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  • Lead software engineer with 6+ years of hands-on experience in IT industry  
  • Hands-on experience with Cloud and Big Data related concepts and ecosystems
  • 6+ years delivering production code in object-oriented languages such as C++, Python, and Java
  • Good Knowledge of data structures and algorithms
  • Highly motivated with superior analytical, organizational and communication skills
  • Willingness to learn, seek for new challenge, and able to adapt new environment
  • Ability to work as a team member as well as individual with a minimal supervision


  • Programming languages: C++, C#, Python, Java
  • Cloud Platform: Amazon Web Services, Google Cloud
  • Big data technologies: MapReduce, Spark, Kafka, Hadoop, HDFS
  • Databases and Tools: MySQL, MongoDB, Google BigTable
  • Architecture/Design Pattern: Singleton, Factory, Façade, MVC, MVVM, 
  • Operating Systems: Windows, Linux (Ubuntu, Fedora)
  • IDEs: Visual Studio, Intellij IDEA, Pycharm, Visual Studio Code
  • SCM Tools: SVN, Git, Github, TortoiseSVN

Work Experience

Jan 2017Present

Lead Software Developer - Cloud Migration

Presagis - CAE

Lead a team of developers towards cloud migration of an existing application and implementation best practices

Achievement highlight:

  • Decoupled monolithic application into micro-services and ensure design is taken scalability, low latency, and fault tolerance into consideration
  • Leveraged RESTful API, RPC, and brokered messaging as inter-process communication styles between micro-services
  • Participated in the design of services discovery and automatic fail-over recovery strategies
  • Deployed the new architecture to on-premise infrastructure as well as AWS Cloud platforms
  • Analyzed and monitor performance bottlenecks and key metrics to optimize software and system performance
  • Designed user manuals, FAQs, detailed product specifications and project reports
  • Worked closely with technical account managers and support teams t ensure operational integrity of the solution

Technologies used: Python, Flask, JSON, gRPC, protobuf, RabbitMQ, AWS

Sep 2011Dec 2016

Software Developer

Presagis - CAE

Design, develop and maintain high fidelity correlated 3D terrain generation tools

Achievement highlight:

  • Designed and developed the backend components of distributed build architecture 
  • Implemented image texture classification using machine learning algorithms in supporting IR sensor workflow
  • Handy working experience in applying geometry computation algorithms to create 2D based map features (e.g. road network)
  • Drove continual improvement to system architecture (64 bit migration, Visual Studio migration)
  • Developed automating pipelines by using continuous delivery tools including Jenkins
  • Bug fixing and debugging in C++, C# and Python
  • Worked closely with remote team members on a regular basis

Technologies used: C++, C#, Python, .NET, Geospatial Data Abstract Library (GDAL),  Computational Geometry Algorithm Library (CGAL), OpenCV, Visual Studio, OpenGL

Research Projects

Sep 2017Jan 2018

Analysis of Financial Credit Risk using Deep Learning Models


  • Applied data pre-processing techniques (filtering, scaling, normalization, one-hot encoding)
  • Applied Synthetic Minority Over Sampling Technique (SMOTE) to adjust class distribution
  • Fine-tuned hyper-parameters of the models using k-fold cross validation
  • Trained multiple neural network models (DNN, CNN)  with result of high accuracy and low log loss
  • Validated the models with domain specific metrics (KS, PSI AUROC)
  • Made Prediction with a new dataset and result shows 89% accuracy

Technologies used: Tensorflow, sklearn, numpy, Python 


Sep 2014Sep 2017

Master of Applied Science

Concordia University, Montreal, Canada

Research topics: Streaming data algorithm design for big data analysis


    • Designed and Implemented trajectory pattern mining framework by leveraging parallel computing technologies
      • Proposed various data partition methods (Fixed-Grid, K-D tree)
      • Proposed clustering algorithms (point-to-polyline, polyline-to-polyline, DBSCAN) to discover density reachability between trajectories
      • Implemented batched-based and streaming-based trajectory pattern discovery framework using Apache Spark Core and Streaming APIs
      • Utilized Apache Kafka with Spark integration for streaming data ingestion
      • Optimized system performance by minimizing data shuffling and Spark workflow tuning
      • Experimentally evaluated the performance of proposed solution on Microsoft GeoLife dataset 

Technologies used:  MapReduce, HDFS, Kafka, Spark (Streaming), AWS EC2 clusters, AWS S3 bucket.


Programming on the Cloud (COEN691P) - Cloud based Image Processing Service


    • Designed and implemented RESTful API for interacting with the image processing service
    • Developed an image processing service which connects to Cloudinary API as a backend
    • Connected Facebook API using OAuth for user authentication
    • Connected Dropbox using its Core API for images/metadata storage
    • Designed NoSQL data model and implement with Google datastore
    • Designed and implemented an web UI using HTML, CSS, Javascript
    • Debugged and deployed the application to Google App Engine

Technologies used: REST API, OAuth, Google App Engine, Facebook API, Dropbox API, Google datastore, HTML5, CSS3, JQuery, AJAX, Javascript

Relevant coursesProgramming on the Cloud, Model Driven Software Engineering, Microprocessors and their applications, Foundations of Cryptography, Optical Networking

Sep 2007Sep 2011

Bachelor of Computer Engineering

Concordia University, Montreal, Canada

Relevant Courses: Embedded System and Software Design, Communication Network and Protocol, Software Process, Microprocessor Systems,  Software Testing and Validation, Real Time System Design, Computer Graphics

Publications and Presentations

  • Yongyi X., Yan L., Chuanfei X. (2016, December). "Parallel Gathering Discovery over Big Trajectory Data", IEEE International Conference on Big Data, Washington, DC.
  • Yongyi X., Chuanfei X., Yan L. (2016, December). "Implementing Trajectory Data Stream Analysis in Parallel", IEEE International Conference on Big Data, Real-time and Stream Analytics in Big Data workshop


  • IEEE International Conference on Big Data, student travel award, 2016
  • Bravo Zulu Award - Presagis, 2015
  • Computer Engineering Capstone Team Project 3rd place (out of 10 teams), Concordia University, 2011