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Barath Narayanan

Research Scientist / Adjunct Faculty

School of Engineering: Department of Electrical and Computer Engineering; University of Dayton Research Institute: Sensor and Software Systems

Contact

Email: Barath Narayanan
Phone: 937-396-2783
Website: Visit Site
1700 S. Patterson Boulevard, Dayton, OH 45409

Profile

Dr. Barath Narayanan holds a Joint Appointment as a Research Scientist in UDRI's Software Systems Group and as an Adjunct Faculty for the Electrical and Computer Engineering (ECE) department at UD. Dr. Narayanan develops machine learning and deep learning algorithms for applications in computer vision and data analytics for commercial entities. He graduated with M.S. and Ph.D. degrees in Electrical Engineering from UD in 2013 and 2017 respectively. He also graduated with distinction from SRM University, Chennai, India in 2012 with a Bachelor’s degree in Electrical and Electronics Engineering. He has developed machine learning and deep learning algorithms for various medical imaging applications that includes the detection of Lung Cancer, Breast Cancer, Pneumonia, Tuberculosis, Malaria, Skin Cancer, Brain Tumor, Diabetic Retinopathy and COVID-19.

Research

Dr. Narayanan's research includes work in the following areas:

Education

  • Ph.D (Electrical Engineering), University of Dayton, 2017
  • M.S. (Electrical Engineering), University of Dayton, 2013
  • B.T. (Electrical and Electronics Engineering), SRM University, India, 2012

Honors

  • IEEE Krishna M. Pasala, Ph.D. Memorial Scholarship, 2015
  • Graduate Summer Fellowship, 2012, 2015 & 2017
  • University of Dayton International Scholarship, 2011-2013
  • SRM University Merit Scholarship, 2008-2012
  • Treasurer & Secretary of Society of Asian Scientists & Engineers for University of Dayton chapter – Ranked no. 2 among 65 competitive other chapters for SASE Inspire Awards, 2015

Selected Publications

Journals

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 Society167(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 Applications22(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 Imaging5(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 Processing2014(1), 55.

Past Conferences

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. NarayananR.C. Hardie, and R.A. Ali. “Performance Analysis of Machine Learning and Deep Learning Architectures for Malaria Detection on Cell ImagesProc. 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 imagesProc. 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 DiagnosisMedical 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.