Himansu Das
Himansu Das
Associate Professor
Dr. Himansu Das, works as Associate Professor in the School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Deemed to be University, Bhubaneswar, India. He has received Ph.D. in Engineering degree from Veer Surendra Sai University of Technology (VSSUT), Odisha. He has received M.Tech degree in Computer Science and Engineering from the National Institute of Science and Technology, Odisha. He has also received B.Tech degree from the Institute of Technical Education and Research, Odisha, India. He has published several research papers in various international journals and has presented at conferences. He has also edited several books published by IGI Global, Springer, CRC press, and Elsevier. He has also served on many journals and conferences as editorial or reviewer board member. He is proficient in the field of Computer Science Engineering and served as an organizing chair, a publicity chair and acted as a member of the technical program committees of many national and international conferences. His research interests include the field of Data Mining, Soft Computing, and Machine Learning. He has also more than seventeen years of teaching and research experience in various engineering colleges and universities.
Profile Links
Email :
[email protected]
Website :
sites.google.com
Google Scholar :
https://scholar.google.co.in/citations?hl=en&user=OnjKfNQAAAAJ&view_op=list_works&sortby=pubdate
Social Links
Research Interests
1. Machine Learning 2. Dimensionality Reduction 3. Feature Selection Classification and Clustering
Administrative Responsibility
1. Faculty in Charge, Laboratories, School of Computer Engineering, KIIT Deemed to be University, India. 2. Course Coordinator, Operating System Laboratory, School of Computer Engineering, KIIT Deemed to be University, India. (2021) 3. Course Coordinator, Operating System, School of Computer Engineering, KIIT Deemed to be University, India. (2020) 4. Course Coordinator, Operating System Lab, School of Computer Engineering, KIIT Deemed to be University, India. (2019) Course Coordinator, Computer Organization and Architecture, School of Computer Engineering, KIIT Deemed to be University, India. (2018) Faculty in Charge, Time Table, School of Computer Engineering, KIIT Deemed to be University, India. Faculty in Charge, Quality Assurance Cell, School of Computer Engineering, KIIT Deemed to be University, India. Faculty in Charge, Project, School of Computer Engineering, KIIT Deemed to be University, India. Faculty in Charge, Library, School of Computer Engineering, KIIT Deemed to be University, India. Course Coordinator, Computer Organization and Architecture Subject, School of Computer Engineering, KIIT Deemed to be University, India. (2016)"
Awards & Honours
1. Summer Research Fellow 2014, Indian Science Academy 2. Conducted several Community service Programs for the rural, un-employed and un-organized youth to give Awareness on “Computer and internet related Applications 3. Guided several students in doing their projects and helped poor students to obtain their settle in teaching position.
1. Machine Learning 2. Dimensionality Reduction 3. Feature Selection Classification and Clustering
Administrative Responsibility
1. Faculty in Charge, Laboratories, School of Computer Engineering, KIIT Deemed to be University, India. 2. Course Coordinator, Operating System Laboratory, School of Computer Engineering, KIIT Deemed to be University, India. (2021) 3. Course Coordinator, Operating System, School of Computer Engineering, KIIT Deemed to be University, India. (2020) 4. Course Coordinator, Operating System Lab, School of Computer Engineering, KIIT Deemed to be University, India. (2019) Course Coordinator, Computer Organization and Architecture, School of Computer Engineering, KIIT Deemed to be University, India. (2018) Faculty in Charge, Time Table, School of Computer Engineering, KIIT Deemed to be University, India. Faculty in Charge, Quality Assurance Cell, School of Computer Engineering, KIIT Deemed to be University, India. Faculty in Charge, Project, School of Computer Engineering, KIIT Deemed to be University, India. Faculty in Charge, Library, School of Computer Engineering, KIIT Deemed to be University, India. Course Coordinator, Computer Organization and Architecture Subject, School of Computer Engineering, KIIT Deemed to be University, India. (2016)"
Awards & Honours
1. Summer Research Fellow 2014, Indian Science Academy 2. Conducted several Community service Programs for the rural, un-employed and un-organized youth to give Awareness on “Computer and internet related Applications 3. Guided several students in doing their projects and helped poor students to obtain their settle in teaching position.
Journals/Conferences :
Journals (27)
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 (62)
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
Books :
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
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
Journals (27)
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 (62)
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
Books :
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
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
Himanshu Das
Assistant Professor
[email protected]
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Edited Books/Volumes (5)
- N Dey, A S Ashour, H Kalia, R T Goswami, Himansu Das, ” Histopathological Image Analysis in Medical Decision Making” (Under Process)
- 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
- Patnaik, PK, S S Routray, Himansu Das, 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
- 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
- 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
Journals/Conferences (14)
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 (4)
- 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
- 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
- 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.
- 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.
National Conferences (2)
- Himansu Das, D.S.Roy, “Grid Computing Based Power System Monitoring, Analysis, and Control: A Graph Theoretic Approach,” National Conference on High Performance Computing and Simulation (NCHPCS), 2013, pp. 40-44, Print ISBN: 978-93-82208-55-6.
- Himansu Das, D.S.Roy, “The Topological Structure of the Odisha Power Grid: A Complex Network Analysis,” National Conference on Advanced Computing Techniques and Applications (NCACTA-2012), 2012, pp. 47-53.
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