Zhishan Liu *** Taylor Ct

Mountain View, CA

+1-669-***-****

Curriculum Vitae acn27j@r.postjobfree.com

Education

2010–2013 M.S. in Precision Instrument, Tsinghua University.

2005–2009 B.A. in Mechanical Engineering, Beijing Institute of Technology.

Courses

- Machine Learning, Introduction to Algorithms, Data Structure and Algorithm Analysis,

Probability Theory, Practical Common Lisp, Structure and Interpretation of Computer

Programs

- Familiar with common machine learning algorithms, such as Linear Regression, Bayesian

Classification, Gaussian Discriminant Analysis, K-means

- Familiar with common data structures and algorithms, such as Binary Search Tree, Graph,

Hash, Heap, Sorting, Divide and Conquer, Dynamic Programming

Experience

2013–2014 Meituan.com, Data Engineer, Machine Learning and Data Mining Team.

(Meituan.com is China’s version of Groupon.com)

Query Recommendation

- Designed and implemented all components for the recommendation service, mainly

including extracting featurs from log using ETL, training model, updating data to

redis, and writing service program, etc.

- Increased CTR(click through rate) by 20% through improving association rule algo-

rithm. The main idea was to treat association rule similarity as a feature, and then

use cosine similarity to find more similar queries.

- Increased CTR by 30% by using GBDT(Gradient Boosted Decision Trees) algorithm

to resort candidate queries.

- Skills: Python, ETL, Go, Redis, MySQL, Hive SQL, Thrift, Data Mining

Deal Recommendation

- Increased CTR by 15% through improving association rule algorithm to remove noise

in data, which could figure out the most probable deal branch based on users’ single-

branch-deal visiting history, and then remove multi-branch noise.

- Wrote a web application using tornado to show best cases and bad cases of deal

recommendation, which updated daily.

- Wrote different SQL to monitor performance of deal recommendation based on dif-

ferent standards, such as performance of cities, performance of classes, etc.

- Skills: Python, ETL, Redis, MySQL, Hive SQL, Recommendation System

Projects (https://github.com/liuzhishan/practice)

2014 Implemented PLSA(Probabilistic Latent Semantic Analysis) using Go

Given a set of articles, I used EM(expectation maximization) algorithm to compute model

parameters of PLSA, such as topic distribution and word distribution, and used goroutine

to compute parameters concurrently.

2014 Implemented decision tree using Go

Given a set of labeled data, I used mean square error as the regression criterion to build

decision tree. By presorting all samples according to one feature, the implementation

reached a O(Nf eatures Msamples (lgMsamples )2 ) time complexity.

2014 Solved 2-d k-nearest problem (Quora Programming Challenges) using kd-tree

The challenge asks programmers to find k-nearest points for every query, given N 2-d

points, k and Q query points(N and Q are in range [1, 10000]). I built kd-tree based on

given points and used priority queue to store nearest points, and then used the best-bin-

first method/recursive search method to look for the answer, which proved to be much

faster than the commonly used linear algorithm.

Skills

Domain Machine Learning and Data Mining

Languages Python, Go, C++, SQL, Common Lisp

Languages

English Be able to read English professional and technical books and take open courses without

difficulty.

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