Poonguzhali Elangovan

Email: epoonguzhali3@gmail.com

Mob: +91-9940204050

Personal Information:

Nationality: Indian

Permanent Address: Dr. E. Poonguzhali,

                                  D/o Mr. R. Elangovan,

                                  No.17, Vettaikaran Street,,

                                  Kovilpathu, Karaikal, PIN-609605

Educational Qualifications:

Ph.D. (2022), Electronics and Communication Engineering

National Institute of Technology Puducherry, Karaikal, India

MTech (2004), Power Electronics and Drives

Government College of Technology, Coimbatore, Tamilnadu,India

BE (2002), Electronics and Communication Engineering

Institute of Road and Transport Technology, Erode, Tamilnadu, India

HSC (1998), (Physics-Chemistry-Mathematics-Biology)

Board of Higher Secondary Education Tamilnadu, India.

SSLC (1996)

Board of Secondary Education Tamilnadu, India

Research Details:

1. Google Scholar: https://scholar.google.com/citations?hl=en&user=3K447EkAAAAJ 

2. Orchid ID: https://orcid.org/0000-0001-9628-7090 

3. Web of Science Researcher ID: ABB-1694-2020

4. Scopus Author ID: 57210075002

5. IRINS (Govt. of India): 167680

6. Research gate: https://www.researchgate.net/profile/Poonguzhali_Elangovan2 

Area of Research: Medical Image Processing, Machine Learning

Area of Interest: Deep Learning

Publications:

Journals (Total Nos.: 21):

1. Avneet Kaur, Swathi Priya Cherukuri, Megha Shashidhar Handral, Hanisha Reddy Kukunoor, Rikesh KC, Swathi Godugu, Jieun Lee, Gayathri Yerrapragada, Poonguzhali Elangovan, Mohammed Naveed Shariff, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Jayavinamika Jayapradhaban Kala, Sancia Mary Jerold Wilson, Samuel Richard, Shiva Sankari Karuppiah, Dipankar Mitra, Vivek N. Iyer, Scott A. Helgeson, and Shivaram P. Arunachalam, “Artificial Intelligence Enabled Lung Sound Auscultation in the Early Diagnosis and Subtyping of Interstitial Lung Disease” Journal of Clinical Medicine, MDPI, vol. 14, no. 23, 8500, pp. 1-41, November 2025. (SCIE, IF-2.9) https://doi.org/10.3390/jcm14238500

2. Gayathri Yerrapragada, Jieun Lee, Mohammad Naveed Shariff, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Avneet Kaur, Divyanshi Sood, Swetha Rapolu, Jay Gohri, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari, Jahnavi Mikkilineni, Naghmeh Asadimanesh, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Shiva Sankari Karuppiah, Vivek N. Iyer, Scott A. Helgeson, Venkata S. Akshintala, and Shivaram P. Arunachalam, “A Novel Unsupervised You Only Listen Once (YOLO) Machine Learning Platform for Automatic Detection and Characterization of Prominent Bowel Sounds Towards Precision Medicine” , Bioengineering, MDPI, vol. 12, no. 11, 1271, pp. 1-15, November 2025. (SCIE, IF- 3.7) https://doi.org/10.3390/bioengineering12111271

3. Gianeshwaree Alias Rachna Panjwani, Srivarshini Maddukuri, Rabiah Aslam Ansari, Samiksha Jain, Manisha Chavan, Naga Sai Akhil Reddy Gogula, Gayathri Yerrapragada, Poonguzhali Elangovan, Mohammed Naveed Shariff, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Shiva Sankari Karrupiah, Keerthy Gopalakrishnan, Divyanshi Sood, Shivaram P Arunachalam, “Artificial Intelligence in Postmenopausal Health: From Risk Prediction to Holistic Care”, Journal of Clinical Medicine, MDPI, vol. 14, no. 21, 7651, pp. 1- 25, October 2025. (SCIE, IF-2.9) https://doi.org/10.3390/jcm14217651

