• Formulation , Validation and Sensitivity Analysis of Optimization models, Collaboration to Integrate offline models within system creating Decision Support Systems.• Decision Modeling across business domains including Supply Chain and logistics, Manufacturing, Resource Planning, Production Planning and Control ,Business Strategy. • Techniques : LP-MILP, IP, NLP, Dynamic Programming, Multi Criteria Decision Making-Goal Programming, AHP.

Worked under guidance of prof. K. Madduletty, in area of data driven Quality Assurance. Collected Process data from Cast Iron Foundry and Additive Manufacturing units. Focusing on identifying crucial input parameters. Employing various ML techniques, including Random Forest, Linear Regression, Ridge Regression, and Support Vector Machines (SVM), created predictive models to forecast performance based on the selected parameters. Paper highlighting the work presented in IEOM conference.

• Overseeing daily order fulfilment of multiple warehouses and daily reports tracking the service levels• Monitoring inbound consignments to match daily dispatches through Uniware and Magento• Estimations and projections of manpower and forecasting of sales• Process improvements through KAIZEN to address customer escalations

• Application Engineering - requirement analysis and suggesting technical specifications for B2B Clients• Preparing techno commercial proposals and quotations• Submitting PSU Tenders and bids for reverse auction, Enquiry and Quotation handling through ERP

• Studied cyclone shelter infrastructure and developed location allocation - model for population shifting• Formulation, Validation , Sensitivity Analysis of Optimization model using packages like PuLP, PYOMO.• Incorporated GIS Data within the model, constructed engine model for wider deployment.