Wan-Ju Lin

• Composing master thesis supervised by Prof. Dr. Dr. Fabian Theis : Deep Learning Based Prediction of Mass Spectra and Amino Acid Sequences of Peptides • Implemented 2.5M set of peptide datasets over more than 100 species which was conducted by the Max Planck Institute of Biochemistry for over 1 year • Deep learning framework used : Bidirectional LSTM, Transformer, Attention, RNN • Programming language : Python , Tensorflow 2.0

• Responsible for building econometric tools from scratch for the supply chain team to perform sound and stable statistical analysis which is of large scales • Developed a scalable causal impact analysis toolset to support a specific decision making within the Amazon’s EU Customer Fulfillment department • Implemented 100M sets of datasets each having 140+ features • Implemented and assessed regression and classification models using both Spark and TensorFlow

• Industry analysis in the field of mechanical engineering and smart manufacturing to provide industry foresights and suggestions to both the government and the industries, providing high quality solutions • Output value modelling of the mechanical engineering field of Taiwan • Questionnaire analysis of the machinery firms in Taiwan for the Ministry of Economics affairs of Taiwan • Conducted a 6 page industry analysis report on Digital Twin for the industry yearbook of IEK

• Machine Learning • Statistics • Optimization • Data Engineering

• Computational Statistics

• Analysis • Algebra • Geometry • Statistics • PDE, ODE