Yujia Huang

• Responsible for the setup of Made-in-China website, product shelving, export follow up and searching for new customer group • Responsible for the company’s participation in the German TÜV certification matters, assist the domestic sales team for customer negotiations, shipping and documentation production • Control the risk of export orders according to international trade rules and export laws, review export packaging programs • Work as project engineer in the project management of a plant in Mexico

• Responsible for the sales and coordination of large/small harbor machine products in European market • Cooperate with sales in East China to participate in the development and maintenance of major customers and channel management, respond to customer needs and feedback on the use of products in Shanghai, Jiangsu province • Participate in product and shipment optimization with internal manufacturing, quality assurance and management departments, responsible for translation and correction of documents

• Coordinated cross-functionally with sales, supply chain and customer service for SPRC subcontinent • Handled and tracked sales of Polypropylene, Vistamaxx and Adhesions by delivering regular reports to assist the team in taking business decisions • Ensured fulfilment of volume commitments to accounts across SPRC by managing volume allocation on cycle basis • Interface with Regional Sales Planner and Sales Representatives and Supply Planner to resolve allocation

• Getting familiar with implementing neural architectures with PyTorch e.g. GAN, Auto-Encoders, Transfer Learning etc. • Implementing GCN, GAT, GraphSAGE for CORA Datasets using PyTorch withought third party graph network libraries • Review student’s thesis and projects

• Literature review of theoretical basics of physical mechanism and simulation of mechnical product, including literature study on topics related to data analytics in the industry • Developed a validated physical simulation model with Amesim • Implemented a batch operation method with DoE strategies to search for parameter combination and improve the performance of physical model • Developed Feature Engineering workflow • Implemented scickit-learn pipeline to construct machine learning model

• Literature review of existing methods for determining the material behavior • Implementation of a parameter identification method for determining the constitutive parameters of the individual material components • Determination of the accuracy of identified material laws of both components of the variability of the relative volume fractions of both components • Implementation of a parameter identification method for determining the constitutive parameters of the individual material components