About me
I hold a PhD in Signal Processing and AI from the Indian Institute of Technology (IIT) Roorkee. Currently, I lead AI initiatives as Staff AI Engineer at Samsung R&D India, driving scalable health-tech innovations in physiological signal processing (ECG, PPG, audio) and generative AI. My expertise spans full-stack AI development—from large-scale data pipelines to regulatory-ready healthcare algorithms—and I've contributed to FDA-ready solutions for cardiovascular and metabolic monitoring. At Samsung, I also built intelligent RAG systems enabling interactive data analytics for clinicians. My previous roles include developing in-cabin smart intelligent AI features at Mercedes-Benz and leading FDA-cleared AI modules at Elastic Care, Canada. I'm also passionate about explainable AI, clinical validation, and AI on edge devices for global scalability.
Download CVMy Work Experience
With over a decade of experience, I consult for global health-tech startups like Vigo Health Care, Pareto Tree, and Elastic Care. I’ve supported FDA 510(k), SaMD compliance, and clinical trial design, particularly for wearable-based vital sign monitoring (e.g., HR, RR, arrhythmia). My work bridges deep learning, biomedical engineering, and regulatory readiness for commercial deployment.
I regularly deliver workshops and lectures on topics like Machine Learning, Deep Learning, Biomedical Instrumentation, and Automated Decision-Making Systems (ADM) in healthcare. I’ve been an invited speaker at IIM Sambalpur, NIT Jalandhar, and other institutes. During my PhD, I developed virtual biomedical labs and published in leading journals (see Publications tab).
I'm a peer reviewer for top journals including IEEE Transactions on Instrumentation & Measurement, IEEE IoT Journal, Scientific Reports (Nature), and others. My research contributions focus on deep learning in healthcare, including atrial fibrillation classification, XAI, and multimodal learning, with multiple Q1 publications and two pending patents in automotive health sensing.
My skills
I am having a good command on python, matlab and AI frameworks like tensorflow, keras, scikit learn, pandas and others. Please see my CV for full details and publications.
Read moreMy Education
I graduated with a PhD in 2022. My topic of thesis was "Automated Arrhythmia detection using ECG signals". This study was focused on the development of machine learning and deep learning models for the classification of different arrhythmias using ECG signals. I additionally developed explainable AI (XAI) techniques. This thesis resulted in three Q1 publications and a number of conferences.
I earned my Master of Technology in Biomedical Instrumentation in 2015. My Topic of Research in masters was "Impulse Noise Removal using FPGA: Case study- ECG signal". This project entailed designing and implementing an adaptive filter for ECG signals to reduce impulse noises. The implementation was carried out on an FPGA board using Verilog HDL.
In 2011, I received my bachelor of technology in Electronics and Instrumentation from HCST. Courses studied: Digital Signal Processing, Data Structures, Control System, Electrical Instrumentation System etc.
My Publications
- Singh, Prateek, Ambalika Sharma, and Shreesha Maiya. "Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network." Expert Systems with Applications 233 (2023): 120975 (I.F- 8.5).
- P. Singh and A. Sharma, ”Attention-Based Convolutional Denoising Autoencoder for Two-Lead ECG Denoising and Arrhythmia Classification,” in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-10, 2022, Art no. 4007710, doi: 10.1109/TIM.2022.3197757. (I.F. 5.6)
- P. Singh and A. Sharma, ”Interpretation and Classification of Arrhythmia using Deep Convolutional Network,” in IEEE Transactions on Instrumentation and Measurement, 2022, doi: 10.1109/TIM.2022.3204316. (I.F. 5.6)
- P. Singh and A. Sharma, ”P. Singh and A. Sharma, ”Atrial Fibrillation Classification Using Transfer Learning,” 2021 IEEE Bombay Section Signature Conference (IBSSC), 2021, pp. 1-5, doi: 10.1109/IBSSC53889.2021.9673229.
- S. Mirza, K. Bhole and P. Singh, ”Fetal ECG Extraction and QRS Detection using Independent Component Analysis,” 2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA), 2020, pp. 157-161, doi: 10.1109/CSPA48992.2020.9068696.
- P. Singh, K. Bhole and A. Sharma, ”Adaptive Filtration Techniques for Impulsive Noise Removal from ECG,” 2017 14th IEEE India Council International Conference (INDICON), 2017, pp. 1-4, doi: 10.1109/INDICON.2017.8488064.
- SJ. Wadgaonkar, K. Bhole and P. Singh , ”Floating point FPGA architecture of PID controller,” 2015 International Conference on Industrial Instrumentation and Control (ICIC), 2015, pp. 1259-1263, doi: 10.1109/IIC.2015.7150941. ISBN No.978-1-4799-7/15
- P. Singh and K. Bhole, ”Impulsive Noise Removal from ECG”. 2015 International Conference on Computing,. Communication, Electrical, Electronics, Devices and Signal Processing, 2015, Mar 28-30, 2015, Lankapalli(Vijayawada), India.
- P. Singh and K. Bhole, ”Optimized floating point arithmetic unit,” 2014 Annual IEEE India Conference (INDICON), 2014, pp. 1-4, doi: 10.1109/INDICON.2014.7030552. ISBN No. 978-1-4799-5362-2.
My Patents
- "System and Method for sensing vitals of occupants in a vehicle." -(Pending) India Patent Application No. 202311086057 -Date of application: December 16, 2023.
- "Revolutionizing Vital sensing in automotive using semi-supervised deep learning" -(Pending) India Patent Application No. 202413073052 Date of application: November 11, 2024
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