatial web service for smart healthcare system. IEEE Access.

15.Himansu Das; Prajapati, S.; Gourisaria, M.K.; Pattanayak, R.M.; Alameen, A.; Kolhar, M. Feature Selection Using Golden Jackal Optimization for Software Fault Prediction. Mathematics 2023, 11, 2438. https://doi.org/10.3390/math11112438

16.Nayak, N.; Das, S.R.; Panigrahi, T.K.; Himansu Das; Nayak, S.R.; Singh, K.K.; Askar, S.S.; Abouhawwash, M. Overshoot Reduction Using Adaptive Neuro-Fuzzy Inference System for an Autonomous Underwater Vehicle. Mathematics 2023, 11, 1868. https://doi.org/10.3390/math11081868

17.Padhi, B. K., Chakravarty, S., Naik, B., Pattanayak, R. M., & Himansu Das (2022). RHSOFS: Feature Selection Using the Rock Hyrax Swarm Optimization Algorithm for Credit Card Fraud Detection System. Sensors, 22(23), 9321.

18.Gourisaria, M. K., Chandra, S., Himansu Das, Patra, S. S., Sahni, M., Leon-Castro, E., ... & Kumar, S. (2022, May). Semantic Analysis and Topic Modelling of Web-Scrapped COVID-19 Tweet Corpora through Data Mining Methodologies. In Healthcare (Vol. 10, No. 5, p. 881). MDPI.

19.Pattanayak, R. M., Sangameswar, M. V., Vodnala, D., & Himansu Das, (2022). Fuzzy time series forecasting approach using lstm model. Computación y Sistemas, 26(1), 485-492.

20.Himansu Das, B Naik and H S Behera, "Optimal Selection of Features using Artificial Electric Field Algorithm for Classification”, Arabian Journal for Science and Engineering, Springer, 2021 

21.Himansu Das, B Naik and H S Behera, "A Jaya Algorithm based Wrapper Method for Optimal Feature Selection in Supervised Classification", Journal of King Saud University - Computer and Information Sciences, Elsevier, 2020

22.Himansu Das, B Naik and H S Behera, "Biomedical Data Analysis using Neuro-Fuzzy Model with Post-feature Reduction", Journal of King Saud University - Computer and Information Sciences, Elsevier, 2020 

23.Himansu Das, B Naik and H S Behera, "A Hybrid Neuro-Fuzzy and Feature Reduction Model for Classification",Advances in Fuzzy System, Hindawi, 2020

24.Himansu Das, B Naik, H S Behera, "Medical Disease Analysis using Neuro-Fuzzy with Feature Extraction Model for Classification", Informatics in Medicine Unlocked, Elsevier, 2020

25.A K Mishra, S R Das, P K Roy, R K Mallick, Himansu Das, "Harmonic distortion minimization in power system using differential evolution based active power filters", Recent Advances in Computer Science and Communications, Bentham Science, 2021

26.S R Das, P K Ray, D P Mishra, and Himansu Das, "Performance assessment of PV integrated Model Predictive Controller based hybrid filter for Power Quality Improvement", International Journal of Power Electronics, Inderscience, 2021

27. S R Das, P K Ray, A Mohanty, Himansu Das, "Performance Evaluation of Multilevel inverter based Hybrid Active Filter Using Soft Computing Techniques", in Evolutionary Intelligence, Springer, 2019 https://doi.org/10.1007/s12065-019-00217-6

Conferences

1.Jha, R., Kumari, S., Ray, A., Gourisaria, M. K., Panda, A. R., & Das, H. (2024, July). Comparative Analysis of Sentiment Classification using Feature Engineering for Social Media. In 2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN) (pp. 434-440). IEEE.

2.Parihar, V., Gourisaria, M. K., Singh, J. P., Das, H., Panda, A. R., & Mishra, S. R. (2024, June). Deciphering PCOS: Precision Diagnosis through Advanced Machine Learning Techniques. In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.

3.Biraja Isac, N., & Das, H. (2024, May). Optimizing Hyper-Parameters for Sanskrit to English Neural Machine Translation with LSTM and GRU Models. In International Conference on Data & Information Sciences (pp. 159-167). Singapore: Springer Nature Singapore.

