Mrs. Aswathy M. A.
NAME : Mrs. Aswathy M. A.
DESIGNATION : Assistant Professor
QUALIFICATION : B.Tech, M.Tech, (PhD).
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PhD.- Vellore Institute of Technology, Chennai (Thesis Submitted)
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M.Tech. in Electronics & Communication Engineering, K.S.R. College of Technology, Tamil Nadu, India
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B.Tech. in Electronics & Communication Engineering, Vidya Academy of Science and Technology, Kerala, India
OVERVIEW OF PROFILE
Mrs. M.A. Aswathy is an Assistant Professor in the School of Electrical Engineering at MIT Academy of Engineering, Pune, India. Currently, she has submitted her thesis at Vellore Institute of Technology (VIT) Chennai, Tamil Nadu, India. She has received her B.Tech. degree in Electronics and Communication Engineering from Vidya Academy of Science and Technology, Kerala, India and M.E. degree in Applied Electronics from K.S.R. College of Technology, Tamil Nadu, India, in 2011 and 2013 respectively. She has both teaching and industrial experience. She worked in Infoplus Technologies, Chennai as Content Manager for 1 year. She has been with the Department of Electronics Engineering as Assistant Professor at SETCEM, Kerala, India in the year of 2013. Her fields of interest are biomedical engineering, AI in healthcare, computer vision, edge computing, teaching and learning in engineering education and data science
FORE FRONT AREA OF RESEARCH : Signal & Image Processing
EMAIL ID : ammu.dev8@gmail.com
CONTACT NO : 020 30253506 Ext:
EXPERIENCE : Teaching: 2 Years, Industry and Research: 2 years
- Aswathy M A is selected as the winner of the Impact Innovator Award under the Innovation Awards category during the Future Tech Summit’24, at the AI Research Centre, Woxsen University, Hyderabad.
- Aswathy M A is selected as Best Teacher Award in the department of SEE for 2023-2024 AY.
- Aswathy M A is awarded the best case study presentation under the outcome based education category during the Faculty Conclave 2024 conducted by MITAOE.
PATENTS(Granted/Published): 5 (3 Indian and 2 International)
- Solar-Powered AI-Driven Robot for Precision Farming, UK Design Registration No. 6424472, granted on 17/03/2025.
- An Indian Design patent has been granted by the Indian patent office for a patent application titled "Portable Gas Chamber for Alcohol Detection". The patent granted on January 5 2024.
- An Indian utility patent titled “Raspberry Pi based real-time cancer detection device using deep learning technique” granted on dated 21/03/2024 (File No. 202041040783).
- An Indian utility patent titled “Method and Apparatus for Rapid Low Cost COVID-19 detection from Exhaled breath” published on 11/08/2023 (File No. 202321038326).
- A South African design patent titled” System, Method and Device for Non-Invasively Identifying Chronic Kidney Diseases from Saliva of a User” filed on 14/4/2023 (File No. 2023/04407) and granted on 29 November 2023.
PUBLICATIONS
RESEARCH PUBLICATIONS
- Aswathy, M.A. Jagannath, M. 2016, ‘Detection of breast cancer on digital histopathology images: present status and future possibilities.’, Informatics in Medicine Unlocked 8, 74–79. (Scopus, Publisher: Elsevier)
- Aswathy, M.A. Jagannath, M. 2020, ‘Dual stage normalization approach towards classification of breast cancer.’, IETE Journal of Research 68, 3074–3085. (Scopus, Publisher: Taylor and Francis, IF: 1.877)
- Aswathy, M.A. Jagannath, M. 2020, ‘Performance analysis of segmentation algorithms for the detection of breast cancer.’, Procedia in Computer Science 59, 666–667. (Scopus, Publisher: Elsevier)
- Aswathy, M.A. Jagannath, M. 2021, ‘An SVM approach towards breast cancer classification from HandE- stained histopathology images based on integrated features.’, Medical and Biological Engineering and Computing 167, 1773–1783. (Scopus, Publisher: Springer Nature, Impact Factor: 3.079)
- M Jagannath, C Madan Mohan, Aswin Kumar, MA Aswathy, N Nathiya. 2020, “Design and testing of a spirometer for pulmonary functional analysis”, International Journal of Innovative Technology and Exploring Engineering 8, 343-347 (Scopus)
- Tupe-Waghmare, P., Bhaskar, N., & Aswathy, M. A. (2024). An efficient convolutional neural network-extreme gradient boosting hybrid deep learning model for disease detection applications. International Journal of Electrical & Computer Engineering, 14(2), 2088-8708.
- Bherje, A., Jidge, A., Roy, C., Hulke, A., Aswathy, M. A., Yadav, V., & Veenamol, K. V. (2024). Design of deep learning-based approach to predict lung cancer on CT scan images, in 2024 5th International Conference on Innovative Trends in Information Technology (ICITIIT) (pp. 1-5). IEEE.
- Aswathy, M.A. Jagannath, M. (2019),” Performance Analysis of Segmentation Algorithms for the Detection of Breast Cancer”, in Proceedings of International Conference on Computational Intelligence and Data Science, Gurugram, India.
- Aswathy M A, Santha S, Jayanthi K B, “Analysis of Performance of various algorithms for the segmentation of carotid artery” in the IEEE EMBS International Conference held in 2013 Jan. at Sheraton Hotel, Bangalore.
- Aswathy, M.A. and Jagannath, M. (2020),” Analysis of Machine Learning Algorithms for Breast Cancer Detection”, In. Sathiyamoorthi Velayutham (Eds), Handbook of Research on Applications and Implementations of Machine Learning Techniques, IGI Global, India, pp. 1-20.
- Aswathy, M.A. Jagannath, M. (2023),” Machine Learning Algorithms for Breast Cancer Detection.” Research Anthology on Medical Informatics in Breast and Cervical Cancer, edited by Information Resources Management Association, IGI Global, pp. 309-329.
- Sontakke, R., Shinde, P., Avhad, V., Kadam, Y., Yadav, V., & Aswathy, M. A. (2024). Web-based framework for the prediction of Type 1 diabetes in youth using EHR's data. In Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2024, Volume 2 (p. 445). Springer Nature.
- Sawant, P., Bokefode, S., Deshmukh, S., Yadav, V. P., & Aswathy, M. A. (2024). Real-time AI-based face-mask detection. In U. Nanda et al. (Eds.), Advances in distributed computing and machine learning, Lecture notes in networks and systems, Volume 1015 (Vol. 2, pp. 85-97). Springer.