Shweta Mishra | Pharmaceutical Science | Research Excellence Award

Published-on by Indian Scientist

Dr. Shweta Mishra | Pharmaceutical Science | Research Excellence Award

Pancholi Consultancy | India

Dr. Shweta Mishra is a dedicated pharmaceutical researcher known for her expertise in analytical method development, stability-indicating studies, and advanced characterization techniques, reflected in her citation count of 669, an h-index of 13, and 22 indexed documents. She holds a Bachelor’s and Master’s degree in Pharmacy with strong academic performance and a doctoral qualification specializing in the development and validation of LC-MS/MS methods for identifying and characterizing degradation products of complex drug molecules. Her professional journey includes significant leadership responsibilities in QC and ADL departments, serving as Manager at reputed analytical laboratories, and later contributing as a Consultant overseeing WHO-GMP compliance, documentation systems, audits, validation, and quality improvements across pharmaceutical manufacturing environments. Her research interests focus on forced degradation studies, impurity profiling, chromatographic optimization, and structural elucidation using LC-MS/MS and NMR. She has published impactful research articles in peer-reviewed journals, delivered conference presentations, and contributed to scientific advancements related to anticancer agents and stability-indicating analytical methods. Her work has been recognized through honors such as a prestigious award for outstanding research in pharmaceutical analysis and an international excellence award for contributions to LC-MS/MS and NMR-based studies. She continues to advance pharmaceutical quality standards through research, technical expertise, and industry engagement.

Profile: Google Scholar

Featured Publications

Cudney, E. A., Furterer, S., & Dietrich, D. (2013). Lean systems: Applications and case studies in manufacturing, service, and healthcare. CRC Press.

Mishra, S., & Nath, M. (2013). Growth of vertically aligned CdTe nanorod arrays through patterned electrodeposition. Nano Energy, 2(6), 1207–1213.

Singh, D., Sharma, S. K., Rani, R., Mishra, S., & Sharma, R. A. (2011). Kaempferol-7-O-glucoside and their antimicrobial screening isolate from Cassia renigera Wall. International Journal of Pharmaceutical and Clinical Research, 3(2), 30–34.

Mishra, S., & Mukhopadhyay, P. K. (1996). Ascorbic acid requirement of catfish fry Clarias batrachus (Linn.). Indian Journal of Fisheries, 43(2), 157–162.

Mishra, S., Song, K., Koza, J. A., & Nath, M. (2013). Synthesis of superconducting nanocables of FeSe encapsulated in carbonaceous shell. ACS Nano, 7(2), 1145–1154.

Kabil Dev Mahato | Spectroscopy | Editorial Board Member

Published-on by Indian Scientist

Mr. Kabil Dev Mahato | Spectroscopy | Editorial Board Member

National Institute of Technology Jamshedpur | India

Kapil Dev Mahato is a researcher in physics whose work spans laser spectroscopy, computational chemistry, and data-driven modeling of organic dyes. His scientific contributions focus on predicting photophysical properties such as absorption and emission wavelengths, quantum yields, Stokes shift values, and Förster distance parameters using advanced machine-learning approaches. He has authored multiple peer-reviewed journal articles, conference papers, review works, and a book chapter, reflecting strong academic engagement and interdisciplinary impact. His Google Scholar profile reports 153 citations, an h-index of 7, and an i10-index of 6, demonstrating growing recognition in spectroscopy and machine-learning research communities. His academic training includes strong foundations in physics at both undergraduate and postgraduate levels, further strengthened by competitive national research fellowships. He has collaborated with experts in spectroscopy and computer science, contributing to work on fluorescent dyes, sol-gel systems, optical materials, and predictive ML models for scientific and biomedical data. His research interests include organic dye photophysics, fluorescence mechanisms, nanomaterials, ensemble learning methods, and scientific data modeling. He has participated in multiple national and international conferences, presenting work on spectroscopy and machine-learning applications. His overall profile highlights consistent research productivity, interdisciplinary collaboration, and commitment to advancing spectroscopy and computational modeling.

Profile: Google Scholar | Research gate | Linked In

Featured Publications

Mahato, K. D., & Kumar, U. (2024). Optimized machine learning techniques enable prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum yields. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 308, 123768.

Mahato, K. D., Das, S. S. K., Azad, C., & Kumar, U. (2024). Machine learning based hybrid ensemble models for prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum yields. APL Machine Learning, 2(1).

Bhowmick, A., Mahato, K. D., Azad, C., & Kumar, U. (2022). Heart disease prediction using different machine learning algorithms. In 2022 IEEE World Conference on Applied Intelligence and Computing (AIC) (pp. 60–65).

Mahato, K. D., Das, S. S. G. K., Azad, C., & Kumar, U. (2024). Stokes shift prediction of fluorescent organic dyes using machine learning-based hybrid cascade models. Dyes and Pigments, 222, 111918.

Mahato, K. D., & Kumar, U. (2023). A review of organic dye-based nanoparticles: Preparation, properties, and engineering/technical applications. Mini-Reviews in Organic Chemistry, 20(7), 655–674.