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About Me

Hi! I'm Peilun Li, a second-year graduate student at School of Computer Science, Carnegie Mellon University. I'm pursuing Master of Science in Intelligent Information Systems under Language Technologies Institute.
I'm passionate about machine learning, deep learning and their applications in real-world challenges. Currently I'm conducting research on machine learning (especially deep learning and vision) and distributed systems under the supervision of Prof. Eric Xing. Before coming to CMU, I received my Bachelor's degree (SE) from Beihang University and worked with Prof. Zhenwei Shi on deep learning applications.


Carnegie Mellon UniversityAug 2016 - Dec 2017

Master of Science in Intelligent Information Systems

Selected Courses: Machine Learning (PhD-level), Language and Statistics (PhD-level), Machine Learning with Large Datasets, Search Engines, Machine Learning for Text Mining, Multimedia Databases and Data Mining, Deep Learning.

GPA: 4.08/4.33

Beihang UniversitySep 2012 - Jul 2016

B.E. in Software Engineering, with dual B.S. degree in Mathematics

Core Courses: Programming Languages, Data Structures, Algorithms, Database, Advanced Mathematics, Discrete Mathematics, Linear Algebra, Probability and Statistics.

Rank: 3/136 Overall GPA: 91.1/100 (3.83/4) Major GPA: 93.2/100 (3.95/4)

Professional Experience

Data Science & Engineering, Analytics Group, ZillowMay 2017 - Aug 2017

Software Development Engineer, Machine Learning Intern

  • Implemented a widely-applicable high-efficiency fault-tolerant user-friendly distributed pipeline to extract features for large scale datasets (e.g., 500 million images) using Caffe and AWS (EC2, S3, CloudFront).
  • Visualized deep learning models using multiple methods (e.g., t-SNE) to find patterns and helped improve the models.
  • Researched on deep neural random forest and implemented a delicate approach using TensorFlow.
  • SAILING lab, Carnegie Mellon UniversitySep 2016 - present

    Research Assistant, Supervised by Prof. Eric Xing

  • Implemented a Keras interface to simplify the usage of Poseidon TensorFlow.
  • Implemented data parallel and data preprocessing functions for large scale distributed machine learning.
  • Contributed to DyNet, an open source project aimed at dynamic neural network.
  • LEVIR lab, Beihang UniversitySep 2015 - Jun 2016

    Research Assistant, Supervised by Prof. Zhenwei Shi

  • Analyzed the pros and cons of both conventional pattern recognition methods and deep learning methods for scene text detection and recognition.
  • Implemented a deep learning approach for scene text detection and recognition with 92.65% accuracy on ICDAR 2003 dataset, which outperformed most conventional pattern recognition methods and many deep learning methods.
  • Database Research Group, University of MichiganApr 2015 - Aug 2015

    Research Assistant, Supervised by Prof. Barzan Mozafari

  • Added Octave support for DBSeer (a database intelligence framework) and optimized performance by reimplementing core codes using Julia, which reduced more than 90% time of slow executions, e.g., from 942.6s to 9.1s.
  • Implemented a prototype middleware to predict database schema for big data, so that database users can take advantage of the benefits of a relational database without formulating a schema beforehand.
  • Implemented the “schema-later” method that automatically performs necessary schema modifications for unexpected data elements or requirement changes, so that big data users can store and manipulate big data easily and efficiently.
  • Skills

    Having competed in ACM-ICPC Asia Regional Contests, I have strong ability to learn new technologies in a very short time and apply them to real world projects.


    • Python
    • C/C++
    • Java
    • C# .NET
    • SQL
    • MATLAB
    • PHP
    • Objective-C
    • Octave
    • Julia
    • LaTeX


    • TensorFlow
    • Keras
    • Caffe
    • DyNet (Contributor)
    • Git
    • Hadoop


    • Software Engineering
    • Machine Learning
    • Deep Learning
    • Mathematics
    • Data Structures
    • Algorithms Design
    • Databases


    A Brief History of Information TechnologySep 2016

    Peilun Li, Yunxiang Lu

    Beijing: Tsinghua University Press [801-821-3409]

    Introduction to Computer ScienceAug 2016

    Peilun Li, Yunxiang Lu

    Beijing: Publishing House of Electronics Industry [(931) 441-2943]

    Computer ConceptsApr 2015

    Peilun Li, Yunxiang Lu

    Reprinted within 3 months.

    Sixth Edition available in Sep 2017!

    Beijing: Tsinghua University Press [Press Link (in Chinese)]

    Selected Awards & Honors

    1st Prize of Innovative TechnologyDec 2014

    School of Software, Beihang University

    Only 1 team per year can win this prize.

    Bronze Medal in 39th ACM-ICPC Asia Shanghai Regional ContestDec 2014


    Bronze Medal in 39th ACM-ICPC Asia Guangzhou Regional ContestNov 2014


    1st Prize in 24th "Feng Ru Cup" Student Academic Science and Technology CompetitionMay 2014

    Beihang University

    “Feng Ru Cup” is an academic, scientific and technological innovation competition with the highest reputation and widest participation of students at Beihang University. Only Top 3% teams can win 1st prize

    Outstanding Student Leader of Hebei Province

    Hebei Province, China

    Top 0.1%

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    Last Updated: Sep 13, 2017