4.Rath, P. K., Mahato, S., Gourisaria, M. K., Patro, S. K., & Das, H. (2024, May). WOAFS: Feature Selection Using Whale Optimization Algorithm for Software Fault Prediction. In International Conference on Data & Information Sciences (pp. 121-146). Singapore: Springer Nature Singapore.

5.Rath, P. K., Mahato, S., Bhowmik, R., Gourisaria, M. K., & Das, H. (2024, February). CSOFS: Feature Selection Using Cuckoo Search Optimization Algorithm for Software Fault Detection. In 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC) (pp. 456-461). IEEE.

6.Rath, P. K., Mahato, S., Singh, N., Gourisaria, M. K., & Das, H. (2024, February). FPAFS: Feature Selection Using the Flower Pollination Algorithm for Software Fault Detection System. In 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC) (pp. 439-444). IEEE.

7.Pethe, Y. S., & Das, H. (2024, June). Feature Selection using Genetic Algorithm for Software Fault Prediction. In 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 1132-1137). IEEE.

8.Payne, P., Singh, V., Gourisaria, M. K., Patra, S. S., & Das, H. (2024, January). Insomnia, Sleep Apnea, Serenity: Unveiling Sleep Disorders with Machine Learning. In 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) (pp. 1603-1609). IEEE.

9.Romould, R. V., Singh, V., Gourisaria, M. K., Das, H., & Dash, B. B. (2024, January). Deciphering Migraine Types: A Machine Learning Odyssey for Precision Prediction. In 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) (pp. 1610-1616). IEEE.

10.Pethe, Y. S., Uparkar, S., & Das, H. (2023, November). Data Mining Classification Techniques to Analyze the TV Market Data. In 2023 2nd International Conference on Futuristic Technologies (INCOFT) (pp. 1-5). IEEE.

11.Raj, R., Tiwari, P., Gourisaria, M. K., & Das, H. (2023, December). Efficient Object Detection and Labeling in Retail Environments using MobileNetV2 with Inverted Residuals. In 2023 OITS International Conference on Information Technology (OCIT) (pp. 634-639). IEEE.

12.P. Tiwari, R. Raj, H. Das and M. K. Gourisaria, "A Comparative Analysis of Regression Models for Crop Yield Prediction Based on Rainfall Data: Experimental Study and Future Perspective," 2023 International Conference on Network, Multimedia and Information Technology (NMITCON), Bengaluru, India, 2023, pp. 1-6, doi: 10.1109/NMITCON58196.2023.10275902.

13.Shah, H., Das, H. (2023). A Wrapper-based Feature Selection Approach Using Particle Swarm Optimization for Software Fault Prediction. In: Das, A.K., Nayak, J., Naik, B., Vimal, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. CIPR 2022. Lecture Notes in Networks and Systems, vol 725. Springer, Singapore. https://doi.org/10.1007/978-981-99-3734-9_31

14.Pethe, Y. S., & Das, H. (2023, May). Software fault prediction using a differential evolution-based wrapper approach for feature selection. In 2023 International Conference on Communication, Circuits, and Systems (IC3S) (pp. 1-6). IEEE.

15.Prajapati, S., Das, H., & Gourisaria, M. K. (2023, March). Feature Selection using Ant Colony Optimization for Microarray Data Classification. In 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1-6). IEEE.

16.Kumari, S., Gourisaria, M. K., Das, H., & Banik, D. (2023, April). Deep Learning Based Approach for Milk Quality Prediction. In 2023 11th International Conference on Emerging Trends in Engineering & Technology-Signal and Information Processing (ICETET-SIP) (pp. 1-6). IEEE.

17.Pati, N., Gourisaria, M. K., Das, H., & Banik, D. (2023, April). Wind Speed Prediction using Machine Learning Techniques. In 2023 11th International Conference on Emerging Trends in Engineering & Technology-Signal and Information Processing (ICETET-SIP) (pp. 1-6). IEEE.

18.Prajapati, S., Das, H., & Gourisaria, M. K. (2023, February). Feature Selection using Genetic Algorithm for Microarray Data Classification. In 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) (pp. 1-6). IEEE.

19.Samantaray, R., & Das, H. (2023, March). Performance Analysis of Machine Learning Algorithms Using Bagging Ensemble Technique for Software Fault Prediction. In 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1-7). IEEE.

20.Mondal, S., Sahu, A. K., Kumar, H., Pattanayak, R. M., Gourisaria, M. K., & Das, H. (2023, March). Software Fault Prediction using Wrapper based Ant Colony Optimization Algorithm for Feature Selection. In 2023 6th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1-6). IEEE.

