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Data Assistant

Location:
Springfield, MO
Salary:
60000-80000
Posted:
February 25, 2019

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Resume:

JUNYA ZHAO

Data Scientist

[ ac8lus@r.postjobfree.com Ó 417-***-**** 1 2 Apt B12 2010 Page St, Springfield, MO ̄ junya-zhao-61370a132 github.com/JunyaZ

EDUCATION

Master of Computer Science GPA:3.86/4.0

Certificate of Data Science GPA:4.0 / 4.0

Missouri State University Aug 2016–May 2019 1 2 Springfield, MO

M.S Coursework: Machine Learning, Advanced Database System, Advanced Algorithm, Software Testing, Operation Sys- tem, Multimedia Programming

Data Science Coursework: Applied Statistics, Stochastic Modelling, Data Mining, Data Analysis, Evolutionary Computing Bachelor of Electrical Engineering

Hangzhou Normal University Sep 2010–June 2014 1 2 Hangzhou,China

Coursework: Statistics, Linear Algebra,Calculus, Principle of Single-chip Computer, Operation System, C Programming, Computer Network, Sensor Technology, Embedded System,Signal Processing EXPERIENCE

Data Analytics

Andy’s Frozen Custard Inc. Oct 2018 – Present 1 2 Springfield, MO

Interpreting big data, analyzing results using statistical techniques( T-testing, Hypothesis testing) and providing reports

Implementing databases, taking the database reporting needs and turn them into SQL queries

Using simple machine learning technique that optimize statistical efficiency and analyzing patterns in complex data sets

Monthly sale promotion measurement analysis and research in big data analysis Research assistant

Missouri State University Jan 2018 – Present 1 2 Springfield, MO

Research assistant in machine learning and data analysis on bioinformatics

Design computational and mathematical methods for processing big data

Apply classification/clustering models to analyze and interpret biological data

Utilize data visualization tools( matplotlib, seaborn packages) to make concise visual representations of data

Implement evolutionary based algorithms on gene expression data to find bicluster patterns Data Analytics

Netopstec Inc. April 2014- Aug 2014 1 2 Hangzhou,China

Web traffic analytics. tracks how many pages are served to the user, how long it takes each page to load, how often the user hits the browser’s back or stop button and how much data is transmitted before the user moves on

E-commerce-based analysis. uses clickstream data to determine the effectiveness of the websites. what pages the cus- tomer lingers on, what the customer puts in a shopping cart?what items the shopper purchases, whether or not the shop- per is loyal to our store, and uses a coupon code and the customer’s preferred method of payment

Build predictive model for optimizing web usage and improving the effectiveness of a website

Responsible for Goldlion Tmall online flagship store’s website daily operation and maintenance SKILLS

Statistics: Hypothesis testing (A/B testing, T testing), Non-parametric Tests, Regression, Multivariate models, probabilistic modeling

Machine Learning: Random forest,Neutral network, K-means, DBSCAN,Self-organizing map, Evolutionary algorithm, Reinforcement learning, Bandit algorithm.

Computer Science: Strong programming skills in Python and its analysis package ( Numpy, Panda, Scipy and Scikit-learn). Intensive experience in big data prepossessing, feature engineering and data visualization. Fluent in SQL and relational database, experience with R, Scala, SAS and Spark MLlib. PROJECTS

Movie Recommendation System

Built an hybrid recommendation model on "Movielens" DataSet that includes over 100 millions ratings. Our model in- cludes 4 different modes based on 4 types user input( null, MoiveID, UsrId Or Moive and UsrID).

This system is able to predict movie ratings based on how the other users have predicted the movie.

Build an engine that gave movie suggestions to a particular user based on the estimated ratings that it had internally cal- culated for that user.

Playing DoomwithaRecurrentNetwork

Trained a reinforcement learning agent (combined with Double Deep Recurrent Network) in ViZDoom.

The AI agent was able to play the game Doom,attacking the enemy and survived automatically. Node-Based Resilience Graph Theoretic Framework Designed

Designed the graph based clustering algorithm to distinguish subgroups of Autism Spectrum Disorder (ASD). Used graph quality measures, internal cluster validation measures, and clinical analysis outcome to demonstrate the potential useful- ness of resilience measure for biomedical datasets. Facial Detection for Class Attendance

Developed an transfer learning Matrix as an head classifier to detect faces in the class

Different camera angle, position, image quality were the major challenges. The overall accuracy up to 90%. Object Recognition for Robot

Built an robot car on a raspberry Pi and implemented an object recognition model with deep neural networks.

The robot car is able to recognize traffic signs and avoid obstacles on its own. Implementation of Genetic algorithm

Using Genetic algorithm to provide optimal solution for “2-D-Jump-It game” whose goal is to move the character from the first cell to the last cell with the lowest total cost. Employee Database Design

Designed a software used for progression tracking and job scheduling for employee’s daily opeartion. Implemented in Python, SQL, and TCP/IP.

Multi-objective Optimization Approach to Find Biclusters.

Designed evolutionary based biclustering algorithm to find meaningful biclusters in gene expression data. Provided infor- mation about the effects of disease at genetic level. Key contributions include synthetic data generation, improvement of recovery and relevance measures.

PUBLICATIONS

J. Matta, J. Zhao, G. Ercal, T. Obafemi-Ajayi. “Applications of Node-Based Resilience Graph Theoretic Framework to Clus- tering Autism Spectrum Disorders Phenotypes”, Journal of Applied Network Science, Aug 2018.

Zhao, J., Adjeroh, D. Obafemi-Ajayi, T. (2018) Identification of Genotype Markers Linked to Phenotype Subgroups in Autism Spectrum Disorders.In IEEE-EMBS, International Conference on Biomedical and Health Informatics BHI. ( In submission)

Dale, J., Zhao, J.,Obafemi-Ajayi, T. (2018) Multi-objective Optimization Approach to find Biclusters in Gene Expression Data.In 2018 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE( In submission)

HONORS & AWARDS

Awarded with Research Assistant Scholarship in Missouri State University, Jan 2018 - present

Won 2nd Prize of the Outstanding Scholarship in Hangzhou Normal University, Sep 2012- June 2013



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