Dr Roopashree S

Dr Roopashree S

Associate Professor

PhD

roopashrees.cse@bmsce.ac.in

Research Interests: Machine Learning, Deep Learning and Generative AI

About

Dr. Roopashree S currently working as Associate Professor in Department of Computer Science and Engineering is a highly motivated and accomplished professional with over 16 years of experience spanning both academia and industry. With 9 years of specialized research expertise in the area of machine learning, deep learning and Generative AI. She has achieved significant milestones in her academic journey. Dr. Roopashree S earned her Bachelor's degree in Computer Science and Engineering from Mysore University in 2001, followed by a Master's degree in Computer Science and Engineering from Visveswaraya Technological University in 2013. She subsequently completed her Ph.D. in 2022 in machine learning and computer vision at Visvesvaraya Technological University in Belagavi, India. Dr. Roopashree is a dedicated researcher in the fields of Artificial Intelligence, Computer Vision, Machine Learning, Generative AI, Large Language Models, Small Language Models and Image Processing. She has an impressive track record, including the publication of four Indian patents and the grant of German Utility Patent and two Australian patent. As a Senior Member of IEEE and a lifetime member of the Computer Society of India, Dr. Roopashree has significantly contributed to both research and academia. She has published over 30 papers in peer-reviewed international journals, including those indexed in Web of Science and SCIE Q1 and Q2 categories, authored one text book and three book chapters. In addition, she is an active reviewer for leading SCIE journals. Her achievements extend to work as R&D consultant to start-ups, receiving KSCST sponsorship for three projects, and securing first place for a project in the IEEE humanitarian project proposal. Moreover, her team clinched first place in the Smart India Hackathon 2020.

Education

  • Doctor of Philosophy - Machine Learning and Deep Learning
    Visvesvaraya Technological University
    Passed Year: 2022 | Program Type: PartTime
  • Master of Technology - Computer Science and Engineering
    Visvesvaraya Technological University
    Passed Year: 2013 | Program Type: FullTime
  • Bachelor of Engineering - Computer Science and Engineering
    Mysore University
    Passed Year: 2001 | Program Type: FullTime

