Haitang Wang, Ph.D.
352-***-**** firstname.lastname@example.org GitHub Specializations LinkedIn Data Scientist
I am a self-motivated Physicist with dual degrees in quantitative engineering majors. I have experience with Statistical Analysis and Machine Learning Algorithms, including, but not limited to, k-NN, k-Means, Naïve Bayes, Random Forests, Regression, A/B testing, and Artificial Neural Network, with knowledge of Data Structure and Algorithms. I am passionate about Machine Learning and Artificial Intelligence, and I would like to make use of my analytical and coding skills to tackle complex problems. Analytics skills
Matlab, Python, Machine Learning, Data Mining, Statistics, Scikit-learn, R, Deep Learning, Tensorflow, Keras, Boosting, C++, noSQL, Java, Git, SAS, Hadoop, Spark, MapReduce, AWS, Oracle, Mathematica, Linux Selected Projects
Prediction: Washington house price prediction using multiple models was studied. Simple linear/multiple/polynomial regression, gradient descent method, regularization, LASSO feature selection algorithm, RSS, k-nearest neighbors, and cross validations were studied. Loan Classification: A loan data set of LendingClub was investigated to predict whether a loan will be paid off in full or the loan will be charged off and possibly go into default. Category data encoding, greedy algorithm for splitting feature selections, binary decision trees, tree visualization, multiple early stopping methods, and boosting algorithms were implemented. SQL-based E-Commerce: Data-driven E-commerce platform implemented in C# and SQL for buyers, sellers and managers with performance analysis.
Server Monitor: Scalable and dynamic system with a large amount of Internet traffic data. Busiest hours and popular users were found, and abnormal attempts were analyzed on the serve log file. Natural Language Processing (NLP) with deep learning, using word vector representations and embedding layers to train recurrent neural networks. A emogify system was built with LSTM algorithm in Keras. Additionally, word counts and TF-IDF was applied to retrieve articles using nearest neighbor search. Selected Experience
University of Florida, Gainesville, FL 2013 - 2017 Graduate Research Assistant & Consortium for Verification Technology Associate (link) Data preprocessing: binary raw data acquisition, extract feature information, build data pools with millions of events, and calculate response timing difference to track energy of incident particles. Mathematical Modelling the scintillation molecule excitation and decay process to study the populations of singlets and triplets as a function of time. Introduce convolution of Gaussian resolution function with exponential scintillation decay function to produce Ex-Gaussian distributions. Forecasting the 3-D stochastic collision process of fast neutron with deuterated scintillation medium and light output generated by deposited energy based on historical measurements and probability database. Identifying patterns by training detection parameters of starting, tail and end positions of wave vectors by maximizing the separation of particle categories based on Figure-of-Merits. Artificial Neural Network and Gaussian Mixture Classification algorithm were used to process digital waveforms. Microstructure and component study of carbon nanotube mixed ceramics using Scanning Electron Topography, Raman Spectra, Density, and Indentation hardness tests. Education
University of Florida Ph.D. in Nuclear Engineering (dissertation, publications), 2014 – 2017 University of Florida M.S. in Computer Engineering, 2016 - 2017 Recipient of full research assistantship through DOE-funded projects Specializations of Machine Learning and Deep Learning through Coursera (link) China University of Petroleum (East China) B.S. in Applied Physics (report), 2008 - 2012 Graduated with Honors of Best Thesis and Outstanding Undergraduate of Shandong Province