Assistant Professor
Computer Science and Artificial Intelligence
GIET University, Odisha
19 Years
Artificial Intelligence, Evolutionary Computing, Machine Learning
Evolutionary ANNs, HONNs, and Financial Time Series
Ph.D in Computer Science and Engineering from GIET University, Odisha
M.Tech in Computer Science and Engineering from GIET, BPUT, Odisha
B.Tech in Computer Science and Engineering from JITM, BPUT, Odisha
Associate Professor at Sree Dattha Institute of Engineering and Science, Hyderabad, from 2024-11-11 to 2025-05-10.
Associate Professor at Sphoorthy Engineering College, from 2023-03-06 to 2024-07-25.
Assistant Professor at Sreenidhi Institute of Engineering and Science, from 2015-04-16 to 2023-02-28.
Assistant Professor at Gandhi institute of Engineering and Technology, from 2009-08-12 to 2015-03-31.
Assistant Professor at Khadeer Memorial College of Engineering and Technology, from 2005-01-03 to 2009-07-31.
PG
UG
1. Sudersan Behera, Sarat Chandra Nayak, & A V S Pavan Kumar, “A Comprehensive Survey on Higher Order Neural Networks and Evolutionary Optimization Learning Algorithms in Financial Time Series Forecasting” in Archives of Computational Methods in Engineering, Volume 30, 4401–4448 (2023), SPRINGER, SCIE, Q1, IF 12.1, https://doi.org/10.1007/s11831-023-09942-9
2. Sudersan Behera, Sarat Chandra Nayak, & A V S Pavan Kumar, “Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting”, Computational economics, Volume 64,1219–1258 (2023), SPRINGER, SCIE, Q2, IF 2.2, https://doi.org/10.1007/s10614-023-10466-4
3. Sudersan Behera, A V S Pavan Kumar, & Sarat Chandra Nayak, “Improved Set Algebra-Based Heuristic Technique for Training Multiplicative Functional Link Artificial Neural Networks for Financial Time Series Forecasting”. SN COMPUT. SCI. Volume 5, 567 (2024). SPRINGER, SCOPUS, Q2 https://doi.org/10.1007/s42979-024-02902-5
4. Sudersan Behera, A V S Pavan Kumar, & Sarat Chandra Nayak, “Analyzing the performance of geometric mean optimization- Based artificial neural networks for cryptocurrency forecasting”. International Journal of Information Technology. (2024). SPRINGER, SCOPUS, Q2, https://doi.org/10.1007/s41870-024-01953-4
5. Sudersan Behera, A V S Pavan Kumar, & Sarat Chandra Nayak, “Enhanced Stock Index Forecasting: Metaheuristic Insights and Extreme Learning Machines Evaluation”. Vision, 0(0), (2025). SAGE, ESCI, SCOPUS, Q3, IF 3.1, https://doi.org/10.1177/09722629251349031
6. Abdul Khadeer, Vanaparthi Kiranmai, B. Suvarnamukhi, Ayaz Mohiuddin, Balika Mahesh, P M Suresh, J Arthy, Sasikumar A N, Sudersan Behera, Mohd Ayaz Uddin “SAHAANN: A Novel Evolutionary Artificial Neural Network for Improved Financial Time Series Forecasting”. Proceedings on Engineering Sciences, (2025) SCOPUS, Q3, DOI: 10.24874/PES07.01D.020
7. Sudersan Behera “Metaheuristic-Based Support Vector Machines for Exchange Rate Forecasting”, SSRG International Journal of Recent Engineering Science, Volume 11 Issue 2, 31-38, (2024), SSRG, https://doi.org/10.14445/23497157/IJRES-V11I2P105
8. Sudersan Behera, P M Suresh “Enhancing Bitcoin Price Prediction with Evolutionary Radial Bias Function Networks”, in IJIMSR, EDUSKILL Publisher, Vol 2, No, 1 (2024), https://ijimsr.org/abstract.php?id=33
9. Pratap Sekhar Puhan, Sudersan Behera “Soft Computing Approach to Detect Fault in Induction Motor". i-manager’s Journal on Electrical Engineering, 12(2), 6-14, (2018), https://doi.org/10.26634/jee.12.2.14845
10. Sudersan Behera “Application of Cloud Computing in Healthcare Domain” in International Journal of Scientific Engineering and Research (IJSER) in the year 2017, https://www.ijser.in/archives/v5i7/IJSER171673.pdf
11. Sudersan Behera, A V S Pavan Kumar, & Sarat Chandra Nayak, (2024). “Predicting Stock Market Prices Using a Hybrid of High-Order Neural Networks and Barnacle Mating Optimization”. In: Kumar, R., Verma, A.K., Verma, O.P., Wadehra, T. (eds) Soft Computing: Theories and Applications. SoCTA 2023. Lecture Notes in Networks and Systems, vol 971. Springer, Singapore.SCOPUS. https://doi.org/10.1007/978-981-97-2089-7_25
