• Singur, Hooghly, West Bengal, India

Samit Bhanja

  • Designation : Assistant Professor
  • Highest Qualification : M.Tech. in CSE
  • Subject Taught : C/C++, Java, Internet Technology, Operating System, Soft Computing
  • Academic Experience : 12 + years
    • Assistant Professor (W.B.E.S.) in Computer Science at GGDC Singur since 2015 to till date.
    • Assistant Professor in Computer Science at Scotish Churge College from 2014 to 2015.
    • Assistant Professor in Master of Computer Applications at Seacom Engineering College from 2010 to 2014.
  • Number of Publications : Thirteen (09)
    • Conference : 01
    • Journal : 04
    • Book Chapter : 04
  • Recent Publication Details (last 3 years) :
    • Book/Book Chapter : 
      • Bhanja, S., & Das, A. (2021). Deep neural network for multivariate time-series forecasting. In Proceedings of international conference on frontiers in computing and systems (pp. 267-277). Springer, Singapore. 
      • Bhanja, S., & Das, A. (2021). A Deep Learning Framework to Forecast Stock Trends Based on Black Swan Events. In Proceedings of International Conference on Innovations in Software Architecture and Computational Systems (pp. 221-235). Springer, Singapore.
      • Bhanja, S., & Das, A. (2021). Electrical Power Demand Forecasting of Smart Buildings: A Deep Learning Approach. In Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing (pp. 71-82). Springer, Singapore. 
      • Bhanja, S., & Das, A. (2021). Deep Learning Approaches to Improve Effectiveness and Efficiency for Time Series Prediction. In Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing (pp. 71-82). Springer, Singapore.
    • Journals :    
      • Bhanja, S., & Das, A. (2019). Deep learning-based integrated stacked model for the stock market prediction. Int. J. Eng. Adv. Technol, 9(1), 5167-5174.
      • Bhanja, S., & Das, A. (2021). A hybrid deep learning model for air quality time series prediction. Indonesian Journal of Electrical Engineering and Computer Science, 22(3), 1611-1618. 
      • Bhanja, S., & Das, A. (2022). A Black Swan event-based hybrid model for Indian stock markets trends prediction. Innovations in Systems and Software Engineering, 1-15.
      • Bhanja, S., Metia, S., & Das, A. (2022). A hybrid neuro-fuzzy prediction system with butterfly optimization algorithm for PM2. 5 forecasting. Microsystem Technologies, 1-16. 
         

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