Richland, Washington, United States
-----Python (Programming Language) · GAMS · Amazon Web Services (AWS) · Gitlab · domino · Pulp · SharePoint · Pandas (Software) · EDA · Portfolio Optimization · ModelingObject-Oriented Programming (OOP) · Data Science · Data Analysis -----MIP, MILP, NLP, MINLP, QP model, etc., solver of CPLEX, CONOPT, ANTIGONE, BARON, etc. My research emphasized Operations Research, Applied Mathematics, Statistics, Industrial and Systems Engineering, Mathematical Modeling, and Programming Techniques, e.g., linear, non-linear (convex, non-convex), mixed integer programming, (i.e., LP, NLP, MILP, MINLP) deterministic & stochastic programming). I am currently working as Data Scientist in The Climate Corporation-Bayer and actively seeking a new (full-time) data science-related position: Full-time Data Scientist/Operations Research Engineer/Scientist position in Industrial Engineering, Operations Research Engineering, Chemical/Petrochemical Industry (Oil&Gas), Transportation Engineering, or other Process System engineering.
Laboratory of Integrated Systems Engineering, Chemical Engineering, Lamar University Project: • Maximum Resiliency Identification for the General Refinery Supply Chain (GRSC). Develop a resilience characterized optimization model for a full-scale GRSC system. Help oil & gas companies to not only quantitively recognize the inherent resilience of their supply chains; but also have better decision support to deal with threats of multi-natural disasters and unpredictable accidents in proactive and cost-effective ways.
Laboratory of Integrated Systems Engineering (Modeling and Optimization), Chemical and Biomolecular Engineering Dissertation Topic: "Large-scale Mathematical Modeling and Optimal Scheduling for Manufacturing and Supply Chain Management in Petroleum Refinery Industries"– Advisor/Dissertation Chair: Prof. Qiang Xu Simultaneous Scheduling of Multi-Product Pipeline Distribution and Depot Inventory Management for Petrochemical Refinery • Simultaneous scheduling of multiproduct pipeline distribution and depot inventory management. • Developed a novel MILP (by linearization method for NLP constraints) scheduling model with GAMS on multi-product pipeline distribution for petroleum refineries. • Economically handling trans-mix between different oil slugs during pipeline transportation. • Closed the gap between the modeling and reality by considering realistic operating rules of oil storage tanks. Simultaneous Scheduling of Refinery Manufacturing & Multi Oil-Product Pipeline Distribution (RM&MOPD) • Developed a novel systematic MINLP mathematical model with GAMS, solved by DICOPT with CPLEX and CONOPT4 as sub-solvers. • Included refinery manufacturing sub-model covering all major refinery processing units. • Adopted comprehensive transmix handling measures. • Deeply analyzed the total operating and utility cost-saving along the supply chain by comparing the integrated and sequential modeling and solving methods. • The newly developed integrated methodology: saved 12.5% of total operating and utility cost. Integrated Scheduling of the Holistic Refinery Supply-Chain Management • Constructed an integrated methodology and mathematical framework (with GAMS) to critically benefit the studied refinery supply-chain management by saving the total operating cost. • Avoid imbalances by refinery overproduction or underproduction. • Keep all the tanks along the supply chain at a relatively low level to greatly reduce the cost and increase depot management safety.
Teaching Assistant – Advanced Modelling Data Analysis – Summer II, 2019 • Planning and prepared course materials for optimization and GAMS software programming. • Delivered teaching materials clearly and efficiently. • Students learned the concept of optimization, programming language, mathematical modeling techniques, debugging method, and solving method. • Students can program a simple mathematical model on GAMS and solve it with appropriate commercial solvers.
• Effectively monitoring and controlling the terminal production through PLC system in the Central Control Room. • Improving the management efficiency through ERP system and CNPC Self-owned Oil Depot Management System. • Properly managing and scheduling the logistics of oil product regarding forecast, inventories, oil quality, demand, receiving, storage, and exporting of oil product. • Consistently track record of delivering, transportation, storage of oil product on an oil terminal scale. • Accurately providing the monthly production, economic, and safety statistics statement for the oil company. • Timely and efficient communication with other departments related to the production. • Properly handling customer disputes during the oil product exporting production. • Support the security team and other engineering teams for the fire drill and other HSE-related production and operating activities through the Central Control Room.
• Prepared key technical analysis and professional summaries of the quality testing for oil products. • Effectively assisted the operational decision-making process of the logistics branch manager. • Completely avoided oil product quality risks during the distribution production. • Improved the oil product quality reputation and economically benefit the profit margin for the company.