Faculty & Staff
Contact
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Email
nayanabr.cs.et@msruas.ac.in
- Phone
- Websites
Dr. Nayana B R
Associate Professor
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School/College
Faculty of Engineering and Technology
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Department
Department of Computer Science and Engineering
Passionate teacher and researcher with expertise in Machine Learning and Signal Processing domain like Pattern Recognition, Statistical Signal Processing, Biomedical Signal Processing, Detection and Estimation, Modern Spectral Analysis, Audio Signal Processing, Data Compression, Computer Vision, Advanced Medical Image Processing, Deep Learning.
- Demonstrated a novel methodology to extract frequency domain features directly from time domain evolutionary algorithms for feature selection
- Developed and demonstrated several mini projects on signal processing
- Demonstrated implementation of two different inverse intersetellar model on pulsar data for de-dispersion at Raman Research Institute
Qualifications
- Ph.D., Machine Learning and Computational Intelligence Application
Vellore Institute of Technology (VIT, Vellore), 2019 April
- M.Tech, Signal Processing
S.J.C Institute of Technology (VTU), 2012 June
- B.E., Electrical and Electronics Engineering
Nitte Meenakshi Institute of Technology (VTU), 2010 June
Experience
Total Years of Experience12 Years
Academic Experience
- Sir M Visvesvaraya Institute of Technology, Bangalore. 9 years 9 months
- Associate Professor : June 2019-October 2022
- Assistant Professor : April 2013-May 2019
- Lecturer : Jan 2013-March 2013
- Bangalore Technological Institute, 6months.
- Lecturer Aug 2012-Dec 2012
Industry Experience
- Raman Research Institute, Bangalore, 1year
- Research Intern (Visiting Student Program) March 2011-April 2012
Training Experience
- J2EE-1 from APTECH Education Center
- Attained NPTEL certifications Medical Image Processing, Introduction to Machine Learning, Computer Vision, Introduction to Artificial Intelligence, Artificial Intelligence : search methods for problem solving, Deep Learning, Biomedical Signal Processing
- Attended ATAL FDP on “AI in Biomedical Engineering”
- Signal Processing, Machine Learning, Computational Intelligence
- 1st prize for paper presentation of “Detection of Pulsars at ultra-high time resolution” at KSHTHIJA-2012 National Level Symposium
- Best paper award for the paper entitled “Comparison of Digital Signal Processing Algorithms for Radio Pulsar Data De-Dispersion at Higher Time Resolutions” in International Conference on ATRPD
- "NPTEL Star" - "NPTEL BELIEVERS"
- "NPTEL Star" - "NPTEL ENTHUSIASTS"
- "NPTEL Star" - "NPTEL DISCIPLINE STARS"
National Conference Papers
- Comparison of Digital Signal Processing Algorithms for Radio Pulsar Data De-Dispersion at Higher Time Resolutions International Conference on ATRPD
- Study of Pulsars at ultra-high time resolution National Conference ICON-RF 2012
- Detection and study of Pulsars at ultra-high time resolution National Conference on “Signal Processing & Communication”
International Conference Papers
- Nayana. BR and P. Geethanjali, "Feature Extraction for Bearing Fault Diagnosis in Noisy Environment: A Study," 2019 Innovations in Power and Advanced Computing Technologies (i-PACT), Vellore, India, 2019, pp. 1-5, doi: 10.1109/i-PACT44901.2019.8960103.
- B. R. Nayana and P. Geethanjali, "Study of Effective Feature Combination for Fault Diagnosis of Bearings in Motors," 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), Thoothukudi, India, 2020, pp. 1541-1546, doi: 10.1109/ICISS49785.2020.9316038.
- B. R. Nayana and P. Geethanjali, "A low-cost laboratory based research platform for mechanical faults diagnosis of Induction Motor using FFT," 2017 Innovations in Power and Advanced Computing Technologies (i-PACT), Vellore, India, 2017, pp. 1-5, doi: 10.1109/IPACT.2017.8245028.
- Nayana B R et al "Hybrid Machine Learning Model Using Particle Swarm Optimization for Effectual Diagnosis of Alzheimer's Disease from Handwriting," 2022 4th International Conference on Circuits, Control, Communication and Computing (I4C), Bangalore, India, 2022, pp. 491-495, doi: 10.1109/I4C57141.2022.10057948.
- Subha, R., Radhakrishnan, R., Sumalatha, P., Nayana, B.R. (2023). Identification and Validation of Prominent Features for Predicting Mortality in Heart Patients with Left Ventricular Dysfunction Using Machine Learning. In: Namrata, K., Priyadarshi, N., Bansal, R.C., Kumar, J. (eds) Smart Energy and Advancement in Power Technologies. Lecture Notes in Electrical Engineering, vol 927. Springer, Singapore. https://doi.org/10.1007/978-981-19-4975-3_26
- Nayana. B R and G. P, "A Study on Pattern Analysis of Extracted Features from Bearing Fault Vibration Signals," 2021 Innovations in Power and Advanced Computing Technologies (i-PACT), Kuala Lumpur, Malaysia, 2021, pp. 1-6, doi: 10.1109/i-PACT52855.2021.9696973.
International Journal Papers
- B. R. Nayana and P. Geethanjali, "Analysis of Statistical Time-Domain Features Effectiveness in Identification of Bearing Faults From Vibration Signal," in IEEE Sensors Journal, vol. 17, no. 17, pp. 5618-5625, 1 Sept.1, 2017, doi: 10.1109/JSEN.2017.2727638.
- B. R. Nayana and P. Geethanjali, "Improved Identification of Various Conditions of Induction Motor Bearing Faults," in IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 5, pp. 1908-1919, May 2020, doi: 10.1109/TIM.2019.2917981.
- Nayana B R and Geethanjali P 2018 Effective time domain features for identification of bearing fault using LDA and NB classifiers Int. J. Mech. Product Eng. Res. Dev. 8 1135–50
- Nayana, B.R. and Geethanjali, P., 2018. Identification of bearing faults using statistical time domain features and fused time-domain descriptor features. J Advan Res Dynam Control Syst, 10(3).
- Severity Identification and multi-Fault Classification of Roller Bearings, volume 119, issue 14, pages 221-229 2018
- ISTE
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