Ms. Swati Ankit Suchak

@sakec.ac.in

Assistant Professor, Computer Engineering Department
Shah and Anchor Kutchhi Engineering College

Ms. Swati Ankit Suchak


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https://researchid.co/swatisuchak

EDUCATION

Master of Engineering (Computer) and M. Sc. Mathematics

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Mathematics, Computer Science Applications, Computational Theory and Mathematics
2

Scopus Publications

3

Scholar Citations

1

Scholar h-index

Scopus Publications

  • Deep Reinforcement Learning-Optimized Resource Allocation Method for Edge Computing
    E. Afreen Banu, Prachi Wagde, Pallavi Nehete, Krupa Chotai, Karishma Tiware, Swati Suchak
    Proceedings Iceconf 2025 2025 2nd International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering, 2025
    The environment of edge computing requires effective resource allocation approaches to support the heterogeneous workloads, reduce the latency, and optimize the energy usage. The heuristic or rule-based approach to the issue is not always very dynamic and can fall short of the dynamic adaptability needed in response to the extremely volatile arrival of tasks and user mobility. In this paper, a Deep Reinforcement Learning-Optimized Resource Allocation framework based on the Soft Actor-Critic (SAC) algorithm, with TensorFlow implementation, is proposed to optimize the utilization of computational and communication resources in the multi-edges case. Through modelling an allocation process as a continuous state-action Markov Decision Process, the SAC agent is able to learn policies that strike a balance between task offloading, CPU allocation and power control without sacrificing latency and energy requirements. Experimental assessments show that the suggested approach minimizes significantly the infractions of task deadlines and energy consumption as opposed to heuristic guidelines on the baselines. The findings reveal the scalability, flexibility, and resiliency of DRL-based solutions and make SAC with TensorFlow a potent method of intelligent edge resources orchestration in the next generation.
  • Clinical Risk Prediction of Acute Coronary Syndrome Using Deep Learning Approach
    Swati Suchak, Uttara Gogate
    Lecture Notes in Networks and Systems, 2021

RECENT SCHOLAR PUBLICATIONS

  • Deep Reinforcement Learning-Optimized Resource Allocation Method for Edge Computing
    EA Banu, P Wagde, P Nehete, K Chotai, K Tiware, S Suchak
    2025 2nd International Conference on Artificial Intelligence and Knowledge … , 2025
    2025
  • Clinical risk prediction of acute coronary syndrome using deep learning approach
    S Suchak, U Gogate
    Intelligent Computing and Networking: Proceedings of IC-ICN 2020, 207-217 , 2020
    2020
    Citations: 3
  • Blockchian Technology: A Revolution in Economy
    PUG Ms. Swati Suchak
    International Journal for Research in Engineering Application & Management … , 2019
    2019

MOST CITED SCHOLAR PUBLICATIONS

  • Clinical risk prediction of acute coronary syndrome using deep learning approach
    S Suchak, U Gogate
    Intelligent Computing and Networking: Proceedings of IC-ICN 2020, 207-217 , 2020
    2020
    Citations: 3
  • Deep Reinforcement Learning-Optimized Resource Allocation Method for Edge Computing
    EA Banu, P Wagde, P Nehete, K Chotai, K Tiware, S Suchak
    2025 2nd International Conference on Artificial Intelligence and Knowledge … , 2025
    2025
  • Blockchian Technology: A Revolution in Economy
    PUG Ms. Swati Suchak
    International Journal for Research in Engineering Application & Management … , 2019
    2019