Raphael Chazelle

Data Science


Time Series Analysis
Signal Processing
Hadoop and Spark
Machine Learning


B.S. Computer Science, UMBC


New Hampshire

Recent Projects

Railroad Technology and Information Services
Next Generation Estimated Time of Arrival System
Built a highly-accurate system to estimate when cargo and intermodal trains will arrive on the North American major rail lines. The approach is implemented with a graph-style database in HBase and machine learning models developed on Spark.

Railroad Technology and Information Services
Predicting Failures of Train Wheels
Implemented advanced time-series analysis and machine learning to predict when wheels on trains would register a reading designating failure.

Technical Expertise

  • Python data stack: scikit-learn, pandas, numpy, Jupyter, others
  • Hadoop: Spark, Hive, HBase
  • Machine Learning: supervised and unsupervised learning
  • Time series analysis and signal processing
  • Amazon Web Services: EC2, EMR, S3
  • PostgreSQL, MySQL, SQL
  • Matlab, R