4. Samiksha Jain, Avneet Kaur, Abdul Qadeer, Victor Ghosh, Shivani Thota, Mallareddy Banala, Jieun Lee, Gayathri Yerrapragada, Poonguzhali Elangovan, Mohammed Naveed Shariff, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Jayavinamika Jayapradhaban Kala, Samuel Richard, Saai Poornima Vommi, Shiva Sankari Karuppiah, Anjani Muthyala, Vivek N Iyer, Scott A Helgeson, Dipankar Mitra, Shivaram P Arunachalam, “Leveraging Artificial Intelligence for the Diagnosis of Systemic Sclerosis Associated Pulmonary Arterial Hypertension: Opportunities, Challenges, and Future Perspectives”, Advances in Respiratory Medicine, MDPI, vol. 93, no. 5, 47, pp. 1- 40, October 2025. (ESCI, IF-2.3) https://doi.org/10.3390/arm93050047

5. Divyanshi Sood, Zenab Muhammad Riaz, Jahnavi Mikkilineni, Narendra Nath Ravi, Vineeta Chidipothu, Gayathri Yerrapragada, Poonguzhali Elangovan, Mohammed Naveed Shariff, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Naghmeh Asadimanesh, Shiva Sankari Karuppiah, Keerthy Gopalakrishnan, Shivaram P Arunachalam, “Prospects of AI-Powered Bowel Sound Analytics for Diagnosis, Characterization, and Treatment Managemnet of Inflammatory Bowel Disease”, Medical Sciences, MDPI, vol. 13, no. 4, 230, pp. 1- 26, October 2025. (ESCI, IF-4.4) https://doi.org/10.3390/medsci13040230

6. Swathi Priya Cherukuri, Anmolpreet Kaur, Bipasha Goyal, Hanisha Reddy Kukunoor, Areesh Fatima Sahito, Pratyush Sachdeva, Gayathri Yerrapragada, Poonguzhali Elangovan, Mohammed Naveed Shariff, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Samuel Richard, Shakthidevi Pallikaranai Venkatesaprasath, Shiva Sankari Karuppiah, Vivek N Iyer, Scott A Helgeson, Shivaram P Arunachalam, “Artificial Intelligence-Enhanced Liquid Biopsy and Radiomics in Early-Stage Lung Cancer Detection: A Precision Oncology Paradigm”, Cancers, MDPI, vol. 17, no. 19, 3165, pp. 1- 31, September 2025. (SCIE, IF-4.4) https://doi.org/10.3390/cancers17193165

7. Ansari, Rabiah Aslam, Sidhartha Gautam Senapati, Vibhor Ahluwalia, Gianeshwaree Alias Rachna Panjwani, Anmolpreet Kaur, Gayathri Yerrapragada, Jayavinamika Jayapradhaban Kala, Poonguzhali Elangovan, Shiva Sankari Karuppiah, Naghmeh Asadimanesh, Anjani Muthyala, and Shivaram Poigai Arunachalam, “Artificial Intelligence-Guided Neuromodulation in Heart Failure with Preserved and Reduced Ejection Fraction: Mechanisms, Evidence, and Future Directions”, Journal of Cardiovascular Development and Disease, MDPI, vol. 12, no. 8, 314, pp. 1-28, August 2025. (SCIE, IF-2.3) https://doi.org/10.3390/jcdd12080314

8. Rohan Kalahasty, Gayathri Yerrapragada, Jieun Lee, Keerthy Gopalakrishnan, Avneet Kaur, Pratyusha Muddaloor, Divyanshi Sood, Charmy Parikh, Jay Gohri, Gianeshwaree Alias Rachna Panjwani, Naghmeh Asadimanesh, Rabiah Aslam Ansari, Swetha Rapolu, Poonguzhali Elangovan, Shiva Sankari Karuppiah, Vijaya M. Dasari, Scott A. Helgeson, Venkata S. Akshintala, and Shivaram Poigai Arunachalam, “A Novel You Only Listen Once (YOLO) Deep Learning Model for Automatic Prominent Bowel Sounds Detection: Feasibility Study in Healthy Subjects”,Sensors,MDPI, vol. 25, no. 15, 4735, pp. 1-13, July 2025. (SCIE, IF-3.5) https://doi.org/10.3390/s25154735

9. Mrinnal Kanti Dhar, Mou Deb, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Divyanshi Sood, Avneet Kaur, Charmy Parikh, Swetha Rapolu, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari, Naghmeh Asadimanesh, Shiva Sankari Karuppiah, Scott A. Helgeson, Venkata S. Akshintala, and Shivaram Poigai Arunachalam, " A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Classification", Journal of Imaging, vol. 11, no. 7, 243, pp. 1-15, July 2025. (SCI, IF-3.3) https://doi.org/10.3390/jimaging11070243