12. Sudersan Behera, A V S Pavan Kumar, & Sarat Chandra Nayak, (2023). "Improved Firefly-Based Pi-Sigma Neural Network for Gold Price Prediction" at the 2023 OITS International Conference on Information Technology (OCIT) in Raipur, India, IEEE, WOS and SCOPUS. https://ieeexplore.ieee.org/document/10430837
13. Sudersan Behera, A V S Pavan Kumar, & Sarat Chandra Nayak, (2024) "Forecasting Financial Commodities Using an Evolutionary Optimized Higher-Order Artificial Neural Network" In: Chillarige, R.R., Distefano, S., Rawat, S.S. (eds) Advances in Computational Intelligence and Informatics. ICACII 2023. Lecture Notes in Networks and Systems, vol 993. Springer, Singapore.SCOPUS. https://doi.org/10.1007/978-981-97-4727-6_23
14. Sudersan Behera, G. Kadirvelu, P. Sambasiva Rao, P. Jangaiah, G.V Prasad, Kailash Sinha, (2024). "Financial Time Series Forecasting Using Hybrid Evolutionary Extreme Learning Machine". In: Tripathi, A.K., Anand, D., Nagar, A.K. (eds) Proceedings of World Conference on Artificial Intelligence: Advances and Applications. WCAIAA 2024. Algorithms for Intelligent Systems. Springer, Singapore. WOS, https://doi.org/10.1007/978-981-97-4496-1_7
15. Sudersan Behera "Knowledge Mining from a Large Volume of Dataset Using Fuzzy Association Rules" at the International Conference on Intelligent Sustainable Systems (ICISC) in Tamil Nadu in 2019. IEEE, SCOPUS and WOS, https://ieeexplore.ieee.org/document/9036356.
16. Sudersan Behera "Implementation of Finite State Automaton to Identify and Remove Stop Words from English Text Documents on Retrieval" at the International Conference on Emerging Trends in Information Technology (ICOEI) in Tamil Nadu in 2018. IEEE, SCOPUS and WOS, https://ieeexplore.ieee.org/document/8553828
17. Sudersan Behera, Sarat Chandra Nayak, Sanjib Kumar Nayak, Sung-Bae Cho, (2024), "A Swarm Optimised Deep Learning Model for Financial Time Series Forecasting”, In book: Computing, Communication and Intelligence (pp.283-286), Srinivas Sethi, Bibhudatta Sahoo, Deepak Tosh, Suvendra Kumar Jayasingh, Sourav Kumar Bhoi (Eds), Taylor & Francis, SCOPUS, https://doi.org/10.1201/9781003581215
18. Sudersan Behera, Attili Venkata Ramana, P Venkata Pratima, Kailash Sinha, P Sambasiva Rao, Mohd Ayaz Uddin, (2024). "Evolutionary hybrid neural networks for time series forecasting," 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), Gwalior, India, 2024, pp. 1-6, IEEE, SCOPUS and WOS. https://ieeexplore.ieee.org/document/10502740
19. N. Sahoo, M. Srividya, B. Surekha, G. Divyavani, K. Karthikeyan and S. Behera, "Enhancing Exchange Rate Forecasting with Genetically Optimized RBFN," 2024 IEEE International Conference on Smart Power Control and Renewable Energy (ICSPCRE), Rourkela, India, 2024, pp. 1-6, IEEE, SCOPUS and WOS, https://ieeexplore.ieee.org/document/10675215
20. Pratap Sekhar Puhan, Sudersan Behera "Application of Soft Computing Methods to Detect Fault in A.C. Motor" at ICAC'3 in Mumbai in 2017.IEEE, SCOPUS and WOS, https://ieeexplore.ieee.org/document/8318754
The method involves the initiatio transaction request by a user utilizing a unique cryptographic key, which is verified by a decentralized network of nodes through consensus mechanisms. A smart con the blockchain is executed to authorize the transaction based on predefined rules, and the authenticated transaction is recorded in an immutable and transparent le method ensures the security and transparency of digital transactions, mitigating vulnerabilities associated with centralized systems.
The present invention introduces a sophisticated deep reinforcement learning (DRL) framework tailored for autonomous navigation in unstructured environments. C framework is a neural network architecture adept at processing raw sensor data from diverse modalities. Guided by a reinforcement learning algorithm with a reward mechanism, the system iteratively learns optimal navigation policies through trial and error.
Received Best Paper Presentation Award for the Paper titled "Financial Time Series Forecasting Using Hybrid Evolutionary Extreme Learning Machine" in WCAIAA 2024 .
Received Reviewers certificate from one of the top most journal "Archives of Computational Methods in Engineering" of Computer Science.
Reviewers Certificate Received from 3 rd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI-2025)
