New York, NY 979-***-**** firstname.lastname@example.org www.linkedin.com/in/jiajun-bao-b638a0170
New York University, Courant GPA:3.5 New York, NY
Master of Science in Computer Science 09/2018-05/2020 The University of Texas at Austin GPA:3.6 Austin, TX Bachelor of Science in Mathematics 09/2014-05/2018
Minored in Computer Science
Programming Languages: Proficient in Python, Java, familiar with SQL, Swift, R, C++, Scala, Ocaml
Tools and Utilities: Linux, Hadoop, Scikit-learn, Processing, AWS, Oracle databases, Xcode, Tableau PROFESSIONAL EXPERIENCE
Citibank New York, NY
Software Engineering Project 09/2019-05/2020
Developed trading bots using different machine learning models for bonds.
Employed Python packages including Pandas, Numpy, Matplotlib, and Tensorflow. The Q-learning model gives the best performance.
Built a complete infrastructure that enables the trading bots to track inventory and communicate with the simulated market through RabbitMQ.
ChinaOly Technology Hangzhou, China
Software Engineer Intern 05/2017-07/2017
Developed local police’s status web page with PostgreSQL database, Flask Python framework.
Used data analysis and SQL to assist the local police flag threats and high threat areas. PROJECTS
Parallelize PageRank algorithm, New York University Spring 2020
Built different parallel implementations of the PageRank algorithm using OpenMP and MPI.
Tested and compared the performance, scalability, and stability of different implementations under different scenarios.
With a million highly connected pages, the hybrid implementation of OpenMP and MPI achieve the best performance and reduce the time cost by 87.2%.
Operating System Simulation, New York University Spring 2019
Built Linker, CPU Scheduler, IO Scheduler, and Virtual Memory Management parts in OS using C++.
Implemented a two-pass Linker that resolves external symbol references and module relative address by global address. Implemented different replacement algorithms for the schedulers.
Created different simulations to test the implementations and compare the performance of different replacement algorithms.
Quora Insincere Questions detection, New York University Spring 2019
Built a 7-layer CNN-LSTM model using Pytorch to detect insincere question posted on Quora. Improved accuracy by 20% and AUC by 0.17 compared to baseline models(MNB, SVM).
Implemented preprocessing and feature extraction techniques using Keras and Gensim to encode every question.
Deployed a simple user interface using Tkinter to determine whether an input question is insincere. Real-time chat app, The University of Texas at Austin Spring 2018
Used Xcode(Swift) and Firebase to build a real-time chat app called Fastalk.
Developed functions such as picture uploading, group chat, font, and schema selections.
Built a login system and a powerful search function that can be used to search for friends or chat history.