Dr. Sibarama Panigrahi
Dr. Sibarama Panigrahi has completed his M.Tech and Ph.D. in Computer Science and Engineering from Veer Surendra Sai University of Technology, Odisha, India. He has been sanctioned with five research grants from major funding agencies of India like Science and Engineering Research Board (SERB), Indian Council of Medical Research (ICMR), Odisha State Higher Education Council (OSHEC), Sambalpur University and Hindalco. Recently, He has developed and deployed an electricity load forecasting software employing deep learning models for India’s one of the major Power Distribution Company Tata Power Western Odisha Distribution Limited (TPWODL) through his research project sponsored by OSHEC. He has published more than 40 research papers in reputed Journals and Conferences. His research interest includes Swarm and Evolutionary Algorithms, Machine Learning, Deep Learning and Time Series Forecasting. He has served as a reviewer of more than 30 reputed international SCI Journals. He has delivered more than 10 invited technical talks in Seminars, Symposia, Webinars, Faculty Development Programs and Workshops in institutions of national importance. He is a Senior member of IEEE and presently working on developing Crude Oil Price Forecasting Methodologies employing Deep Learning Models through his project sponsored by SERB, Govt. of India. Apart from research, he loves to teach, deliver talks and learn by discussing with the audience.
Biographical Info
EDUCATION
- VSSUT, Burla, Odisha, India
- Doctor of Philosophy (2019)
- VSSUT, Burla, Odisha, India
- M.Tech in Computer Science & Engineering
- BPUT, Odisha, India
- B.Tech in Computer Science & Engineering
ACHIEVEMENT
- UGC-NET, Computer Science & Application
- GATE – 2011, 2012, 2013
PROFESSIONAL EXPERIENCE
- Teaching: 8+ yrs
- Research: 6+ yrs
- Subjects Taught: Algorithm, Theory of Computation, Compiler Design, Programming and Data Structure, Database Management System, Machine Learning, Soft Computing.
- Area of Specialization :
- Machine Learning
- Guidance
- B.Tech: 20
- M.Tech: 08
RESEARCH
- Training/Workshop: 6
- SCI JOURNAL PUBLICATIONS
| 1 | Sibarama Panigrahi, and Himansu Sekhar Behera. “A hybrid ETS–ANN model for time series forecasting.” Engineering Applications of Artificial Intelligence 66 (2017): 49-59. ISSN: 0952-1976 [Elsevier, IF:6.20, SCI, Scopus] |
| 2 | Sibarama Panigrahi, and Himansu Sekhar Behera. “A study on leading machine learning techniques for high order fuzzy time series forecasting.” Engineering Applications of Artificial Intelligence 87 (2020): 103245. ISSN: 0952-1976. [Elsevier, IF:6.20, SCI, Scopus] |
| 3 | Sibarama Panigrahi, and H. S. Behera. “Time Series Forecasting Using Differential Evolution-Based ANN Modelling Scheme.” Arabian Journal for Science and Engineering 45.12 (2020): 11129-11146. ISSN: 2191-4281 [Springer, IF:2.33, SCI, Scopus] |
| 4 | Panigrahi, Sibarama. “A Novel Hybrid Chemical Reaction Optimization Algorithm with Adaptive Differential Evolution Mutation Strategies for Higher Order Neural Network Training.” International Arab Journal of Information Technology (IAJIT) 14.1 (2017). ISSN: 1683-3198 [IF:0.66, SCI, Scopus] |
| 5 | Sibarama Panigrahi, Radha Mohan Pattanayak, Prabira Kumar Sethy, Santi Kumari Behera. “Forecasting of Sunspot Time Series Using a Hybridization of ARIMA, ETS and SVM Methods.” Solar Physics 296.1 (2021): 1-19. ISSN: 0038-0938 [Springer, IF:2.67, SCI, Scopus] |
| 6 | Radha Mohan Pattanayak, Sibarama Panigrahi, and H. S. Behera. “High-order fuzzy time series forecasting by using membership values along with Data and Support Vector Machine.” Arabian Journal for Science and Engineering 45.12 (2020): 10311-10325. ISSN: 2191-4281 [Springer, IF:2.33, SCI, Scopus] |
| 7 | Radha Mohan Pattanayak, H. S. Behera, and Sibarama Panigrahi. “A novel probabilistic intuitionistic fuzzy set based model for high order fuzzy time series forecasting.” Engineering Applications of Artificial Intelligence 99 (2021): 104136. ISSN: 0952-1976 [Elsevier, IF:6.20, SCI, Scopus] |
| 8 | Radha Mohan Pattanayak, H. S. Behera, and Sibarama Panigrahi. “A Non-Probabilistic Neutrosophic Entropy Based Method For High Order Fuzzy Time Series Forecasting.” Arabian Journal for Science and Engineering. Accepted (In Press). [Springer, IF:2.33, SCI, Scopus] |
| 9 | Santi Kumari Behera, Prabira Kumar Sethy, Santosh Kumar Sahoo, Sibarama Panigrahi, Sharad Chandra Rajpoot. “On-tree fruit monitoring system using IoT and image analysis.” Concurrent Engineering 29, no. 1 (2021): 6-15. ISSN: 1063-293X [IF:1.01, SCI, Scopus] |
| 10 | Prabira Kumar Sethy, Chanki Pandey, Mohammad Rafique Khan, Santi Kumari Behera, K. Vijaykumar, Sibarama Panigrahi. “A cost-effective computer-vision based breast cancer diagnosis.” Journal of Intelligent & Fuzzy Systems Preprint (2021): 1-11. ISSN: 1064-1246 [IF:1.85, SCI, Scopus] |
