1. (Emma)Tao Liang
E-mail: tliang@caltech.edu Mobile: (626)7874931 1028 East Del Mar Apt 205, Pasadena, CA,91106
Education
California Institute of Technology, 2015-Present (Dec expected)
Master of Science: Electrical and Electronic Engineering
• GPA: 4.0
• Database, Communication Networks, Internet of things, Machine Learning Data Mining, GPU Programming
Beijing University of Posts and Telecommunications(BUPT) & Queen Mary University 2011-2015
of London (QMUL) Joint Program, BS Major: Telecommunications Engineering with Management
• GPA: 90.5/100, Ranked 8/381, 95% of the courses are A
• Data structure, Java, C, advanced network programming, Internet application, Software development
Work Experience
• Connectivity Team Software Engineering Intern, iRobot, Boston (Python, AWS, C) Summer 2016
Used python code automation testing for validating the schema and checking the message publish to the AWS IoT thing
shadow. Manual test the service discovery of AWS through mqtt.fx, rsim and minicom. Implemented Http Client by C.
• Web Design Intern, 21st Century Education, Inc, Silicon Valley (HTML) Summer 2013
Designed and implemented web applications for company’s websites, including 21st Century Education, Jaymes Hines,
Startup Edutech and parents4kids.com, using PHP and HTML. Developed databases for keeping customer information.
• Market Research Intern, Microsoft, China Apr.-May, 2013
Analyzed the market. Collected and processed data using database and drew conclusions to the degree of satisfaction
about office 365 Home.
IT Skills
Experience with: Java, Python, C, MySQL, Matlab, Opnet, HTML Familiar with: JavaScript, VHDL, Assembly, Wireshark
Research and Projects
Projects at California Institute of Technology Sep. 2015 ∼ Jun. 2016
• Matrix Factorization (C, GPU)
Used C implement latent factor model based on matrix factorization on CPU, batch size GPU and sequential addressing
GPU. Tried accelerating different strategies, traded off between accuracy and runtime
• Shakespeare Poem Generator (Python, Machine learning, HMM)
Used Python to train three unsupervised Hidden Markov Models on the entire corpus of Shakespeare’s sonnets. The
result HMM was used to generate a new poem that Shakespeare may have written. Added the rhyming dictionary and
stressed state to improve the rhyme and meter of the poem.
• Sentiment Analysis (Python, Machine learning)
Implemented Machine Learning Data Mining to build up suitable models to predict the opposition or support sentiment
from speech by Python. Trained and tested various models including decision tree, random forest, bagging, adaboosting.
Employed different techniques including data pre-processing, cross-validation, and ensemble methods.
• Network Simulator (Python, TCP/IP)
Implemented different TCP congestion control algorithms including TCP Reno and FAST-TCP. Compared the
performance of them under different topology
• FreshenUp (Java, IOT)
Internet of things project: built up an air qualifier hardware with modular design and mobile app in Java for customer.
Customized sensor detected different air composition can be selected and added to hardware. And the mobile app can
remote monitor the change of air composition and provide alarm and suggestions.
Research Assistant at BUPT & QMUL Oct. 2012 ~ Jun. 2015
• Adjust Classified Hello Scheme (C, Opnet)
Designed a new scheme to improve the efficiency and energy consuming of the Hello Message in AODV. Designed
codes and run simulations in Opnet for validation.
• Design and implementation of DNS (C, Wireshark)
Designed a DNS server and client-based Linux commands using C to achieve Chinese domain name resolution.
Implemented functionalities to support selected query types, set UDP/TCP connection between client and server, capture
and identify packets in Wireshark, handle errors and retry.
• Enhanced Associativity-Based Multicast Routing Protocol (C, Opnet)
Proposed an improved scheme based on Associativity-Based Ad Hoc Multicast Routing (ABAM) and Cognitive Radio
Mobile Ad Hoc Networks (CR MANET) and further improved the stability of the multicast tree. Designed algorithms for
tree formation and node mobility handling. Developed an OPNET based platform for simulations and validated that the
new scheme, with higher link break resistance, provides much better performance compared to ABAM when nodes are
moving in CR MANET.
Ø The paper published on 25th IEEE International Symposium on Personal, Indoor and Mobile Radio
Communications (PIMRC), Washington DC, 2014