Experience

Member of Technical Staff-Research

AT&T Labs-Research, Bedminster, NJ / Oct. 2007 - Present

Research focus includes data storage for big data and cloud computing, 3D visual content generation and processing, joint source-channel coding, and error-resilient compression theory and algorithms.

Postdoctoral Researcher

EPFL, Lausanne, Switzerland / Sep. 2005 - Sep. 2007

Research focus included coding problems in multiuser communication systems, and image and video coding.

Education

Cornell University, Ithaca, NY

PhD Electrical and Computer Engineering / Aug. 2005

Tsinghua University, Beijing, China

Bachelor of Engineering (BE), Electronic Engineering / Jul. 2000

Awards

AT&T Key Contributor Award

For technical contribution in AT&T / 2010, 2011

Liu-Memorial Award, Cornell University

For excellence in graduate study and research / 2004

Selected Publications

Characterizing the rate-region of the (4,3,3) exact-repair regenerating codes

C. Tian, accepted, JSAC on Communication Methodologies for the Next-Generation Storage Systems

A fundamental problem in distributed data storage systems is whether the capacity of the functional-repair regenerating codes is the same as the exact-repair version. This paper answers in the negative through a novel computer-aided approach.

Optimality and approximate optimality of source-channel separation in networks

C. Tian, J. Chen, S. N. Diggavi and S. Shamai, IEEE Trans. Inform. Theory, Feb. 2014

Underlying the layered architecture of most communication networks (e.g., Internet) is the optimistic assumption that such a separation does not incur any loss, which is however not generally true in many multiuser scenarios. Fortunately, here we show for several general classes of communication networks, separation is either optimal or close to optimal.

Accelerated bilateral filtering with block skipping

C. Tian, and S. Krishnan, IEEE Signal Processing Letters, May 2013

An improvement is proposed which provides up to 5x speedup for the fastest bilateral filtering algorithm in the literature.

The achievable distortion region of sending a bivariate Gaussian source on the Gaussian broadcast channel

C. Tian, S. N. Diggavi and S. Shamai, IEEE Trans. Inform. Theory, Oct. 2011

A complete distortion region characterization for the joint source-channel coding problem of broadcasting bivariate Gaussians. This is the first case where a hybrid signaling scheme is found to be optimal.

Approximating the Gaussian multiple description rate region under symmetric distortion constraints

C. Tian, S. Mohajer and S. N. Diggavi, IEEE Trans. Inform. Theory, Aug. 2009

An approximate solution for a long-standing open problem in lossy distributed data storage. The surprise here is that a simple combination of scalable coding and unequal loss protection is in fact approximately optimal.

To selected publications by topic, or full publication list, or google scholar profile.

Services and Membership

Associated Editor

IEEE Signal Processing Letters / Feb. 2012-Feb. 2014

IEEE Senior Member

Elected February 2012

Conference TPC Member

ChinaCom-08, NetCod-12, NVMW-2014