Barath Narayanan

Barath Narayanan graduated with MS and Ph.D. degree in Electrical Engineering from University of Dayton (UD) in 2013 and 2017 respectively. He currently holds a joint appointment as a Research Scientist at UDRI's Software Systems Group and as an Adjunct Faculty for the ECE department at UD. He graduated with distinction from SRM University, Chennai, India in 2012 with a Bachelor’s degree in Electrical and Electronics Engineering. His research interests include deep learning, machine learning, computer vision, and pattern recognition.

Patents

Narayanan, B.N, Hardie, R.C, Krishnaraja, V, Kodeboyina, S. “Systems and methods for transfer-to-transfer learning-based training of a machine learning model for detecting medical conditions,” U.S. Patent 11,087,883, issued August 10, 2021.

Journal

Redha Ali, Hardie, R.C, Narayanan, B.N, & Kebede, T. M., “IMNets: Deep Learning Using an Incremental Modular Network Synthesis Approach for Medical Imaging Applications,” Applied Science 2022, 12 (11), 5500.
Narayanan, B.N, Hardie, R.C, Krishnaraja, V, Karam, C, Davuluru, V.S.P. “Transfer-to-Transfer Learning Approach for Computer Aided Detection of COVID-19 in Chest Radiographs,” AI 2020, 1(4), 539-557.
Narayanan, B.N, Hardie, R.C., De Silva, M. S., Kueterman, N. K. (2020), “Hybrid machine learning architecture for automated detection and grading of retinal images for diabetic retinopathy,” Journal of Medical Imaging, 7(3), 034501.
Narayanan, B. N., Davuluru, V. S. P. (2020). “Ensemble Malware Classification System using Deep Neural Networks”, Electronics, 2020, 9 (5), 721.
Namuduri, S., Narayanan, B. N., Davuluru, V. S. P., Burton, L., & Bhansali, S. (2020). “Deep Learning Methods for Sensor Based Predictive Maintenance and Future Perspectives for Electrochemical Sensors”. Journal of The Electrochemical Society, 167(3), 037552.
Narayanan, B. N., De Silva, M. S., Hardie, R. C., Kueterman, N. K., & Ali, R. (2019). “Understanding Deep Neural Network Predictions for Medical Imaging Applications”. arXiv preprint arXiv:1912.09621.
Narayanan, B. N., Hardie, R. C., Kebede, T. M., & Sprague, M. J. (2019). “Optimized feature selection-based clustering approach for computer-aided detection of lung nodules in different modalities”. Pattern Analysis and Applications, 22(2), 559-571.
Narayanan, B. N., Hardie, R. C., & Kebede, T. M. (2018). “Performance analysis of a computer-aided detection system for lung nodules in CT at different slice thicknesses”. Journal of Medical Imaging, 5(1), 014504.
Narayanan, B. N., Hardie, R. C., & Balster, E. J. (2014). “Multiframe adaptive Wiener filter super-resolution with JPEG2000-compressed images”. EURASIP journal on Advances in Signal Processing, 2014(1), 55.

