Dr. Divya Singh is working as an Assistant Professor in the Department of Electronics and Telecommunication at BIT Durg, Chhattisgarh, India. She completed her Postdoctoral Research in the Department of Electrical Engineering at the Indian Institute of Technology (IIT), Bhilai (2024–2025), and earned her PhD in Biomedical Engineering from the National Institute of Technology (NIT), Raipur, which involved data collaboration with AIIMS Raipur's Department of Pulmonary Medicine. Her research interests lie in Explainable AI and Machine Learning in Healthcare, Biomedical Signal Processing (specifically Lung & Heart Sounds), Digital Health Systems & Wearable Technology, and Clinical Data Analytics and AI-based Diagnosis. Her previous academic appointments include serving as an Assistant Professor in the Department of Electronics & Telecommunication at Rungta College of Engineering & Technology and as a Lecturer at Kalinga University (2016–2017). She has published numerous technical research papers in reputed international platforms, including IEEE conference proceedings as well as SCIE, ESCIE, and SCOPUS indexed journals, covering advanced subjects like explainable deep learning models and federated learning.
About Faculty
Dr. Divya Singh
| Employee ID | 10432 |
| Date of Joining | 01-07-2026 |
| Nature of Association | Contractual |
| Department | Electronics and Telecommunication |
| Designation | Assistant Professor |
| Educational Qualification | Post-doc exp- IIT Bhilai PhD- NIT Raipur Mtech- BIT Durg BE- SSCET junwani |
| dsingh.phd2018.bme@gmail.com | |
| Contact Number |
Areas of Interest
* Explainable AI and Machine Learning in Healthcare * Biomedical Signal Processing (Lung & Heart Sounds) * Digital Health Systems & Wearable Technology * Clinical Data Analytics and AI-based Diagnosis
Publications
- Comparative Analysis of Lung Sound Denoising Techniques, ICPC2T 2020 (IEEE)
- Differential Diagnosis of Asthma and COPD using Statistical Analysis of PFT Data, I2CT 2021 (IEEE)
- Comparative Study of Different IIR Filters for Lung Sound Denoising, I2CT 2021, (IEEE)
- A correlative analysis between Covid-19 severity patient blood report and lung condition, 2025 (IEEE)
- Multi-Ensemble Filtering Approach for Heart Sound Removal from Lung Auscultations — IJOS (ESCI)
- A real-time correlation model between lung sounds & clinical data for asthmatic patients- IJIT (SCOPUS)
- A review on “Application of Machine learning in Diagnosis of Respiratory Disorders”-ECB (SCOPUS)
- A hybrid bioinspired model for improving the efficiency of correlative auscultation analysis-BJIT (SCOPUS)
- Transfer Learning Model for Correlative Analysis of Auscultation & Clinical Parameters using Explainable AI – Biomedical Physica & Engineering Express (SCIE)
- EDCF2SL: design of an explainable deep learning model for cardiovascular disease analysis using federated learning with few-shot learning operations.- JART (SCOPUS)
- Few-Shot Learning Model for COPD–Asthma Differentiation via Multifrequency Auscultation — Under Review
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