● Conduct a comprehensive and in-depth literature review on quantum computing applications in electric power flow optimization. ● Developed and successfully solved a 136-node network system on a real quantum computer, demonstrating the practical impact of quantum optimization in electric power flow applications.

● Conducted an in-depth technical review of RFID technologies, benchmarking performance and identifying cost-effective solutions that reduced installation costs per item from few hundred dollars to less than $20. ● Developed, tested, and maintained robust communication protocols for micro-controller units in a mesh network, cutting latency by 10% and increasing reliability. ● Developed and tested communication protocol between micro-controller units (MCUs) in a mesh network. ● Utilized and embedded machine learning algorithms into MCUs (nRF52 and ESP32).

● Developed mathematical models (MIP, MILP, MICP, Non-convex). ● Developed advanced quantitative models, stochastic differential equations, risk modeling methods, distributionally robust and stochastic optimization techniques, and leveraging decomposition with distributed computing to enhance decision-making under uncertainty. ● Engineered a large-scale stochastic programming model incorporating 500 scenarios and developed innovative decomposition algorithms that reduced overall solution time to under 360 seconds.

● Accomplished the development of approximately 40 digital SOPs for the Civil group; increased equipment utilization by 20% on the jobsite. ● Developed a mobile application (Javascript & PowerApps) and Excel VBA Macro for training purposes.

● Designed and implemented an RFID system and led a motion time study that cut basket-finding time from 7.2 to 2 minutes and reduced monthly solid waste by 7 tons in a 6,000 employee facility. ● Designed a sustainable value stream mapping system with real-time RFID tracking, implemented for under $30,000 to enhance operational efficiency and sustainability.

● Led the Suggestion Scheme (Continuous Improvement) program, achieving a 40% increase in the number of suggestions and saving over $20,000. Won 2 out of 5 “Best of the Year” awards in the factory competition. ● Developed a program based on Visual Studio C# to manage data of the suggestion scheme program.