Shresth Gupta

Shresth Gupta is a Research Fellow in the School of Mathematics and Physics at the University of Surrey, affiliated with the Mathematics at the Interface Group. His research lies at the intersection of biomedical signal processing, artificial intelligence, and healthcare innovation, with a focus on photoplethysmography (PPG)-based monitoring for non-invasive diagnostics.

Education:

• PhD in Electronics and Telecommunication Engineering, International Institute of Information Technology, Naya Raipur, India (2023)
• M.Tech in VLSI Design, CSVTU, Bhilai, India (2014)
• B.E. in Electronics and Telecommunication Engineering, CSVTU, Bhilai, India (2011)

His research interests include biomedical signal processing, PPG signal analysis, machine learning for healthcare, wearable health monitoring, and telemedicine. He specializes in developing AI-driven models for cuffless blood pressure estimation, early diabetes detection, cerebral infarction screening, and PPG signal denoising and compression. His work leverages advanced signal processing techniques such as TQWT, DCT, and Savitzky-Golay filtering, combined with machine learning models like Random Forest, LSTM, and CNNs.

The recent publications reflect a strong trend in leveraging PPG signals for non-invasive, continuous health monitoring. His research spans from fundamental signal enhancement (denoising, compression) to clinical applications (diabetes, hypertension, stroke). The work consistently targets real-world deployment in wearable devices, emphasizing robustness, accuracy, and compliance with clinical standards like the British Hypertension Society benchmarks.

Scientific Awards:

• No awards listed in the provided text.

Shresth Gupta has not published any information about advising students or securing research grants in the given content. However, his extensive publication record in high-impact journals and conferences (IEEE, Springer) indicates active research engagement. He is involved in interdisciplinary teams working on healthcare technology innovation, particularly within the Mathematics at the Interface Group at the University of Surrey, which likely fosters collaboration between mathematics, physics, and medical applications. His future work is expected to further advance AI-powered, wearable-based diagnostic systems for chronic disease management.