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Xi (Charles) Chen has worked for four different companies since 2015. Xi (Charles) began as a Research Associate at The University of Manchester where they collaborated with theoretical physicists and experimentalists, built physics models and formulated predictions, and analyzed experimental data and interpreted phenomena. In 2018, they worked as a Data Scientist at NTD Digital, where they analyzed the online behavior of internet users and the search behavior of the promotion of different industries. Xi (Charles) also worked as a Front End Developer at OPO Group, and as a Senior Research Scientist, Staff Research Scientist, and Research Scientist at CLARA Analytics. At CLARA Analytics, they designed and implemented a pipeline about evaluating the performance of medical institute in the early stage of the claim lifecycle, implemented the recalibration of the model and refactoring of the scripts for evaluation of the attorney in worker's compensation, designed and implemented the prediction of procedure and key events in the life cycle of claims based on time series neural network model, and led and implemented the de-identification protocol for sensitive documentation. Xi (Charles) also designed and implemented the fraud detection pipeline for medical provider in worker's compensation.

Xi (Charles) Chen received a Doctor of Philosophy (Ph.D.) in Theoretical and Mathematical Physics from Jilin University between 2000 and 2010. Xi (Charles) then went on to pursue a Doctor of Philosophy (Ph.D.) in Condensed Matter and Materials Physics from Lancaster University between 2011 and 2015. In addition, Chen has obtained a variety of certifications from Coursera and the Google Digital Academy (Skillshop), including Machine Learning Data Lifecycle in Production (2022), Introduction to Machine Learning in Production (2021), Convolutional Neural Networks in TensorFlow (2021), DeepLearning.AI TensorFlow Developer Specialization (2021), Natural Language Processing (2021), Natural Language Processing Specialization (2021), Natural Language Processing with Attention Models (2021), Natural Language Processing with Classification and Vector Spaces (2021), Natural Language Processing with Sequence Models (2021), Sequences, Time Series and Prediction (2020), Natural Language Processing in TensorFlow (2020), Deep Learning Specialization (2020), Convolutional Neural Networks (2020), Sequence Models (2020), Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization (2020), Structuring Machine Learning Projects (2020), Neural Networks and Deep Learning (2020), Digital Marketing Sales certification (2019), and Google Ads Fundamentals (2019).