- M.S. Industrial Engineering | Arizona State University
- B.S. Mechanical Engineering | Indus University
Graduate Services Assistant @ Arizona State University (August 2023 - Present)
- Reviewed and analyzed Ph.D. assignments, projects, and exam papers and provided insights into convex optimization mathematical models and algorithms to optimize operations, allocate resources, and enhance overall productivity.
- Supporting an information systems application engineering course, adept in coordinating curriculum elements encompassing information technology, data modeling, database engineering, and programming in MySQL and VBA (Macro).
Supply Chain Manager @ Win Industries (April 2021 - July 2022)
- Elevated supply chain efficiency by 12% through strategic management of electrical components and spare parts inventory, harnessing advanced BI tools (PowerBI & Excel) for data analysis and reporting, facilitating informed decision-making.
- Optimized inventory levels for induction furnace, coordinated replenishment processes, and maintained accurate recordkeeping, resulting in a 4% cost reduction and improved inventory turnover.
- Performed data analysis to identify specific areas within the supply chain operations requiring optimization, leading targeted initiatives that resulted in a remarkable 19% increase in overall efficiency and the streamlined enhancement of logistical processes.
- Utilized ERP systems to rigorously evaluate supply chain KPIs, inventory management, and order forecasting, resulting in informed decisions and a notable 9% improvement in relevant KPIs.
- Developed and applied business protocols, including accounting systems, logistics arrangements, and production schedules, to boost operational efficiency by 14% and attain goals.
- Skilled in operations research, optimization, and Python, adept at solving intricate problems through mathematical modeling, with a proven track record in managing projects with 350+ constraints and 500+ variables.
- Built a Python model using Gurobi, Pyomo, AMPL, CPLEX, and GLPK handling linear and integer programming, and coupled with rigorous sensitivity analysis, achieved 100% accuracy improvement in staffing decisions.
- Developed a comprehensive mathematical model capable of handling both linear programming (LP) and mixed-integer linear programming (MILP) scenarios, allowing for precise problem representation and solution generation.