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Dr. Debasish Mukherjee

Dr. Debasish Mukherjee

Assistant Professor

About

Dr. Debasish Mukherjee is working as an assistant professor in school of computer science & engineering, RV University. Before joining RVU, he was working as a postdoctoral researcher in Illinois Advanced Research Center (IARCS) in Singapore. He was involved in the research project titled “Real-Time Deep Learning Networks for Fraud Detection in Modern E-Marketplace Systems”. Prior to joining as a postdoc researcher, he was working as an assistant professor in computer science & engineering at Christ University Bangalore and Indian Institute of Information Technology (IIIT) Raichur. He holds a PhD in computer science and engineering from Indian Institute of Technology (IIT-ISM) Dhanbad.

If four things are followed - having a great aim, acquiring knowledge, hard work and perseverance, then anything can be achieved - Dr. A P J Abdul Kalam

  • Debasish Mukherjee. Parallel implementation of discrete cosine transform and its inverse for image compression applications. Journal of Super computing 80, 23712–23735 (2024).https://doi.org/10.1007/s11227-024-06343-y
  • D. Mukherjee, ""FPGA Implementation of Morphological Gradient Operation using Xilinx System Generator,"" 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), Mysuru, India, 2022, pp. 1-6, doi: 10.1109/MysuruCon55714.2022.9972397.
  • D. Mukherjee and S. Mukhopadhyay, ""Hardware Efficient Architecture for 2D DCT and IDCT Using Taylor-Series Expansion of Trigonometric Functions,"" in IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 8, pp. 2723-2735, Aug. 2020, doi: 10.1109/TCSVT.2019.2928045

  • Designing hardware architectures for compute intensive applications by programming it on field programmable gate arrays (FPGA) platform.
  • Parallel programming on GPU platform.
  • Fraud detection using Large Language Models and Graph Neural Network.
  • Research Interests
  • FPGA based system design.
  • GPU based high performance computing.
  • Fraud detection using Large Language Models.
  • Graph Neural Networks.

  • Reviewer of IEEE Transactions on Circuits and Systems I: Regular Papers.

  • Reviewer of Journal of Super Computing, Springer.

Assistant Professor

Institute: School of Computer Science and Engineering

Ph.D. in Computer Science and Engineering

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