Conferences

Joseph Ivarson, Lars Maneck, B. N. Narayanan, Sidaard Gunasekaran, “AgSpray Atomization Characterization using Deep Learning”, AIAA 2022-0188. AIAA SCITECH 2022 Forum. January 2022.
B. N. Narayanan, Manawduge Supun De Silva, R. C. Hardie, Redha Ali, “Ensemble Method of Lung Segmentation in Chest Radiographs”, 2021 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2021,pp. 382-385.
B. N. Narayanan, Joseph Ivarson, Lars Maneck, Sidaard Gunasekaran , “Deep Learning Algorithm for Atomization Characterization using Shadowgraph Images”, 2021 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2021,pp. 74-79.
Narayanan, B.N, "Transfer-to-Transfer Learning Approach for Computer Aided Detection of COVID-19 in Chest Radiographs", NVIDIA GTC Conference 2021
Barnhart, S. A., Narayanan, B.N, & Gunasekaran, S. (2021), “Blown Wing Aerodynamic Coefficient Predictions Using Traditional Machine Learning and Data Science Approaches” In AIAA Scitech 2021 Forum (p. 0616).
B.N. Narayanan, K.Beigh ,S.Duning and E. Dathan, “Automated Material identification and segmentation using deep learning for laser powder bed fusion”, Proc. SPIE 11511, Applications of Machine Learning 2020, 115110P, August 2020.
D. Flaute, B.N. Narayanan, “Video captioning using weakly supervised convolutional neural networks”, Proc. SPIE 11511, Applications of Machine Learning 2020, 11511006, August 2020.
B.N. Narayanan, V.S.P. Davuluru, and R.C. Hardie. “Two-Stage Deep Learning Architecture for Pneumonia Detection and its Diagnosis in Chest Radiographs”, Proc. SPIE 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 113180G, March 2020.
B.N. Narayanan, R.C. Hardie, and R.A. Ali. “Performance Analysis of Machine Learning and Deep Learning Architectures for Malaria Detection on Cell Images”, Proc. SPIE 11139, Applications of Machine Learning, 111390W, September 2019.
B.N. Narayanan, K.Beigh ,G. Loughnane and N.Powar, “Support Vector Machine and Convolutional Neural Network Based Approaches for Defect Detection in Fused Filament Fabrication”, Proc. SPIE 11139, Applications of Machine Learning, 11139013, September 2019.
Srikanth Namuduri, B.N. Narayanan, Mahsa Karbaschi, Marcus Cooke and Shekhar Bhansali, “Automated quantification of DNA damage via deep transfer learning based analysis of comet assay images”, Proc. SPIE 11139, Applications of Machine Learning, 11139013, September 2019.
B. N. Narayanan and R. C. Hardie, “A Computationally Efficient U-Net Architecture for Lung Segmentation in Chest Radiographs,” 2019 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2019, pp. 279-284.
V. S. P. Davuluru, B.N. Narayanan and E. J. Balster, “Convolutional Neural Networks as Classification Tools and Feature Extractors for Distinguishing Malware Programs,” 2019 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2019, pp. 273-278.
R. Ali, R. C. Hardie, B. N. Narayanan and S. De Silva, “Deep Learning Ensemble Methods for Skin Lesion Analysis towards Melanoma Detection,” 2019 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2019, pp. 311-316.
B. N. Narayanan, V. Krishnaraja and R. Ali, “Convolutional Neural Network for Classification of Histopathology Images for Breast Cancer Detection”, 2019 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2019, pp. 291-295.
B. N. Narayanan, R. C. Hardie and T. M. Kebede, “Performance Analysis of Feature Selection Techniques for Support Vector Machine and its Application for Lung Nodule Detection,” NAECON 2018 - IEEE National Aerospace and Electronics Conference, Dayton, OH, 2018, pp. 262-266.
T. Messay-Kebede, B. N. Narayanan and O. Djaneye-Boundjou, “Combination of Traditional and Deep Learning based Architectures to Overcome Class Imbalance and its Application to Malware Classification,” NAECON 2018 - IEEE National Aerospace and Electronics Conference, Dayton, OH, 2018, pp. 73-77
T. M. Kebede, O. Djaneye-Boundjou, B. N. Narayanan, A. Ralescu and D. Kapp, “Classification of Malware programs using autoencoders based deep learning architecture and its application to the microsoft malware Classification challenge (BIG 2015) dataset,” 2017 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, 2017, pp. 70-75.
B. N. Narayanan, R. C. Hardie, and T.M. Kebede, “Feature Selection using Linear Classifier for Computer Aided Detection of Pulmonary Nodules in CT”, International Conference on Medical Imaging and Diagnosis, Medical Imaging 2016, Chicago, Illinois, October 20-21, 2016. Presentation Date: October 2016
B. N. Narayanan, O. Djaneye-Boundjou and T. M. Kebede, “Performance analysis of machine learning and pattern recognition algorithms for Malware classification,” 2016 IEEE National Aerospace and Electronics Conference (NAECON) and Ohio Innovation Summit (OIS), Dayton, OH, 2016, pp. 338-342.
B. N. Narayanan, R. C. Hardie and T. M. Kebede, “Analysis of various classification techniques for computer aided detection system of pulmonary nodules in CT,” 2016 IEEE National Aerospace and Electronics Conference (NAECON) and Ohio Innovation Summit (OIS), Dayton, OH, 2016, pp. 88-93.
B. N. Narayanan and R. C. Hardie, “Multiframe super resolution with JPEG2000 compressed images,” 2015 National Aerospace and Electronics Conference (NAECON), Dayton, OH, 2015, pp. 15-18.

Courses Taught:

Applications of Machine Learning and Deep Learning (Master's and Ph.D.)
Introduction to MATLAB Programming (Undergraduate)
Control Systems (Undergraduate)
Signals and Systems (Undergraduate)

Blogs:

Awards:

2021 IEEE Fritz J. Russ Bio-Engineering Award
UDRI Exceptional Performance Award for the Year 2020
Graduate Student Summer Fellowship 2012, 2015, and 2017
IEEE Krishna M. Pasala Memorial Scholarship 2015
University of Dayton International Scholarship 2011-2013
SRM University Merit Scholarship 2008-2012

Demos: