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Ranran Cao

Actively seeking for a Software Engineer/Data Analyst position

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About Me

  • Project experiences: Big Data, Machine Learning / Deep Learning, Mobile Development(Android).
  • Languages: Java; Python; SQL; HTML/CSS/JavaScript. Tools: Git/Github; Linux; Docker; Hadoop; MapReduce; HDFS; Hbase; MySQL. Jupyter Notebook; NumPy; Pandas; Scikit-learn; TensorFlow; Google Cloud;

Experience

University of California, Riverside

Deep Learning Research Assistant

Deep Learning Series Projects

  • Implemented the neural style transfer algorithm to generate novel artistic images.
  • Constructed the building blocks of ResNets and combined them to develop and train a neural network for image classification(Residual Networks).
  • Developed object detection on a car detection dataset using YOLO model and tackled bounding boxes problem(Autonomous driving – Car detection).
  • Implemented the triplet loss function and used a pre-trained model to map face images into 128-dimensional encodings.
  • Used these encodings to perform face verification and face recognition.

Hanbacks Electronics

Software Engineer Intern

  • Researched ‘Obstacle Avoiding’ and ‘Orientation Guiding’ for vehicle safety enhancement using HBE-SMARTCAR platform and Android Studio.
  • Conducted C++ programming to implement the method of PWM Control and Track Projection.
  • Improved the performance of tracking by 30% through optimizing the tracking algorithm.
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Education

University of California, Riverside

Sept 2015 - June 2017

Master of Science in Electrical Engineering

Coursework: Artificial Intelligence, Data Structures and algorithms, Convex Optimization, Wireless Network & Mobile Computing.

Beijing Union University

Sept 2011 - June 2015

Bachelor of Science in Automation(concentration in Internet of Things)

Projects

Big Data: Movie Recommender System

  • Developed a movie recommender system using Netflix dataset (1G) and the Hadoop platform (Docker, HDFS, MySQL).
  • Calculated movie rating matrix from Netflix dataset using collaborative filtering algorithm.
  • Implemented MapReduce Java code for co-occurrence matrix generation and multiplication of co-occurrence matrix and movie rating matrix to obtain recommendation list.
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Hadoop Page Rank Project

  • Using MapReduce in Hadoop with Java to realize Google page rank algorithm (Docker, Linux).
  • Established transition matrix as web page relationship representation using wiki data, with the help of MapReduce in huge matrix multiplication.
  • Established the final rank of webpages by the PageRank algorithm, involving HDFS.
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Machine Learning: Eight-Puzzle Solver and KNN Classifier Projects

  • Solved the Eight Puzzle problem by Java using Uniform Cost Search, A* with the Misplaced Tile heuristic search and A* with the Manhattan Distance heuristic search respectively.
  • Used Pandas to deal with missing data and implemented a Nearest Neighbor Classifier by Python using forward selection algorithm and backward elimination algorithm.
  • Improved the classification accuracy for big dataset from 90% to 93% by integrating annealing algorithm with backward selection algorithm.
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Embedded System: Smart Home Project

  • Explored inter-networking and capabilities of Smart Home devices, as well as functions of remote control as part of ‘Internet of Things’ project, using HBE-Zigbex, TinyOS, NesC and Cygwin.
  • Implemented C++ programming on host computer to realize serial communication with wireless sensor network nodes.
  • Implemented NesC programming on WSN nodes to realize Zigbee 2.4G 802.15.4 communication with wireless communication and control modules.

Skills

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