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Dr. Kaushik Das

Dr. Kaushik Das

  • Assistant Professor
    Institute of Engineering & Technology
  • Department

    Department of Electronics & Communication
  • Contact Details:

    Email : kaushik.das@gla.ac.in

    Contact Number :7005728730

  • Experience

    2 years of teaching experience.

  • Qualifications

    • Ph.D.
  • Postgraduate

    Thesis Supervised

  • Awarded/ Completed-

    Working-

  • Undergraduate

    Thesis Supervised

  • Awarded/ Completed-

    Ongoing-

Journals

  • 1 K. Das and S. N. Pradhan. Field-programmable gate array-based design for real-time computation of ensemble empirical mode decomposition. International Journal of Circuit Theory and Applications, 49 (8), 2312-2328, 2021. (SCI)
  • 2 K. Das, D. Nath and S. N. Pradhan. FPGA and ASIC realisation of EMD algorithm for real-time signal processing. IET Circuits, Devices & Systems, 14(6), 741-749, 2020. (SCI)
  • 3 K. Das and S. N. Pradhan. An efficient hardware realization of EMD for real-time signal processing applications. International Journal of Circuit Theory and Applications, 48 (12), 2202-2218, 2020. (SCI)
  • 4 K. Das and S. N. Pradhan. Hardware Architecture Design for Complementary Ensemble Empirical Mode Decomposition Algorithm. Integration, 91, 153-164, 2023. (SCI)
  • 5 K. Das and A. Ahmed. Fractal Dimension and Higher Order Statistics Based Features for Classification of Different Epileptic States. International Journal of Engineering and Techniques, 2017, pp. 13-19.
  • 6 A. Bhattacharjee, A. Nag, K. Das and S. N. Pradhan. Design of power gated SRAM cell for reducing the NBTI effect and leakage power dissipation during the hold operation. Journal of Electronic Testing, 38, 91–105, 2022. (SCI)
  • 7 A. Bhattacharjee, A. Das, D. K. Sahu, S. N. Pradhan and K. Das. A meta-heuristic search-based input vector control approach to co-optimize NBTI effect, PBTI effect, and leakage power simultaneously. Microelectronics Reliability, 144, 114979, 2023

(SCI)

International Conferences

  • 1K. Das and S. N. Pradhan. An FPGA-Based Approach to Eliminate the End Effect of EMD Using Grey Prediction Model. 2nd IEEE IAS International Conference on Computational Performance Evaluation (ComPE), 2021, pp. 426-430.
  • 2K. Das and G. K. Mourya. Classification of EEG Signals in the Improved Complete Ensemble EMD Domain. 2nd IEEE International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE), 2018, pp. 1-9.
  • 3K. Das and R. Mudoi. Analysis of EEG signals using empirical mode decomposition and support vector machine. IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), 2017, pp. 358-362.

High-Speed Communication Circuits. A week long Short Term course organized by IIT Guwahati under Special Man Power Development Programme -Chip to System Design (SMDP-C2SD).

  • 01Awarded MHRD fellowship for the Ph.D.