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Ms M M Asha

Ms M M Asha View All

Assistant Professor

School of Technology

Ms. M M Asha as Assistant Professor in the Department of Computer Science and Engineering, School of Technology, The Apollo University (TAU), with effect from 22 December 2025. Ms. M M Asha completed her Bachelor’s degree in Computer Science and Engineering from Jawaharlal Nehru Technological University, Ananthapur, and her Master’s degree in Computer Science and Engineering from the same university. She has submitted her Ph.D. thesis to the School of Computer Science, Engineering and Information Systems, Vellore Institute of Technology (VIT), and is currently awaiting the viva voce examination. She has over four years of teaching experience as Assistant Professor (Junior) at Vellore Institute of Technology, Vellore, and SITAMS, Chittoor, along with industry experience as a Senior Systems Engineer at Infosys, Bangalore. She has supervised more than 20 undergraduate and postgraduate

student projects. Ms. Asha has published four research articles in International and National Journals and has one patent filed titled “Multi-Biomarker Heart Disease Risk Assessment Tool.” Her domain expertise includes Artificial Intelligence, Machine Learning, Deep Learning, and Federated Learning, and she is proficient in programming languages such as C, C++, Java, and Python. Her research focuses on Bio-Inspired Machine Learning and Optimization techniques for Cardiovascular Disease Diagnosis. Her academic interests include Object-Oriented Programming, Cloud Computing, Computer Architecture and Organization, Database Management Systems, and Formal Languages and Automata Theory.

    • Graduation In :

      B. Tech CSE

    • Graduation From :

      JNTUA

    • Graduation Year :

      2013

    • Post Graduation In :

      M. Tech CSE

    • Post Graduation From :

      JNTUA

    • Post Graduation Year :

      2018

    • Doctorate In :

    • Doctorate From :

      VIT University

    • Doctorate Year :

      Thesis Submitted

    • 4 Yrs

  • Publication in Journals 

    • Asha, M. M., & Ramya, G. (2024). Artificial Flora Algorithm Based Feature Selection with Support Vector Machine for Cardiovascular Disease Classification. IEEE Access.
    • Asha, M. M., & Ramya, G. (2025). Predator crow search optimization with explainable AI for cardiac vascular disease classification. Scientific Reports, 15(1), 11692.

    Publications in Conferences

    • Asha, M. M., & Ramya, G. (2024, June). Artificial Flora Optimization: A Novel Feature Selection Approach for Heart Disease Prediction. In 2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0 (pp. 1-5). IEEE.

    Book Chapters

    • Asha, M. M., & Govindaraj, R. (2025). A Multi-Modal Deep Learning Framework With Feature Selection for Improved Cardiovascular Disease Prediction Using ECG and PCG Signals. In Digital Twins for Sustainable Healthcare in the Metaverse (pp. 219-236). IGI Global Scientific Publishing.

    Patents

    • A Portable Device for Feature-Optimized Cardiovascular Parameter Analysis. Asha M.M., & Ramya. G IN Patent App. 202,541,115,888- published.