Engineer Data

DAOWEI LI

Target Position: Software Engineer / Machine Learning Engineer – New Grad

Tel: 773-***-**** Email: ************@*****.***

Address: **** ******* ****** *** ***, Evanston, IL 60201. EDUCATION Northwestern University, Evanston, IL, USA Sept.2016- Dec.2017 Master of Science in Electrical Engineering and Computer Science GPA: 3.9/4.0

Relevant Courses: Design & Analysis of Algorithms, Machine Learning, Statistical Pattern Recognition, Intro to Artificial Intelligence, Intro to Parallel Computing. Beijing Technology and Business University, Beijing, China Sept.2012- June.2016 Bachelor of Engineering in Information Technology

GPA: 3.8/4.0 Ranking: top2/63

Honors: Excellent Graduate of Beijing, Merit Student of Beijing. WORK EXPERIENCE Sina Weibo June.2017- Sept.2017

Machine Learning Engineer Intern Beijing, China

Depending on Wide & Deep Learning model, implemented the ranking algorithms of recommendation system of micro-blog according to its characteristics, in order to improve the CTR

(Click-Through-Rate) of micro-blog. Analyzed and improved the recommender algorithm, and combined different features as new features to be input to improve the model effect.

According to the current recommendation system, changed the Logistic Regression model with FTRL and enabled the model to do online learning.

Netease Games May.2016- Sept.2016

Data Scientist Intern Beijing, China

According to data of users’ relevant behavior in the past few months, classified the target users who will have in-app-purchase. The behavior data includes registration information, session history, purchase history and spending history.

Analyzed original data distribution, visualized the data and did analysis on the correlation between attributes and the label. Discarded irrelevant attributes, such as roles in the game, and processed relevant data, like splitting records by week for further analysis in machine learning.

Implemented several machine learning algorithms, like Decision Tree, SVM, Naïve Bayes and Neural Network on user data. Evaluated the model by accuracy and training time. Chose Neural Network to do classification, and analyzed the characteristics of target users. SKILLS Programming Languages: Java, Python (Machine Learning – TensorFlow), Database(SQL). PROJECT EXPERIENCE Human resource analysis (Dimission Rate Forecast) Apr.2017- June.2017

Analyzed the original data, and made pretreatment on metadata, like analyzed the relevance of attributes, removed irrelevant attributes and did one-hot encoding on discrete variables.

Used different machine learning algorithms to model and analysis data (such as Random Forest – Decision Tree, Naive Bayes, SVM, DNN), and evaluated each model according to its result and performance. Chinese Character Recognition Dec.2016- Feb.2017

Implemented Convolutional Neural Networks(CNN) to recognize handwritten Chinese characters.

Evaluated the performance of CNN on the recognition, and change the network structure or fine tune the parameters in order to improve the accuracy. Speech Recognition of Endangered Language based on Machine Learning Feb.2016- May.2016

Collected and arranged original speech data, and extracted the mfcc feature as training data.

Applied and implemented GMM or DNN cooperated with Hidden Markov models(HMM) respectively to make acoustic model for each word of speech data by Python. Then based on the results of two models, put forward the improvement of the program and algorithm.

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