10. Poonguzhali Elangovan, D. Vijayalakshmi, Malaya Kumar Nath, Pratheepan Yogarajah, and Loan Condell, " A Novel Approach for Meat Quality Assessment Using an Ensemble of Compact Convolutional Neural Networks ", Applied Sciences, vol. 14, no. 14: 5979, pp. 1-18, July 2024. (SCI, IF-2.5)  https://doi.org/10.3390/app14145979

11. D. Vijayalakshmi, Poonguzhali Elangovan, T. Sandhya Kumari, and Malaya Kumar Nath, "Optimized multi-scale framework for image enhancement using spatial information-based histogram equalization", The Imaging Science Journal, 1–28. May 2024. https://doi.org/10.1080/13682199.2024.2343979 

12. D. Vijayalakshmi, Poonguzhali Elangovan, and Malaya Kumar Nath, " Methodology for Improving Deep Learning-based Classification for CT scan Covid-19 Images", Biomedical Engineering: Applications, Basis, and Communications, World Scientific Publishing Company, March 2024. (SCI, IF-0.9)  https://doi.org/10.4015/S101623722450008X

13. Poonguzhali Elangovan, D. Vijayalakshmi, and Malaya Kumar Nath, " COVID-19Net: An Effective and Robust Approach for Covid-19 Detection Using Ensemble of ConvNet-24 and Customized Pre-trained Models", Circuits, Systems, and Signal Processing, Springer, December 2023. (SCI, IF-2.31)  https://doi.org/10.1007/s00034-023-02564-3 

14. Poonguzhali Elangovan, and Malaya Kumar Nath, "En-ConvNet: A Novel Approach for Glaucoma Detection from fundus images using Ensemble of Deep Convolutional Neural Networks", International Journal of Imaging Systems and Technology, John Wiley & Sons, vol. 32, no. 6, pp. 2034-2048, November 2022. (SCI, IF- 3.3) https://doi.org/10.1002/ima.22761

15. Poonguzhali Elangovan, and Malaya Kumar Nath, "A novel shallow ConvNet-18 for malaria parasite detection in thin blood smear images", SN Computer Science, vol. 2, no. 5, pp. 1-11, July 2021, indexed in ACM Digital Library, Scopus. https://doi.org/10.1007/s42979-021-00763-w 

16. Poonguzhali Elangovan, D. Vijayalakshmi, and Malaya Kumar Nath, "Detection of glaucoma from fundus image using pre-trained Densenet201 model", Indian Journal of Radio & Space Physics (IJRSP), NiScPR-CSIR, vol. 50, no. 1, pp.33-39, March 2021, indexed in Scopus. http://nopr.niscair.res.in/handle/123456789/58080

17. D. Vijayalakshmi, Poonguzhali Elangovan, and Malaya Kumar Nath, "Renyi entropy-based bi-histogram equalization for contrast enhancement of MRI brain images", Indian Journal of Radio & Space Physics (IJRSP), NiScPR-CSIR, vol. 50, no. 1, pp.5-11, March 2021, indexed in Scopus. http://nopr.niscair.res.in/handle/123456789/58085

18. Poonguzhali Elangovan, and Malaya Kumar Nath, “Glaucoma assessment from color fundus images using convolutional neural network”, International Journal of Imaging Systems and Technology, vol. 31, no. 02, pp. 955-971, September 2021, indexed in (SCI, IF- 3.3). https://doi.org/10.1002/ima.22494 

19. Poonguzhali Elangovan, and Malaya Kumar Nath, “A review: person identification using retinal fundus images”, International Journal of Electronics and Telecommunications, vol. 65, no. 4, September 2019, pp. 585-596, indexed in ESCI and Scopus. https://doi.org/10.24425/ijet.2019.129817 

20. G. Ravichandran, Poonguzhali Elangovan, and Malaya Kumar Nath, ”Diagnosis of retinitis pigmentosa from retinal images”, International Journal of Electronics and Telecommunications, vol.65, Issue 3, August 2019, pp. 519-525, indexed in ESCI and Scopus. https://doi.org/10.24425/ijet.2019.129808  

21. Mithun Kumar Kar, G. Ravichandran, Poonguzhali Elangovan, and Malaya Kumar Nath, “Analysis of diagnostic features from fundus image using multiscale wavelet decomposition”, ICIC Express Letters Part B: Applications, vol 10, no. 2, February 2019, pp.175-184, indexed in Scopus. https://doi.org/10.24507/icicelb.10.02.175 

