From AI research in neuro-oncology to statistical consulting and data engineering — a timeline of roles that have shaped my approach to rigorous, reproducible data science.
Advanced DCE-MRI analysis in glioblastoma using voxel-wise parsimonious pharmacokinetic modelling, multiparametric habitat-imaging, and machine learning for treatment response classification. Developing quantitative radiomics pipelines and contributing to multiple manuscripts on AI-driven biomarker discovery. Working with DICOM/NIfTI neuroimaging data at the intersection of clinical medicine and statistical machine learning.
Delivered 700+ high-accuracy solutions across probability theory, regression analysis, statistical inference, mathematical optimization, and stochastic processes. Maintained 98%+ learner satisfaction rating throughout continuous engagement. Developed expertise in explaining complex statistical concepts with clarity and pedagogical precision.
ETL pipeline design using SQL, Hadoop, and MongoDB for heterogeneous large-scale datasets. Improved data retrieval efficiency via indexing strategies, schema redesign, and distributed pipeline optimization using HDFS and MapReduce. Gained hands-on experience with big data infrastructure and NoSQL database design patterns.