| 11 | Manoj Kumar Kar, Sanjay Kumar, Arun Kumar Singh, Sibarama Panigrahi, “A modified Sine Cosine algorithm with ensemble search agent updating operators for small signal stability analysis.” International Transaction on Electrical Energy Systems, Accepted (In Press). ISSN:2050-7038 [Wiley, IF:2.86, SCI, Scopus] |
| 12 | Sourav Kumar Purohit, Sibarama Panigrahi, Prabira Kumar Sethy, Santi Kumari Behera, “Time Series Forecasting of Price of Agricultural Products Using Hybrid Methods”, Applied Artificial Intelligence, pp. 1-19, 2021. DOI: https://doi.org/10.1080/08839514.2021.1981659.[Taylor and Francis, IF:1.58, SCI, Scopus] |
| 13 | Rojalin Pradhan, Sibarama Panigrahi, Prabhat Kumar Sahu, “Implementation of gradient gravitational search algorithm towards conformational search”, Computational and Theoretical Chemistry, no. 1208, pp. 113550, 2022. [Elsevier, IF:1.92, SCI, Scopus] |
- INTERNATIONAL CONFERENCE PUBLICATIONS
| 1 | S. Panigrahi, B. Rath, P. S. Kumar “A Hybrid CRO-K-Means Algorithm for Data Clustering,” Computational Intelligence in Data Mining-Volume 3. Springer, New Delhi, 2015. pp. 627-639.ISBN: 978-81-322-2202-6 |
| 2 | S. Panigrahi, H. S. Behera, A. Abraham “A Fuzzy Filter Based Hybrid ARIMA-ANN Model for Time Series Forecasting,” International Conference on Soft Computing and Pattern Recognition. Springer, Cham, 2016.ISBN:978-3-319-60617-0 |
| 3 | S. Panigrahi, H. S. Behera “An Adaptive Fuzzy Filter-Based Hybrid ARIMA-HONN Model for Time Series Forecasting,” Computational Intelligence in Data Mining. Springer, Singapore, 2019. 841-850.ISBN:978-981-10-8054-8 |
| 4 | R. M. Pattanayak, H.S. Behera, S. Panigrahi “A novel hybrid differential evolution PSNN for fuzzy time series forecasting,” Computational Intelligence in Data Mining. Springer, Singapore, 2020. 675-687.ISBN:978-981-10-8054-8 |
| 5 | R. M. Pattanayak, H.S. Behera, S. Panigrahi “A multi-step-ahead fuzzy time series forecasting by using hybrid chemical reaction optimization with pi-sigma higher-order neural network,” Computational Intelligence in Pattern Recognition. Springer, Singapore, 2020. 1029-1041.ISBN: 978-981-13-9041-8 |
| 6 | S. Panigrahi, H. S. Behera “Fuzzy Time Series Forecasting: A Survey,” Computational Intelligence in Data Mining. Springer, Singapore, 2020. 641-651.ISBN:978-981-10-8054-8 |
| 7 | S. Panigrahi, H.S. Behera, “Time Series Forecasting using a hybrid Jaya-FLANN model,” In 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE), 2018, pp. 3402-3407. IEEE. |
- Sponsored R & D Projects
| # | Project Details |
| 1 | Title: Big Data Platform for Temporal Storage of Clinical Data of Patients of Cardio Vascular Disease (CVD) and Data Mining for Better Diagnosis and Treatment
Co-Investigator: Dr. Sibarama Panigrahi Funding Agency: Indian Council of Medical Research, Government of India. Amount: Rs. 21,15,000/- |
| 2 | Title: Design and Development of Large Scale Time Series Forecasting Methods using Deep Learning Techniques
Principal Investigator: Dr. Sibarama Panigrahi Scheme: Odisha University Research and Innovation Incentivization Plan(OURIIP) Funding Agency: OSHEC, Government of Odisha. Amount: Rs. 4,50,000/- |
| 3 | Title: Studies on Deep Learning Models for Crude Oil Price Forecasting
Principal Investigator: Dr. Sibarama Panigrahi Scheme: Core Research Grant Funding Agency: SERB, Government of India. Amount: Rs. 22,07,700/- |
| 4 | Title: Studies on Machine Learning, Statistical and Hybrid Models for Streamflow Forecasting of Mahanadi River
CO-PI: Dr. Sibarama Panigrahi Scheme: Research and Development Project Funding Agency: Sambalpur University, Government of Odisha. Amount: Rs. 50,000/- |
| 5 | Title: Design and Development of Pot Temperature Forecasting Methods Employing Machine Learning Techniques
PI: Dr. Sibarama Panigrahi Scheme: Consultancy Project Funding Agency: Hindalco, Hirakud Amount: Rs. 3,54,000/- |
REVIEWER OF INTERNATIONAL JOURNALS
| 1 | IEEE Access |
| 2 | Engineering Applications of Artificial Intelligence, Elsevier |
| 3 | Expert Systems with Applications, Elsevier |
| 4 | Information Sciences, Elsevier |
| 5 | IEEE Transactions on Knowledge and Data Engineering |
| 6 | IEEE Transactions on Emerging Topics in Computing |
| 7 | Journal of Forecasting, Wiley |
| 8 | Evolutionary Intelligence, Springer |
| 9 | International Journal of Data Science and Analytics, Springer |
| 10 | Plos One |
| 11 | MethodsX, Elsevier |
| 12 | Information Fusion, Elsevier |
| 13 | Soft Computing, Springer |
| 14 | Pattern Recognition, Elsevier |
RESEARCH PROFILE
| Name | ||
| 1 | Google Scholar | |
| 2 | Research Gate | |
| 3 | SCOPUS | |
| 4 | ORCHID | |
| 5 | Web of Science |
- spanigrahi@suiit.ac.in
- 7377302566