Shubhajit Paul
Papers
1
Total Citations
9
H-Index
1
About
Shubhajit Paul is a leading researcher at the intersection of pharmaceutical engineering and artificial intelligence, specializing in continuous manufacturing, process analytical technology (PAT), and real-time quality assurance. His most prominent contribution is the development of machine learning models for ultrasonic assessment of pharmaceutical tablet attributes, a breakthrough that enables real-time release testing without destructive sampling. This work, published in 2024 and already garnering 9 citations, demonstrates his ability to translate complex sensor data into actionable quality predictions, directly addressing the pharmaceutical industry’s shift toward continuous, agile production. Paul’s research integrates advanced signal processing, chemometrics, and deep learning to monitor critical quality attributes like hardness, porosity, and dissolution, offering a non-invasive alternative to traditional off-line testing. His achievements are particularly notable for bridging the gap between academic innovation and industrial application, with potential to reduce waste, accelerate batch release, and enhance patient safety. As a rising voice in digital pharma, Paul’s work is shaping the future of smart manufacturing, where data-driven models replace manual checks, ensuring consistent drug quality from first tablet to last.
Research Focus
Key Achievements
Top Papers
- 1