21.Kumar, H., & Das, H. (2023, February). Software Fault Prediction using Wrapper based Feature Selection Approach employing Genetic Algorithm. In 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) (pp. 1-7). IEEE.

22.Prajapati, S., Das, H., & Gourisaria, M. K. (2023, February). Microarray Data Classification using Machine Learning Algorithms. In 2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) (pp. 1-6). IEEE.

23.Kundu, A., Dutta, P., Ranjit, K., Bidyadhar, S., Gourisaria, M. K., & Das, H. (2022, December). Software Fault Prediction Using Machine Learning Models. In 2022 OITS International Conference on Information Technology (OCIT) (pp. 170-175). IEEE.

24.Batabyal, A., Singh, V., Gourisaria, M. K., & Das, H. (2022, December). Sleep Stress Level Classification through Machine Learning Algorithms. In 2022 OITS International Conference on Information Technology (OCIT) (pp. 91-96). IEEE.

25.Singh, U., Singh, V., Gourisaria, M. K., & Das, H. (2022, July). Spam Email Assessment Using Machine Learning and Data Mining Approach. In 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT) (pp. 350-357). IEEE.

26.Dutta, H., Gourisaria, M. K., & Das, H. (2022). Wrapper Based Feature Selection Approach Using Black Widow Optimization Algorithm for Data Classification. In International Conference on Computational Intelligence in Pattern Recognition (pp. 487-496). Springer, Singapore.

27.Singh, V., Agrawal, R., Gourisaria, M. K., Singh, P. K., & Das, H. (2022, April). Comparative Analysis of Machine Learning Models For Early Detection of Fetal Disease using Feature Extraction. In 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) (pp. 169-175). IEEE.

28.Agrawal, R., Singh, V., Gourisaria, M. K., Sharma, A., & Das, H. (2022, April). Comparative Analysis of CNN Architectures for Maize Crop Disease. In 2022 10th International Conference on Emerging Trends in Engineering and Technology-Signal and Information Processing (ICETET-SIP-22) (pp. 1-7). IEEE.

29.Sarah, S., Gourisaria, M. K., Khare, S., & Das, H. (2022). Heart Disease Prediction Using Core Machine Learning Techniques—A Comparative Study. In Advances in Data and Information Sciences (pp. 247-260). Springer, Singapore.

30.Singh, V., Gourisaria, M. K., & Das, H. (2021, September). Performance Analysis of Machine Learning Algorithms for Prediction of Liver Disease. In 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON) (pp. 1-7). IEEE.

31.A Kumar, R Razi, A Singh and Himansu Das, "Res-VGG : A Novel Model for Plant Disease Detection by Fusing VGG16 and ResNet Models", in 2nd International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, Springer

32.S Ghosh, S Karmakar, S Gantayat, S Chakraborty, D Saha and Himansu Das, "MLAI: An Integrated Automated Software Platform to Solve Machine Learning Problems", 2nd International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy, Springer

33.S Chakraborty and Himansu Das, "Performance Analysis of Feature Extraction Techniques for Medical Data Classification", 2nd International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy , Springer 

34.K P Panigrahi, A K Sahoo, and Himansu Das, ”A CNN Approach for Corn Leaves Disease Detection to support Digital Agricultural System”, in 4th International Conference On Intelligent Computing And Control Systems, IEEE, 2020

35.K P Panigrahi, Himansu Das, A K Sahoo and S C Moharana, "Maize Leaf Disease Detection and Classification using Machine Learning Algorithms", in International Conference on Computing, analytics, and networking, Springer, 2020

36.A Behura, A Behura, and Himansu Das, "Counterfeit Product Detection Analysis and Prevention as well as Prepackage Coverage Assessment Using Machine Learning", in International Conference on Computing, analytics, and networking, Springer, 2020

37.Himansu Das, B Naik, H S Begera, "Disease Classification using Linguistic Neuro-Fuzzy Model", in International Conference on Computing, analytics, and networking, Springer, 2020 (Scopus Indexed)

38.K Singh, J K Rout and Himansu Das, "Diabetes Prediction using Machine Learning Techniques", in International Conference on Intelligent Computing and Remote Sensing, IEEE, 2019 (Under Production) (Scopus Indexed)