Conferences (Total Nos.: 05):

1. Nicholas Dwork, Poonguzhali Elangovan, Daniel O Connor, Alex McManus, Roland Krug, Galateia J Kazakia, Catherine M Jankowski, Julio Carballido-Gamio, “ Data Augmentation with Generative Deep Learning for Automatic Bone Segmentation from Fat Fraction MRI”, International Society for Magnetic Resonance in Medicine (ISMRM) 2025, Honolulu, Hawaii, United States, 10-15, May 2025. https://archive.ismrm.org/2025/1721_BZoJWVRLN.html

2.  Poonguzhali Elangovan and Malaya Kumar Nath. "Performance analysis of optimizers for glaucoma diagnosis from fundus images using transfer learning", Machine learning, Deep learning, and Computational Intelligence for Wireless Networks (MDCWC2020), October 2020 - Published in Lecture Notes in Electrical Engineering, Springer, vol. 749, May 2021, pp. 507-518. https://doi.org/10.1007/978-981-16-0289-4_37 

3. Poonguzhali Elangovan, Malaya Kumar Nath, and Madhusudan Mishra, "Statistical parameters for glaucoma detection from color fundus images", Third International Conference on Computing and Network Communications (CoCoNet’19) December 2019– Published in Procedia Computer Science, Elsevier, vol. 171, June 2020, pp. 2675-2683. https://doi.org/10.1016/j.procs.2020.04.290 

4. Poonguzhali Elangovan, Giritharan Ravichandran, Malaya Kumar Nath, and Om Prakash Acharya, "Review on localization of optic disc in retinal fundus image", IEEE International Conference on Applied Electromagnetics, Signal Processing and Communication (AESPC2018), October 2018 (Published in IEEE March 2020), KIIT Bhubaneswar, India. https://doi.org/10.1109/AESPC44649.2018.9033304 

5. D. Vijayalakshmi, Poonguzhali Elangovan, and Malaya Kumar Nath, " Multiscale based Joint Histogram Equalization for Nearly Invisible Natural Images", Third National Conference on Communication Systems (NCOCS-2021), December 2021.

Book Chapter (Total Nos.: 02): 

1. Poonguzhali Elangovan, D. Vijayalakshmi, and Malaya Kumar Nath, “ An improved approach for classification of glaucoma stages from color fundus images using Efficientnet-b0 convolutional neural network and recurrent neural network', Computational Methods and Deep Learning for Ophthalmology, Academic Press, March 2023, pp. 89-106. https://doi.org/10.1016/B978-0-323-95415-0.00003-6

2. Poonguzhali Elangovan and Malaya Kumar Nath, " Towards Robust Diagnosis of Alzheimer's Disease using Ensemble of Convolutional Neural Network and Vision Transformer", Handbook of AI-Based Models in Healthcare and Medicine, Taylor and Francis Group, December 2023. http://dx.doi.org/10.1201/9781003363361-9

Awards:

1. Recipient of Best Research Award in the year 2020 by ScienceFather, an International Research Awards on New Science Inventions.

Professional Services (Reviewer):

1. Biocybernetics and Biomedical Engineering  

2. Engineering Reports

3. Mathematical Biosciences and Engineering

4. Scientific Reports

5. BMC Medical Informatics and Decision Making

Professional Body Member:

IEEE Member- 96275345, Region: R10 -Asia and Pacific, Section: Madras Section

Certified Courses:

1. AI for Medical Diagnosis, completed on 04.03.2021 - An online course offered by deeplearning.ai and offered through Coursera.

2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, completed on 14.06.2020 - An online course offered by deeplearning.ai and offered through Coursera.

3. Neural Networks and Deep Learning, completed on 16.05.2020 - An online course offered by deeplearning.ai and offered through Coursera.

4. Machine Learning, completed on 12-09-2018 - An online course offered by Standford University and offered through Coursera.

5. Optical Coherence Tomography in Glaucoma, completed on 06-04-2019 - An online course offered by World Glaucoma Association.

6. Clinical Examination of the Optic nerve, completed on 16-03-2019 - An online course offered by World Glaucoma Association

Training Programmes and Workshops:

1. Winter School on "Advances in Deep Learning for Multimedia Signal Processing", jointly organized by IEEE Signal Processing Society GS, IEEE Computer Society GS, and IEEE Geoscience Sensing Society GS from 03-03-2022 to 05-03-2022.

