Computer Science Assistant

Shilin DING

CURRICULUM VITAE

Department of Statistics, UW-Madison

**** ********** ***, *******, **, 53706

abo1wt@r.postjobfree.com://www.stat.wisc.edu/~sding

Phone: 608-***-****

Education

Univ of Wisconsin-Madison

Ph.D Candidate in Statistics

20082012

Advisor: Grace Wahba

Univ of Wisconsin-Madison

M.S. in Computer Sciences

2009-2011

Stanford University

Visiting Student, AI Lab, Department of Computer Science

2007

Directed by Prof. Andrew Ng

Tsinghua University

M.S. in Computer Science

2005 2008

Advisor: Xiaoyan Zhu

Nanjing Univ of Sci. & Tech.

B.S. in Computer Science

20012005

Work

05/201108/2011SDE Intern, Microsoft SQL Server Business Intelligence, Redmond, WA.

Mentor: Brad Daniels

07/200703/2008Research Intern, NLC Group, Microsoft Research Asia, Beijing, China.

Mentor:

Chin-Yew Lin

Research/Project Experience

UW Madison Research Assistant, Statistics Department

2008 - Focus: Non-parametric Statistics, Graphical Model

Work: Graph Structure Learning; Non-parametric learning based on vector

features and similarity; Distance Metric Learning for dimension

reduction; Multi-task learning; Social Network

iPhone Medical Image Development

Developed an app to retrieve electrocardiograph data, heart rate, and etc

Microsoft SQL SDE Intern, Analysis Services Group

Server Business Focus: Analysis Services Engine

Intelligence Work: Improving the parallel processing of large data sets

2011

Microsoft Research Intern, Natural Language Computing group

Research Asia Focus: Web Knowledge Mining, Question Answering, Parsing

2007 2008 Work: Identifying contextual information in interactive dialogues to retrieve

answers by Graphical Models; Question and Answering system for online

service; Parsing in context free grammar

Stanford Visiting Scholar, AI Lab, Department of Computer Science

University Focus: Stanford WordNet Project

2007 Work: Augmented Wordnets based on semantic taxonomy induction

Tsinghua Research Assistant, Department of Computer Science

University Focus: Machine Learning, Pattern Recognition, NLP

2005 2008 Work: Ontology-based biological relation extraction, evaluation and

integration;

semi-supervised model; Named Entity Recognition

Tsinghua Team leader in BioCreAtIvE 2006 and ranked top 1 in the competition

University Work: Proposed and developed a profile-based approach to extract protein

2006 interaction by incorporating evidence from the full text

Shilin DING

CURRICULUM VITAE

Research Interest

Theoretical end: Machine Learning, Graphical Models, High-Dimensional Data, Optimization

Application end: Information Extraction & Retrieval, Data Mining, NLP, Web Intelligence

Programming

Proficient: C, C++, C#, Java, MATLAB, R

Familiar: Python, Perl, Pascal, Assembly, SQL, SAS

Platforms: Windows, Unix/Linux

Patent

1. Gao Cong, Chin-Yew Lin, Shilin Ding. Summarizing Online Forums into Question-Context-

Answer Triples. Application NO. 201********

Publications

1. Shilin Ding, Grace Wahba, Xiaojin Zhu. Learning Higher-Order Graph Structure with

th

Features by Structure Penalty. To appear in 25 Annual Conference on Neural Information

Processing Systems (NIPS 2011).

2. Xinying Song, Shilin Ding, Chin-Yew Lin. Better Binarization for the CKY Parsing. In

th

Proceedings of 13 Conference on Empirical Methods in Natural Language Processing (EMNLP

2008).

3. Shilin Ding, Gao Cong, Chin-Yew Lin and Xiaoyan Zhu. Using Conditional Random Fields

to

th

Extract Contexts and Answers of Questions from Online Forums . In Proceedings of 46

Annual Meeting of the Association for Comput ational Linguistics (ACL 2008)

4. Minlie Huang, Shilin Ding, Hongning Wang, and Xiaoyan Zhu. Mining Physical Protein-

protein Interactions from Literature. Genome Biology, 2008, 9(Suppl 2): S10.

5. Hongning Wang, Minlie Huang, Shilin Ding, and Xiaoyan Zhu. Exploiting and Integrating

Rich

Features for Biological Literature Classification. BMC Bioinformatics, 2008; 9(Suppl 3):

S4.

6. Shilin Ding, Minlie Huang, Hongning Wang, and Xiaoyan Zhu. Profile-feature Based

Protein

th

Interaction Extraction from Full-Text Articles. In Proceedings of the 7 BIOKDD Workshop

in

th

the 13

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