Dr. Sagar Deep Deb

Dr. Sagar Deep Deb

Assistant Professor

Profile Summary

Dr. Sagar Deep Deb is currently serving as an Assistant Professor in the School of Computer Science, UPES. He completed his Ph.D. from the Department of Electrical Engineering at Indian Institute of Technology Patna. His doctoral research was broadly focused on Biomedical Signal Processing using machine learning and deep learning techniques.

Dr. Deb is passionate about applying advanced computational methods to solve real-world healthcare challenges. His academic interests center on intelligent healthcare systems, biomedical analytics, and technology-driven clinical decision support.

Work Experience

Before joining UPES, Dr. Deb worked as an Institute Post Doctoral Fellow in the Department of Biosciences and Bioengineering at Indian Institute of Technology Bombay from June 2024 to September 2025.

During this period, he worked on healthcare-related projects such as ventilator dyssynchrony detection, ECG annotation systems, and biomedical data analysis.

Research Interests

Biomedical Signal Processing | Human–Computer Interaction | Smart Healthcare Technologies | Computational Biology | Machine Learning | Deep Learning | Clinical AI Systems

Teaching Philosophy

Dr. Deb believes that practical knowledge complements theoretical understanding. He emphasizes application-oriented learning where students connect classroom concepts with real-world computing and healthcare challenges.

His teaching approach encourages curiosity, experimentation, and analytical thinking.

Courses Taught

Foundation of Machine Learning | Operating Systems

Awards and Achievements

Recipient of the Best Paper Award at the 2023 IEEE IConSCEPT, organized by National Institute of Technology Puducherry.

Scholarly Activities

Dr. Deb has been actively involved in scholarly activities and has served as a reviewer for various academic journals. He has presented his research at several national and international conferences.

His work continues to contribute to the fields of biomedical signal analysis, healthcare AI, and intelligent clinical systems.

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