I am a 4th year PhD student in the ECE Department at the University of Texas at Austin. I am fortunate to be advised by Sujay Sanghavi and Alex Dimakis. I got my BS degree in 2011 and MS degree in 2014 from Shanghai Jiao Tong University, advised by Xudong Wang.

My research interests include both theory and practice. For the theory part, I am interested in large-scale data analysis, linear algebra, optimization, and submodular function. For the practice part, I am interested in design and analysis of machine learning algorithms in distributed or parallel systems. I have used Apache Spark as my experimental platform.

Email: shanshan@utexas.edu


June 2017 - August 2017

    Software Engineer Intern | Google Research, New York City

    Representation Learning for High-Dimensioanl Sparse Data

    With Dmitry Storcheus, Felix Yu, Dan Holtmann-Rice, Afshin Rostamizadeh, and Sanjiv Kumar

Jan 2017 - April 2017

    Applied Scientist Intern | Amazon AI, East Palo Alto

    Joint Learning for Named Entity Recognition and Neural Machine Translation

    With Hyokun Yun and Anima Anandkumar


Single Pass PCA of Matrix Products
[Code on GitHub] [Spotlight Video] [Poster]
Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, and Alex Dimakis
To appear in NIPS 2016.

Leveraging Sparsity for Efficient Submodular Data Summarization
[Spotlight Video]
Erik Lindgren, Shanshan Wu, and Alex Dimakis
To appear in NIPS 2016.

Sparse and Greedy: Sparsifying Submodular Facility Location Problems
[Code on GitHub]
Erik Lindgren, Shanshan Wu, and Alex Dimakis
NIPS workshop OPT 2015.

Distributed Opportunistic Scheduling with QoS Constraints for Wireless Networks with Hybrid Links
Wenguang Mao, Xudong Wang, and Shanshan Wu
IEEE Transactions on Vehicular Technology, 2015.
An earlier version appears in Proceedings of the IEEE Globecom, 2013.

Performance Study on a CSMA/CA-Based MAC Protocol for Multi-User MIMO Wireless LANs
[Code on GitHub]
Shanshan Wu, Wenguang Mao, and Xudong Wang
IEEE Transactions on Wireless Communications, 2014.
An earlier version appears in Proceedings of the IEEE Globecom, 2013.

Information-theoretic study on routing path selection in two-way relay networks
Shanshan Wu, Wenguang Mao, and Xudong Wang
Proceedings of the IEEE Globecom, 2013.

Graduate Courses at UT-Austin

2016 Fall
CS395T Sublinear Algorithms (Prof. Eric Price)
    Course project: Rescaled JL Embedding

2016 Spring
EE381K-6 Estimation Theory (Prof. Haris Vikalo)
    Course project: A Survey of Fast Kernel Sketching Algorithms

2015 Fall
EE381V Advanced Probability in Learning, Inference, and Networks (Prof. Sanjay Shakkottai)
    Course project: Low-Rank Approximation of Matrix Product in One Pass
CS388G Algorithms: Techniques/Theory (Prof. Vijaya Ramachandran)
    Course project: PTAS for the Euclidean Traveling Salesman Problem

2015 Summer (Online courses provided by edX)
CS100.1x Introduction to Big Data with Apache Spark (Prof. Anthony D. Joseph)     Certificate
CS190.1x Scalable Machine Learning (Prof. Ameet Talwalkar)     Certificate

2015 Spring
EE381V Advanced Algorithms (Prof. Evdokia Nikolova)
    Course project: Signal Recovery from Permuted Observations
EE381K Information Theory (Prof. Alex Dimakis)

2014 Fall
EE380L Data Mining (Prof. Joydeep Ghosh)
    Course project: Ranking by Alternating SVM and Factorization Machine
EE381V Large-Scale Optimization (Prof. Sujay Sanghavi)
EE381J Probability and Stochastic Processes (Prof. Sanjay Shakkottai)

Teaching Experiences

Teaching Assistant, EE381V (Machine Learning for Large Scale Data), UT-Austin, Spring 2016.

Teaching Assistant, EE313 (Linear Systems and Signals), UT-Austin, Fall 2014.

Teaching Assistant, VE489 (Computer Networks), UM-SJTU Joint Institute, Summer 2013.

Teaching Assistant, VP140 (Physics I), UM-SJTU Joint Institute, Summer 2009.

Last update: Dec. 16, 2017