39.B Panda, S C Moharana, Himansu Das and M K Mishra, "Energy Aware Virtual Machine Consolidation for Load Balancing in Virtualized Environment", in 4th International Conference on Communication and Electronics Systems, IEEE, 2019 (Scopus Indexed)

40.P Das, A R Jamader, B R Acharya, and Himansu Das, "HMF Based QoS aware Recommended Resource Allocation System in Mobile Edge Computing for IoT", in 3rd International Conference On Intelligent Computing And Control Systems, IEEE, 2019  (Scopus Indexed)

41.A Ayush, A Kumar, A Jha, N Sarkar, S C Moharana and Himansu Das, "Voice Controlled Automatic Dustbin with Garbage Level Sensing", in 3rd International Conference On Intelligent Computing And Control Systems, IEEE, 2019  (Scopus Indexed)

42.S Mohanty, S C Moharana, Himansu Das and S C Satpathy, "QoS Aware Group Based Workload Scheduling in Cloud Environment", in 3rd International Conference on Data Engineering and Communication Technology , Springer India, 2019 (Scopus Indexed)

43.Himansu Das, B Naik, and H S Behera, "An Experimental Analysis of Machine Learning Classification Algorithms on Biomedical Data", in 2nd International Conference on Communication, Devices and Computing, Springer India, 2019 (Scopus Indexed)

44.M Rout, A K Jena, J K Rout and Himansu Das, "Teaching-Learning Optimization Based Cascaded Low Complexity Neural Network Model for Exchange Rates Forecasting ", 3rd International Conference on Smart Computing & Informatics, Springer India, 2019. (Scopus Indexed) 

45.A Panigrahi, C Rout, C Badjena, Himansu Das, "An Approximate solution to the NP-Complete Joint Problem in Multi-Radio WMN", in 3rd International Conference on Smart Computing & Informatics, Springer India, 2019. (Scopus Indexed)

46.A Panigrahi, C Rout, C Badjena, Himansu Das, "Dynamic Channel Assignment Strategies in Multi Radio Wireless Mesh Network ", in 17th International Conference on Information Technology, IEEE India, 2019. (Scopus Indexed)

47.A K Das, M Pradhan, A K Das, C Pradhan, and Himansu Das, "A Constructive Machine Translation System for English to Odia Translation", in 7th International Conference on Communication and Signal Processing, IEEE India, 2018. (Scopus Indexed)

48.Himansu Das, AK Jena, JC Badajena, C Pradhan, and RK Barik, "Resource Allocation in Co-operative Cloud Environments", in International Conference on Computing, Analytics and Networking, Springer India, 2018. (Scopus Indexed)

49.Himansu Das, Bighnaraj Naik, and H S Behera, "Classification of Diabetes Mellitus Disease (DMD): A Data Mining (DM) Approach", in International Conference on Computing, Analytics and Networking, Springer India, 2018. (Scopus Indexed)

50.R Sahani, Shatabdinalini, C Rout, JC Badajena, AK Jena, Himansu Das, "Classification of Intrusion Detection using Data Mining Techniques", in International Conference on Computing, Analytics and Networking, Springer India, 2018. (Scopus Indexed)

51.RK Barik, A Tripathi, H Dubey, RK Lenka, T Pratik, S Sharma, K Mankodiya, V Kumar, and Himansu Das, "MistGIS: Optimizing Geospatial Data Analysis Using Mist Computing ", in International Conference on Computing, Analytics and Networking, Springer India, 2018. (Scopus Indexed)

52.P Sarkhel, Himansu Das, and L K Vashishtha, "Task Scheduling Algorithms in Cloud Environment", In 3rd International Conference on Computational Intelligence in Data Mining, Springer India, 2017. (Scopus Indexed)

53.I Kar, RNR Parida, Himansu Das," Energy Aware Scheduling using Genetic Algorithm in Cloud Data Centers "  in International Conference on Electrical, Electronics, and Optimization Techniques, IEEE, 2016. (Scopus Indexed)

54.Sarkar, Joy Lal, C R Panigrahi, B Pati, and Himansu Das. "A Novel Approach for Real-Time Data Management in Wireless Sensor Networks." In 3rd International Conference on Advanced Computing, Networking and Informatics, Springer India, 2016, pp. 599-607. (Scopus Indexed)

