Ads-Click Prediction Model, Internship, Yahoo!

• Learned and utilized commands of MySQL, Hive and Pig
• Analyzed large data of users’ click behavior on different types of ads and extracted important features
• Used machine learning to implement a click prediction model of click behaviors with Vowpal Wabbit

Finding Maximal Cliques with Graph Partitioning

• Studied previous work of graph partitioning and implemented algorithms in C++ to find maximal cliques based on partitioned graphs

Head TA for Discrete Structures at Cornell University

• Managed grading rubrics
• Answered questions of course and homework during office hour
• Facilitated review sessions before exams

Lab Tutor at Colgate University

• Answered students’ questions and helped them understand substantially about Python and Java
• Leaded small groups to go over practice problems