Faculty Profile

About

Dr. Roopashree S, currently working as an Associate Professor in the 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 grant of one Indian utility patent, publication of three Indian patents, the grant of a German Utility Patent, and a few design patents. As a Senior Member of IEEE and a lifetime member of the Computer Society of India, Dr. Roopashree has made significant contributions to both research and academia. She has published over 40 papers in peer-reviewed international journals, including those indexed in Web of Science and SCIE Q1 and Q2 categories, authored one textbook, and three book chapters. In addition, she is an active reviewer for leading SCIE journals. Her achievements include working as an R&D consultant for start-ups, receiving KSCST sponsorship for three projects, and securing first place 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

• Book Chapter or Books | Published On : 05-08-2026
  Dhakshayani, J., Shashidhar, R. and Roopashree, S.
  NextGen Strategies and Tools: Pioneering Innovations in Agriculture is a systematic, application-oriented examination of next-generation strategies and technologies that drive innovation in agriculture. The book focuses on integrating Artificial Intelligence (AI), Internet of Things (IoT), deep learning, robotics, and smart sensing technologies to address challenges in sustainability, precision farming, and agricultural productivity. The book presents information on AI-based decision support frameworks, IoT-enabled precision agriculture, smart sensor networks for crop monitoring, and vision-based systems for disease and pest detection. Contributions explore deep learning and computer vision models applied to real-world agricultural scenarios, emphasizing scalability, accuracy, and deployment feasibility in both large-scale and resource-constrained environments. Practical implementations such as Agrobots, Raspberry Pi-based agricultural platforms, and automated fertilizer dispensing systems further demonstrate the applicability of the proposed methods. In addition to technological advancements, the book examines the sustainability and environmental implications of adopting AI and IoT in agriculture. Key considerations such as efficient resource utilization, climate resilience, and environmentally responsible farming practices are discussed to provide a balanced and holistic perspective. By bridging theoretical foundations with practical deployment, the book supports the development of intelligent agricultural ecosystems. As part of the NextGen Agriculture: Novel Concepts and Innovative Strategies series, this book is intended for postgraduate students, researchers, academicians, and professionals in computer science, AI, data science, electronics and communication engineering, agricultural engineering, and smart farming technologies. It also serves as a reference for policymakers and practitioners seeking to advance sustainable and intelligent agricultural systems.
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• Patents | Published On : 03-06-2026
  Roopashree S et.al.
  Patent No. : 591058 Application No. : 202141056007 Date of Filing: 02/12/2021 Patentee: 1. Roopashree S 2. Shubhra Rao Kuthyar 3. Rasika V 4. Sahana M Patent Title: An Intelligent Pothole Detection and Alerting System using Mobile Sensors and Deep Learning It is hereby certified that a patent has been granted to the patentee for an invention entitled An Intelligent Pothole Detection and Alerting System using Mobile Sensors and Deep Learning as disclosed in the above mentioned application for the term of 20 years from the 2nd day of December 2021 in accordance with the provisions of the Patents Act,1970.
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• 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. Active participation in industry-oriented consultancy projects.

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