55.I Kar, H Das, "Energy Aware Task Scheduling Using Genetic Algorithm in Cloud Datacentres", International Journal of Computer Science and Information Technology Research, Vol. 4, Issue 1, 2016, pp: 106-111 

56.AK Sahoo, H Das, "Energy Efficient Scheduling Using DVFS Technique in Cloud Datacenters", International Journal of Computer Science and Information Technology Research, Vol. 4, Issue 1, 2016, pp: 59-66

57.Panigrahi, C R, Joy Lal Sarkar, B Pati, and Himansu Das. "S2S: A Novel Approach for Source to Sink Node Communication in Wireless Sensor Networks." In 3rd International Conference on Mining Intelligence and Knowledge Exploration, Springer India, 2015, pp. 406-414. (Scopus Indexed)

58.Himansu Das, A K Jena, J Nayak, B Naik, and H. S. Behera, "A Novel PSO Based Back Propagation Learning-MLP (PSO-BP-MLP) for Classification," In 2nd International Conference on Computational Intelligence in Data Mining-Volume 2, Springer India, 2015, pp. 461-471. (Scopus Indexed)

59.Himansu Das, A K Jena, P K Rath , B Muduli , S R Das, "Grid Computing Based Performance Analysis of Power System: A Graph Theoretic Approach",  in International Conference on Intelligent Computing, Communication & Devices, Springer India, 2015,  pp. 259-266. (Scopus Indexed)

60.Himansu Das, G S Panda, B Muduli, and P K Rath. "The Complex Network Analysis of Power Grid: A Case Study of the West Bengal Power Network." In  International Conference on Advanced Computing, Springer India, 2014, pp. 17-29. (Scopus Indexed)

61.Himansu Das, D.S.Roy, “A Grid Computing Service for Power System Monitoring,” International Journal of Computer Applications (IJCA), 2013, Vol. 62 No. 20, pp 1-7. 

62. Himansu Das, D.S.Roy, “The Topological Structure of the Odisha Power Grid: A Complex Network Analysis”, in International Journal of Mechanical Engineering and Computer Applications (IJMCA), 2013, Vol.1 Issue 1, pp 12-18.

Book Chapters

1.Himansu Das, Gourisaria, M. K., Sah, B. K., Bilgaiyan, S., Badajena, J. C., & Pattanayak, R. M. (2022). E-Healthcare System for Disease Detection Based on Medical Image Classification Using CNN. In Empirical Research for Futuristic E-Commerce Systems: Foundations and Applications (pp. 213-230). IGI Global.

2.Himansu Das, S Chakraborty, B Acharya, A K Sahoo, "Optimal Selection of Features based on Teaching Learning based Optimization Algorithm for Classification", in Applied Intelligent Decision Making in Machine Learning, CRC Press.

3.AK Sahoo, C Pradhan, Himansu Das, "Performance Evaluation of Different Machine Learning Methods and Deep-Learning Based Convolutional Neural Network for Health Decision Making", in Nature Inspired Computing for Data Science, Springer, 2020.

4.AK Sahoo, S Mallik, C Pradhan, BSP Mishra, RK Barik, Himansu Das, "Intelligence based Health Recommendation System using Big Data Analytics", in Big Data Analytics for Intelligent Healthcare Management, Elsevier, 2019

5.RK Barik, M Kandpal, H Dubey, V Kumar  and Himansu Das, "Geocloud4GI: Cloud SDI Model for Geographical Indications Information Infrastructure Network", in Cloud Computing for Geospatial Big Data Analytics:  Intelligent Edge, Fog and Mist Computing, Springer, 2019

6.J Nayak, B Naik, A K Jena, Himansu Das, "Nature Inspired Optimizations in Cloud Computing: Applications and Challenges", in Cloud Computing for Optimization: Foundations, Applications and Challenges, Springer, 2018

7.RK. Barik, H Dubey, C Misra, D Borthakur, N Constant, SA Sasane, RK Lenka, BSP Mishra, Himansu Das and K Mankodiya, "Fog Assisted Cloud Computing in Era of Big Data and Internet-of-Things: Systems, Architectures and Applications" , Cloud Computing for Optimization: Foundations, Applications and Challenges, Springer, 2018

8.KHK Reddy, Himansu Das, D S Roy, "A Data Aware Scheme for Scheduling Big-Data Applications with SAVANNA Hadoop", in Futures of Network, CRC Press, 2017. 