Selected Publications

  • Journal | Published On : 03-06-2024
    B. Pranesh, H. Bohara, L. Mahalakshmi, M. Jain and S. Roopashree
    B. Pranesh, H. Bohara, L. Mahalakshmi, M. Jain and S. Roopashree, “Enhancing Data Curation with LLaMA Model,” Indiana Journal of Multidisciplinary Research, vol. 4, no. 3, pp. 10–15, Jun. 2024. DOI: https://doi.org/10.5281/zenodo.12666871. (National Journal)
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  • Journal | Published On : 03-06-2024
    A. Patel, L. Kusuma, S. Tantradi, S. Bekinal and S. Roopashree
    A. Patel, L. Kusuma, S. Tantradi, S. Bekinal and S. Roopashree, “Breaking Language Barriers: A Global Translation Initiative,” Indiana Journal of Multidisciplinary Research, vol. 4, no. 3, pp. 16–23, Jun. 2024. doi: 10.5281/zenodo.12666921. (National Journal)
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  • Journal | Published On : 03-06-2024
    P. Changkakati, A. S. Ramana, A. U. Nayak, P. Sinha and S. Roopashree
    P. Changkakati, A. S. Ramana, A. U. Nayak, P. Sinha and S. Roopashree, “Trans Lingua: Unlocking Language Barriers,” Indiana Journal of Multidisciplinary Research, vol. 4, no. 3, pp. 31–35, Jun. 2024. doi: 10.5281/zenodo.12667108. (National Journal)
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  • Journal | Published On : 01-03-2024
    S. T. Ahmed, V. K. Venkatesan, T. R. Mahesh, S. Roopashree and M. Venkatesan
    S. T. Ahmed, V. K. Venkatesan, T. R. Mahesh, S. Roopashree and M. Venkatesan, ”Augmented Intelligence Based COVID-19 Diagnostics and Deep Feature Categorization Based on Federated Learning,” IEEE Transactions on Emerging Topics in Computational Intelligence, pp. 1–8, Mar. 2024. doi: https://doi.org/10.1109/tetci.2024.3375455. (IEEE, Indexed in WOS SCIE-Q1 Journal)
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  • Journal | Published On : 01-02-2024
    S. Roopashree, J. Anitha, S. Challa, T. R. Mahesh, V. K. Venkatesan and S. Guluwadi
    S. Roopashree, J. Anitha, S. Challa, T. R. Mahesh, V. K. Venkatesan and S. Guluwadi, “Mapping of soil suitability for medicinal plants using machine learning methods,” Scientific Reports, vol. 14, no. 1, p. 3741, Feb. 2024. doi: https://doi.org/10.1038/s41598-024-54465-3. (Springer Nature, Indexed in WOS-SCIE-Q1 Journal)
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  • Conference | Published On : 29-08-2023
    S. Muskan, S. Roopashree, B. Abhina, G. Jagruthi, and S. Challa
    S. Muskan, S. Roopashree, B. Abhina, G. Jagruthi, and S. Challa, ”An Early Recommendation Tool to Enhance Medicinal Plant Growth based on GIS and Soil Data,” in 2023 International Conference on Computer, Electronics & Electrical Engineering & their Applications (IC2E3), NIT Uttarakhand, India, pp. 1–6, 2023, doi: 10.1109/IC2E357697.2023.10262541. (Indexed in Scopus)
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  • Journal | Published On : 01-02-2023
    K. A. Sharada, K. Sushma, V. Muthukumaran, T. R. Mahesh, B. Swapna and S. Roopashree
    K. A. Sharada, K. Sushma, V. Muthukumaran, T. R. Mahesh, B. Swapna and S. Roopashree, “High ECGDiagnosis Rate Using Novel Machine Learning Techniques with Distributed Arithmetic (DA) Based Gated Recurrent Units,” Microprocessors and Microsystems, p. 104796, Feb. 2023. doi: https://doi.org/10.1016/j.micpro.2023.104796.(Elsevier, Indexed in WOS-SCIE Q2 Journal)
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  • Journal | Published On : 01-09-2022
    Bhargavi Mokashi, V. S. Bhat, Jagadeesh Pujari, S. Roopashree, T. R. Mahesh and D. Alex
    Bhargavi Mokashi, V. S. Bhat, Jagadeesh Pujari, S. Roopashree, T. R. Mahesh and D. Alex, “Efficient Hybrid Blind Watermarking in DWT-DCT-SVD with Dual Biometric Features for Images,” Contrast Media & Molecular Imaging, vol. 2022, pp. 1–14, Sep. 2022. doi: https://doi.org/10.1155/2022/2918126. (MDPI, Indexed in WOS-SCIE-Q2 Journal)
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  • Journal | Published On : 01-08-2022
    S. Roopashree, J. Anitha, T. R. Mahesh, V. Vinoth Kumar, W. Viriyasitavat and A. Kaur
    S. Roopashree, J. Anitha, T. R. Mahesh, V. Vinoth Kumar, W. Viriyasitavat and A. Kaur, “An IoT based authentication system for therapeutic herbs measured by local descriptors using machine learning approach,” Measurement, vol. 200, p. 111484, Aug. 2022. doi: https://doi.org/10.1016/j.measurement.2022.111484. (Springer, Indexed in WOS-SCIE-Q1 Journal)
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  • Journal | Published On : 01-04-2022
    S. Roopashree, J. Anitha, V. Sathiyamoorthi, B. Arunadevi, S. Ashutosh, G. Sachin and K. Manoj
    S. Roopashree, J. Anitha, V. Sathiyamoorthi, B. Arunadevi, S. Ashutosh, G. Sachin and K. Manoj, “An IoT and Machine Learning Based Intelligent System for the Classification of Therapeutic Plants,” Neural Processing Letters, vol. 54, no. 5, pp. 4465–4493, Apr. 2022. doi: https://doi.org/10.1007/s11063-022-10818-5. (Springer, Indexed in WOS-SCIE-Q2 Journal)
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  • Conference | Published On : 01-02-2022
    S. R. Kuthyar, S. Roopashree, Rasika, V, M. Sahana, G. Ritu, A. Rahul Davis and S. Priyadarshini
    S. R. Kuthyar, S. Roopashree, Rasika, V, M. Sahana, G. Ritu, A. Rahul Davis and S. Priyadarshini, ”An intelligent pothole detection and alerting system using mobile sensors and deep learning,” in 2021 IEEE 18th India Council International Conference (INDICON), IIT Guwahati, India, pp. 1–6, 2021, doi: 10.1109/INDICON52576.2021.9691661. (Indexed in Scopus)
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  • Journal | Published On : 01-09-2021
    S. Roopashree and J. Anitha
    S. Roopashree and J. Anitha, “DeepHerb: A Vision Based System for Medicinal Plants Using Xception Features,” IEEE Access, vol. 9, pp. 135927–135941, Sep. 2021. doi: https://doi.org/10.1109/access.2021.3116207. (IEEE, Indexed in WOS-SCIE-Q1 Journal)
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  • Book Chapter or Books | Published On : 01-09-2021
    S. Roopashree, J. Anitha, and P. Madhumathy
    S. Roopashree, J. Anitha, and P. Madhumathy, ”Machine learning approach: Enriching the knowledge of Ayurveda from Indian medicinal herbs,” in Research Anthology on Recent Advancements in Ethnopharmacology and Nutraceuticals, Eds. Information Resources Management Association, IGI Global, 2021, pp. 349–366, https://doi.org/10.4018/978-1-6684-3546-5.ch018. (Indexed in Scopus)
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  • Journal | Published On : 01-12-2020
    S. Roopashree and J. Anitha
    S. Roopashree and J. Anitha, ”Enrich Ayurveda knowledge using machine learning techniques,” Indian Journal of Traditional Knowledge (IJTK), vol. 19, pp. 813-820, NISCAIR-CSIR, Dec. 2020. (Indexed in WOS-SCIE-Q2 Journal)
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Other Information

IEEE Senior Member and Life Member of the Computer Society of India

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