eSupervisor Detail

About me

PhD and CSIR-NET qualified Biotechnology professional with an engineering background and 8+ years of experience spanning academic research, scientific publishing, and computational data science. Combines rigorous life sciences expertise with advanced capabilities in machine learning, biostatistics, and scientific communication to deliver measurable impact across research, editorial, and analytical domains.

Interests: Machine Learning & Artificial Intelligence in Life Sciences Application of supervised and deep learning models — including Artificial Neural Networks, Deep Neural Networks, Convolutional Neural Networks, Random Forest, and Support Vector Machines — to biological prediction, optimization, and decision-making problems. Particular interest in developing and validating ML pipelines for real-world biomedical and agricultural research challenges. Biostatistics & Quantitative Research Methods Advanced statistical modelling in life sciences research, encompassing multivariate regression, Response Surface Methodology, sensitivity analysis, meta-analysis, and thematic analysis. Emphasis on rigorous experimental design, reproducibility, and translating statistical outputs into actionable scientific insights. Computational Biology & Bioinformatics Molecular structure prediction, sequence analysis, feature engineering for molecular interaction modelling, and development of bioinformatics pipelines for large-scale biological datasets. Experience with high-performance computing environments for managing complex computational workflows. Natural Product Chemistry & Phytochemistry GC-MS and UV-Vis Spectrophotometry-based profiling, identification, and quantification of plant secondary metabolites, with a focus on essential oil composition, curcuminoid analysis, and agroclimatic influences on metabolite yield in medicinal and aromatic plants. Scientific Communication & Editorial Science Evidence-based peer review, manuscript quality assessment, and the application of editorial standards to improve the clarity, rigour, and reproducibility of published scientific research. Interest in the automation and optimisation of editorial and publication workflows. Agri-Biotech Innovation & Entrepreneurship Startup ecosystem development, evaluation of agri-biotech innovation proposals, and knowledge transfer through training and outreach — bridging research outputs and real-world agricultural application.