2. Short term course on "Emerging Topics on Instrumentation, Electronics, and Communications", organized by Department of ECE, Madanapalle Institute of Technology and Science, Madanapalle from 27-10-2021 to 31-10-2021.

3. Workshop on "Artificial Intelligent Techniques to Address Societal Challenges", jointly organized by IEEE India Council Educational Activities Committee in Association with IEEE Madras Section, Pune Section, Educational Society, Hyderabad Section and YP, Madras Section from 01-10-2021 to 03-10-2021.

4. Faculty development programme on "Artificial Intelligence in Revolutionizing Healthcare", organized by ATAL at National Institute of Technology Puducherry, Karaikal from 19-07-2021 to 23-07-2021.

5. Webinar on "Computer Aided Diagnosis of Medical Images using Deep Learning", organized by Signal Processing Group of ECE Department, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi on 31-05-2021.

6. Faculty development programme on "Machine Learning for Computer Vision", jointly organized by Electronics and ICT Academics at IIT Guwahati, IIT Kanpur, MNIT Jaipur, PDPM IITDM Jabalpur from 01-02-2021 to 12-02-2021.

7. Short term course on "Research Opportunities in Bio-medical Engineering: Theory to Device (ROBIE)", organized by Indian Institue of Information Technology, Design, and Manufacturing (IITDM), Kancheepuram from 08-01-2021 to 12-01-2021.

8. Webinar on "Current Trends in Medical Image Analysis", jointly organized by IEEE EMBS Madras Section in Association with PSG Tech EMBS SB Chapter & Biomedical Engineering Association at PSG College of Technology, Coimbatore on 26-12-2020.

9. Faculty development programme on "Deep Learning Networks and Applications", organized by IEEE Madras Section 26-08-2020 to 29-08-2020.

10. Faculty development programme on "Advanced Communication System Design and Simulations", organized by Department of ECE, National Institute of Technology Puducherry, Karaikal from 17-08-2020 to 25-08-2020.

11. Webinar on "Lung Ultrasound Imaging for Covid-19: From Physics to Neural Network", organized by IEEE at National Institute of Technology Tiruchirappalli on 15-08-2020.

12. Webinar on "Insights to Machine Learning", organized by SCAD College of Engineering and Technology, Tirunelveli on 26-05-2020.

13. Workshop on "ML and AI using Covid-19 Virus Data Analysis", jointly organized by IIT Roorkee and Finland Labs from 29-04-2020 to 30-04-2020.

Experience:

1. Faculty on Contract, Department of ECE, NIT Puducherry, Karaikal, India.

(i) 22.02.2013 - 10.07.2103

(ii) 15.07.2013 - 16.12.2013

(iii) 26.12.2013 - 26.05.2014

(iv) 10.07.2014 - 17-12-2014

(v) 11.07.2016 - 07.12.2016

(vi) 26.12.2016 -16.05.2017

2. Assistant Professor (Senior Grade), Department of Information Technology, Valliammai Engineering College, Chennai (10.12.2008 - 21.02.2013).

3. Lecturer, Department of ECE, R.M.K Engineering College, Chennai (26.06.2006 - 02.05.2008)

4. Lecturer, Department of ECE, V.L.B Engineering College, Coimbatore (07.06.2004 - 31.05.2006)

Subjects Handled at NIT Puducherry: 

Theory: Laboratory:

1. Semiconductor Physics and Devices       1. Digital Electronics Lab

2. Digital Signal Processing       2. Microprocessor Lab

3. Microprocessors and Microcontrollers       3. Microwave Lab

4. Digital Signal Processor

5. Advanced Microprocessors

6. Embedded System

7. Fiber Optic Communication

Subjects Handled at Other Colleges: 

Theory: Laboratory:

1. Microprocessors and Microcontrollers       1. Digital Electronics Lab

2. Digital Principles and System Design       2. Microprocessor Lab       

3. Embedded System Design       3. Embedded System Design Lab

4. Electron Devices       4. Communication System Lab

5. Signals and Systems       5. Digital Signal Processing Lab

6. Digital Signal Processing       6. Electronics Circuits-II and Simulation Lab

7. Transmission Lines and Networks       7. Engineering Practice Lab

8. Industrial Electronics

9. Electronic Circuits