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Barath Narayanan

Senior Research Scientist & Adjunct Professor

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

Contact

Email: Barath Narayanan
Phone: 937-229-4951
1700 S. Patterson Boulevard, Dayton, OH 45409
Website: Visit Site

Profile

Dr. Barath Narayanan currently holds a joint appointment as a Senior Research Scientist in UDRI’s Sensor and Software Systems group and as an adjunct professor for the Electrical and Computer Engineering department at UD. Dr. Narayanan has 7+ years of experience in the field of computer vision, machine learning, data analytics and natural language processing. He has integrated his deep learning and data science algorithms for various applications that include manufacturing, medical imaging, environmental monitoring, cybersecurity, predictive analytics and aerospace industry. Dr. Narayanan has over 7 years of experience in teaching Control Systems, MATLAB programming, and Machine Learning and Deep Learning courses. He holds a patent and has published over 11 journals and 25 conference papers in the field of machine learning.

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.Tech., Electrical and Electronics Engineering, SRM University, India, 2012

Honors

  • 2023 UDRI Wohlleben-Hochwalt Outstanding Researcher Award
  • 2023 IEEE Ravi Pallerla Memorial Award for Young Professionals
  • 2021 IEEE Fritz J.Russ Bio-Engineering Award
  • 2020 UDRI Exceptional Performance Award
  • IEEE Senior Member
  • Conference chair for IEEE and SPIE hosted conferences

Student Awards

  • IEEE Krishna M. Pasala Memorial Scholarship: 2015
  • Graduate Student Summer Fellowship: 2012, 2015, and 2017
  • SRM University Merit Scholarship, 2008-2012

Patents

  1. Narayanan, Barath, Russell Hardie, Vignesh Krishnaraja, and Srikanth Kodeboyina. “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.

Selected Journals

  1. Hardie, R. C., Trout, A. T., Dillman, J. R., Narayanan, B. N., & Tanimoto, A. A., “Performance Analysis in Children of Traditional and Deep-Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults”. American Journal of Roentgenology (2023).
  2. De Silva, M. S., Narayanan, B.N, Hardie, R.C, “A Patient-Specific Algorithm for Lung Segmentation in Chest Radiographs,” AI 2022, 3(4), 931-947.
  3. 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.
  4. 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.
  5. 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.
  6. Narayanan, B.N., Davuluru, V.S.P. “Ensemble Malware Classification System using Deep Neural Networks”. Electronics 2020, 9(5), 721.
  7. 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.
  8. 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.
  9. 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.
  10. 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.

Selected Conference Papers

  1. B. N. Narayanan, Manawaduge Supun De Silva, R. C. Hardie. “A Patient Specific Algorithm for Plasmodium Malaria Detection on Cell Images”, 2023 IEEE National Aerospace and Electronics Conference (pp. 258-262).
  2. Joseph Ivarson, Lars Maneck, B. N. Narayanan, Sidaard Gunasekaran , “Deep Learning Algorithm for Atomization Characterization using Shadowgraph Images”, AIAA 2022-0188. AIAA SCITECH 2022 Forum. January 2022
  3. B. N. Narayanan, Manawaduge Supun De Silva, R. C. Hardie, Redha Ali, “Ensemble Method of Lung Segmentation in Chest Radiographs”, 2021 IEEE National Aerospace and Electronics Conference (pp. 382-385).
  4. 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 (pp. 74-79).
  5. Narayanan, B.N,Transfer-to-Transfer Learning Approach for Computer Aided Detection of COVID-19 in Chest Radiographs,” NVIDIA GTC Conference 2021
  6. Barnhart, S. A., Narayanan, B.N, & Gunasekaran, S. (2021), “Blown Wing Aerodynamic Coefficient Predictions Using Traditional Machine Learning and Data Science Approaches”, AIAA 0021-0616, AIAA SCITECH 2021 Forum, January 2021.
  7. B.N. Narayanan, K. Beigh, S. Duning, and E. Dathan, “Material identification and segmentation using deep learning for laser powder bed fusion”, Proc. SPIE 11511, Applications of Machine Learning 2020, 115110P, August 2020. 
  8. D. Flaute, B.N. Narayanan, “Video captioning using weakly supervised convolutional neural networks”, Proc. SPIE 11511, Applications of Machine Learning 2020, 11511006, August 2020. 
  9. 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. 
  10. B.N. Narayanan, R.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 2019, 111390W, September 2019.
  11. 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 2019, 11139013, September 2019.