The document is a resume for Yu Wang that outlines his education and work experience in software engineering and computer science. It details projects implementing operating systems, distributed systems, machine learning algorithms, and localization applications. It also lists relevant coursework, programming languages and technologies, and academic awards.

1. Connecticut CT 06511 YU WANG
(510) 710-2326
yu.wang.yw486@yale.edu
EMPLOYMENT & PROJECTS
Software Engineer, Intern Barclays Capital Investment Banking Division June 2014 – Aug 2014
 Developed disaster recovery system using Java, which reinjected missing orders into trading system under disaster scenario,
completed in half the allocated time.
 Devised hand-fill solution interface for traders to import orders manually.
 Implemented various new features in C#, including post-trade signaling and auto-highlighting.
Unix Style OS Fall 2015
 Implemented physical memory management, virtual page translation, thread-process management, trap handling and timer
interrupt, which allowed the execution of kernel to be preempted.
 Simulated producer and consumer buffer problem on QEMU with multicore CPU using schedulers and locks.
 Implemented a file system similar to Fast File System with multi-level indexing.
 Implemented inter-process communication with message buffer and shell functions in kernel mode for better responsiveness.
Multi-PAXOS in Cloud Computing Fall 2015
 Implemented PAXOS algorithm for a group of computers to agree on a single value as long as a majority of the machines
running.
 Added heartbeat message and leader election mechanism for the system to decide on a series of values.
 Implemented distributed consistent and durable key value pair application based on the above.
Image Classification With Machine Learning Techniques Fall 2014
 Implemented Ensemble Projection in MATLAB and combined it with HOG feature selection. Explored and analyzed PCA and
Ensemble Projection on image classification tasks on various categories of images, and justified using Ensemble Projection
instead of PCA. Created an ensemble method by connecting MATLAB and WEKA in java interface.
 Implemented Deep Neural Network in MATLAB. Improved the performance by 5 percent by applying grid search to select
optimal number of layers. Combined Neural Network, dimension reduction and feature extraction techniques and achieved 54
percent accuracy on classifying 10 categories of images.
Indoor localization with iBeacon Mar 2014 –June 2014
 Developed Android application for iBeacon signal testing and data sampling.
 Constructed regression model of distance function with respect to measured attributes, implemented new distance function
based on model, with original prediction accuracy improved by 20 percent.
Independent Study Sept 2014 – Dec 2014
 Implemented triangle decomposition algorithm on Stanford Network Analysis Platform using C++.
 Guided by mathematical insight, tuned triangle decomposition algorithm to handle hierarchical community detection under
the context of threshold graph. Theoretical computer science proofs with implementation of practical heuristics, which allow
communities obtained to have zero error on good points.
EDUCATION
Connecticut, CT Yale University Fall 2015 – May 2016
 MSc in Computer Science. GPA 3.25/4; major GPA: 3.7/4
 Graduate Coursework: Operating System, Cloud Computing, Spectral Graph Theory, Algebraic Topology
Hong Kong HKUST, Exchange in CMU Fall 2011 – May 2015
 BSc in Math and Economics & Computer Science. GPA: 3.7/4.3, Computer Science GPA: 4/4.3
 Undergraduate Coursework: Operating Systems; Advanced Algorithms; Machine Learning; Graphics; Computer Architecture;
Advanced Probability; Stochastic Process, Analysis, Abstract Algebra, Calculus on Manifold
ADDITIONAL EXPERIENCE AND AWARDS
 Spring 2015: The 3rd HKUST UG Senior Math Competition first runner-up.
LANGUAGES AND TECHNOLOGIES
 C++; C; Java; Python; Mathematical Modeling; Machine Learning; Distributed System; MATLAB; Visual Studio; Eclipse