Ting Liu

The printable version of my resume: [PDF] [PS]

Objective

To find a permanent position in research labs, research-oriented companies, or financial corporations.

Research Interests

My research interest lies in machine learning and data mining, with focus on nonparametric statistics, memory-based learning and kernel-based learning. I am currently interested in designing high-performance algorithms that solve fundamental tasks (such as k nearest neighbor and support vector machine) on massive and high-dimensional data sets. I am also interested in solving real-world problems, such as content-based vedio segmentation, image retrieval, biological problems and financial modeling problems.

Education

Carnegie Mellon University,Pittsburgh, PA. 2001-Present
Ph.D. Candidate in Computer Science Department.
Adviser: Andrew W. Moore

Tsinghua University, Beijing, P.R.China, 1997-2001.
B.E. in Computer Science, June 2001.

List of Publications (thesis related)

T.Liu, A. W. Moore, A. Gray.
New Algorithms for Efficient High-Dimensional Nonparametric Classification.
Accepted to Journal of Machine Learning Research.

T.Liu, A. W. Moore, A. Gray.
New Algorithms for Efficient High-Dimensional Nonparametric Classification.
To appear in Chapter 4, Nearest-Neighbor Methods in Learning and Vision.

J. Adcock, A. Girgensohn, M. Cooper, T. Liu, E. Rieffel, L. Wilcox.
FXPAL Experimentx for TRECVID 2004.
In Proceedings of TRECVID 2004, March 1, 2005.[PDF]

T.Liu, A. W. Moore, A. Gray, Ke Yang.
An Investigation of Practical Approximate Nearest Neighbor Algorithms.
In proceedings of Neural Information Processing Systems(NIPS 2004), Vancouver, BC, Canada, 2004.[PS][PDF][Dataset]

T.Liu, Ke Yang, A. W. Moore.
The IOC algorithm: Efficient Many-Class Non-parametric Classification for High-Dimensional Data.
In proceedings of the 10th ACM SIGKDD conference(KDD 2004),Seattle,WA,2004.[PS][PDF]

A.Gray,P.Komarek,T.Liu,A.W.Moore.
High-Dimensional Probabilistic Classification For Drug Discovery .
In proceedings of COMPSTAT 2004, 16th Symposium of IASC,Prague,2004.[PS][PDF]

T.Liu, A. W. Moore, A. Gray.
Efficient Exact k-NN and Nonparametric Classification in High Dimensions.
In Proceedings of Neural Information Processing Systems, 2003.[PS][PDF]

Y. Qi, A. Hauptman, T.Liu.
Supervised Classification for Video Shot Segmentation.
In proceedings of IEEE International Conference on Multimedia & Expo, 2003.[PDF]

List of Publications (something else I did for fun)

C. Lin, Z. Shan, T. Liu, Y. Qu, F Ren.
Modeling and Inference of Extended Interval Temporal Logic for Nondeterministic Intervals.
In IEEE Transactions On Systems, Man, and Cybernetics, 2005, 35(5):682-696.

T.Liu, C. Lin, W. Liu.
Linear temporal inference of workflow management system based on timed Petri net models.
In Acta Electronica Sinica, Feb. 2002, 30(2): 245-248.

T.liu, C. Lin, W. Liu.
The inference engine of extended interval temporal logic.
In Chinese Journal of Computers, 2002, 25(6):637-644.

C. Lin, T.Liu, Y. Qu.
Extended interval temporal logic for undetermined Interval:modeling and linear inference using time Petri nets.
In Chinese Journal of Computers},2001, 24(12):1299-1309.

Professional Experiences

Summer Intern (June, 2005 -- Oct, 2005): Google Inc.

My work in Google mainly focused on near-duplicate image search problem. By extending a previous research project, we developed very efficient and scalable algorithm capable of finding approximates nearest neighbors and clustering more than 1 billion images.
References: Dr. Henry Rowley, Dr. Chuck Rosenberg

Summer Intern (June,2004 -- Sept,2004): Fuji Xerox Palo Alto Laboratory

My work in FXPAL mainly focused on building a simple general framework for automatic Video Shot Segmentation, and we submit our result to TRECVID04 evaluation, and ranks 2nd among 35 submissions from world-wide participants.
Reference:: Dr. Matthew Cooper, Dr. Eleanor Rieffel

Technical Consultant (Sept,2004 -- Sept, 2005): Fuji Xerox Palo Alto Laboratory

We extend our work of shot segmentation to story based segmentation.
References: Dr. Matthew Cooper, Dr. Eleanor Rieffel

Patents

M. Cooper, T. Liu, E. Rieffel
Media Segmentation Combining Similarity Analysis and Classification, Filed 11/12/2004

Research Experience

Image Retrieval (On going)
We are working on detecting whether an image is a near duplicate or a sub image of a database of images.
References: Prof. Martial Hebert, Ke Yan.

3-D models for Computer Vision
One popular approach to recognizing objects in 3D data is to use semi-local shape signatures to find similarly-shaped regions between a scene and objects from a model database, conventional algorithm is slow, we are investigating the application of our new data-structure to further enhance recognition speed.
References: Prof. Martial Hebert, Dr. Daniel Huber.

Efficient Nonparametric Classification in High Dimensions
We designed new ball tree algorithms to achieve non-approximate acceleration of high dimensional nonparametric operations such as k nearest neighbor classifiers and the prediction phase of Support Vector Machine classifiers.
References:Prof. Andrew W.Moore, Prof. Alexander Gray.

Pfizer Global Research and Development
Computational chemistry and proteomics for drug design. High-throughput screening (metric learning, classification).
References: Prof. Andrew W. Moore, Prof. Alexander Gray.

Course Projects

Computer Vision. Sep. 2004 -- Dec. 2004

Shape Matching and Object Recognition Using Shape Contexts.
We implement a novel approach to measure similarity between shapes and exploit it for object recognition.
Reference: Prof. Martial Hebert.

Computer Network. Sep. 2002 -- Dec. 2002

Geographic Routing with Imperfect Positioning for Wireless Networks.
We proposed a new routing protocol that works well in ad-hoc wireless networks with highly dynamic topology and imprecise geographic position information.
Reference: Prof. Srini Seshan.

Computer Architecture. Sep. 2001 -- Dec. 2001

Evaluating Dynamic Prefetching in a Software DSM (Distributed Shared Memory) system.
We proposed and evaluated a dynamic prefetching algorithm in JIAJIA (a software DSM system).
Reference: Prof. Todd C. Mowry.

Teaching Experience

Teaching Assistant for "15-381: Artificial Intelligence", Spring 2005, Carnegie Mellon University.

Teaching Assistant for "15-780/16-731, Anvanced AI concepts / Fundamentals of AI for Robotics", Spring 2004, Carnegie Mellon University.

Awards and Hornors

Carnegie Mellon University Doctorate Fellowship, 2001 -- Present.

Graduated with Honor from Tsinghua University, 2001.

Tsinghua-ISS Scholarship for outstanding students, 2000.

Beijing outstanding college student of the year, 1999.

Tsinghua-Sony Scholarship for outstanding students, 1998.

First Prize in National Mathematics Contest (China), 1995.

References

Available upon request.