9.Panigrahi, C R, M Tiwary, B Pati, and Himansu Das., "Big Data and Cyber Foraging: Future Scope and Challenges." In Techniques and Environments for Big Data Analysis, Springer India, 2016, pp. 75-100.

10. Himansu Das, Bighnaraj Naik, Bibudendu Pati, and Chhabi Rani Panigrahi, "A Survey on Virtual Sensor Networks Framework," International Journal of Grid & Distributed Computing (IJGDC), 2014, Vol. 7 no. 5, pp 121-130.

1.Himansu Das, C R Pradhan, S Bhatia, Kuan-Ching Li, Intelligent Technologies: Concepts, Applications, and Future Directions, Volume 4, Studies in Computational Intelligence, Springer Singapore

2.Himansu Das, A A Acharya, Kuan-Ching Li, Intelligent Technologies: Concepts, Applications, and Future Directions, Volume 3, Studies in Computational Intelligence, Springer Singapore

3.S R Dash, Himansu Das, Kuan-Ching Li, Esau Villatoro Tello, Intelligent Technologies: Concepts, Applications, and Future Directions, Volume 2, Studies in Computational Intelligence, Springer Singapore

4.S Bilgaiyan, J Singh, and Himansu das, Empirical Research for Futuristic E-Commerce Systems: Foundations and Applications, IGI Global

5.Himansu Das, J K Rout, S C Moharana, N Dey, "Applied Intelligent Decision Making in Machine Learning", CRC Press 

6.Himansu Das, P K Pattnaik, S S Rautaray, K C Li, "Progress in Computing, Analytics, and Networking: Proceedings of ICCAN 2019", Springer.

7.J K Rout, M Rout, Himansu Das, "Machine Learning for Intelligent Decision Science", Springer

8.A K Jena, Himansu Das, D P Mohapatra, "Automated Software Testing: Foundation, Applications and Challenges", Springer

9.Himansu Das, C Pradhan,  and N Dey, "Deep Learning for Data Analytics: Foundations, Applications and Challenges", Elsevier.

10.M Rout, J K Rout, Himansu Das, "Nature Inspired Computing for Data Science", Springer 

11.Himansu Das, N Dey, and V E Balas, "Real-Time Data Analytics for Large Scale Sensor Data", Elsevier.

12.N Dey, Himansu Das, B Naik, and H S Behera, "Big Data Analytics for Intelligent Healthcare Management", Elsevier.

13.Himansu Das, R K Barik, H Dubey, and D S Roy, "Cloud Computing for Geospatial Big Data Analytics:  Intelligent Edge, Fog and Mist Computing ", Springer 

14.N Dey, A S Ashour, H Kalia, R T Goswami, and Himansu Das, " Histopathological Image Analysis in Medical Decision Making", IGI Global, 2019, pp:1-340, doi:10.4018/978-1-5225-6316-7

15.Mishra, BB, S Dehuri, BK Panigrahi, AK Nayak, BSP Mishra, and Himansu Das, "Computational Intelligence in Sensor Networks", vol. 776, Studies in Computational Intelligence, Springer, 2018, doi: 10.1007/978-3-662-57277-1 

16.Patnaik, PK, S S Routray, Himansu Das, and J Naik, "Progress in Computing, Analytics, and Networking: Proceedings of  ICCAN - 2017", vol. 710, Advances in Intelligent Systems and Computing, Springer, 2018, pp:1-845, doi: 10.1007/978-981-10-7871-2

17.Pradhan, Chittaranjan, Himansu Das, Bighnaraj Naik, and Nilanjan Dey. "Handbook of Research on Information Security in Biomedical Signal Processing", IGI Global, 2018. pp:1-414. Web. 30 Mar. 2018. doi:10.4018/978-1-5225-5152-2

18. Mishra, BSP, Himansu Das, Satchidananda Dehuri, and Alok Kumar Jagadev, "Cloud Computing for Optimization: Foundations, Applications, Challenges" Vol. 39, Studies in Big data Series, Springer, 2018, pp:1-463, doi: 10.1007/978-3-319-73676-1

1.Himansu Das, M K Gourisaria, Fuzzy Logic and Computational Intelligence, MDPI (2024)

2.Himansu Das, Applied AI for Sustainable Data Science and Machine Learning, Springer (2024)