ABOUT

 

Hi! I'm Sijia Liu. I am a Research Fellow (supervised by Dr. Alfred Hero ) at the University of Michigan, Ann Arbor. I received my Ph.D. degree (advisors Dr. Pramod K. Varshney and Dr. Makan Fardad) in Electrical and Computer Engineering from Syracuse University. I received my M.S. and B.S. degrees (advisor Chongzhao Han) in Electrical Engineering from Xi'an Jiaotong University in 2008 and 2011, respectively. My hometown is the lovely city of Zhengzhou, China.

In summer 2015, I was a Research Intern in Wireless Access Lab at Huawei R&D USA (mentor Dr. Kai Yang).

My research area is distributed optimization, graph signal processing, estimation, resource management in wireless sensor networks, data fusion, wireless communications, networking, and the newly emerging field of learning and big data. See my CV (pdf) for more details.

Email: sliu17 [at] syr [dot] edu



RECENT RESEARCH PROJECTS

Distributed optimization: acceleration and topology design

Collaborators: Pin-Yu Chen (IBM)
Problem: Since network connectivity affects convergence of distributed optimization, is it possible to accelerate the optimization procedure with the help of well-designed networks? How to evaluate the improved convergence performance?
Goal: Study impacts of network topology design on the convergence rate of distributed optimization
Novelty: Improved theoretical and empirical convergence results under evolving networks of growing connectivity
Impact: Accelerated parallel scientific computing/distributed optimizatoin/learning over graphs
[paper]

   

Cellular reprogramming: from graph signal processing perspective

Collaborators: Indika Rajapakse (UM)
Problem: How to capture dynamics of genome structure and function for cellular reprogramming
Goal: Develop a data-guided mathematical foundation for direct reprogramming
Novelty: Data-guided control and learning theory under multiple views (genome structure and function)
Impact: Reprogramming the immune system, resupply

   

Sensor selection/scheduling

Collaborators: Geert Leus (TU Delft), Engin Masazade (Yeditepe Univ.) and Aditya Vempaty (IBM)
Problem: How to determine optimal sensor activations over both time and space in energy-constrained networks?
Goal: Seek optimal trade-offs between estimation accuracy and sensor activations
Novelty: Sensor management via sparsity-promoting regularizations
Impact: Near-optimal solutions from low-complexity sensor selection/scheduling algorithms
[paper]

   

Sensor collaboration

Collaborators: Swarnendu Kar (Intel Corporation)
Problem: How to determine optimal network topology in the presence of sensor collaboration?
Goal: Find power-efficient inter-sensor collaboration strategies to minimize the estimation distortion
Novelty: Innovated a sparsity-aware sensor collaboration framework with nonzero collaboration cost and unknown collaboration topologies
Impact: Up to 30% conservation of battery power (typical setups)
[paper]



AWARDS

  • Recipient of All University Doctoral Prize, Syracuse University, 2016
  • Signal Processing Society (SPS) Travel Grant Award at IEEE ICASSP'15
  • Best Student Paper Nominee (among the seven finalists) at Asilomar'13
  • Best Department Poster Award at Nunan poster competition, Syracuse University, 2012
  • First Class Award in China National Mathematics Olympiad (exempted from Chinese College Entrance Examination), 2004


PUBLICATIONS

Submissions

P.-Y. Chen and S. Liu, "Bias-Variance Tradeo of Graph Laplacian Smoothing Regularizer," IEEE Signal Process. Lett., 2017

Journals

S. Liu, S. Kar, M. Fardad and P. K. Varshney, "Optimized Sensor Collaboration for Estimation of Temporally Correlated Parameters," IEEE Transactions on Signal Processing, vol. 64, no. 24, pp. 6613-6626, Dec. 2016

B. Kailkhura, S. Liu, T. Wimalajeewa and P. K. Varshney, "Measurement Matrix Design for Compressive Detection with Secrecy Guarantees," IEEE Wireless Communications Letters, vol. 5, no. 4, pp. 420-423, Aug. 2016

S. Liu, S. Kar, M. Fardad and P. K. Varshney, "Joint Design of Optimal Sensor Selection and Collaboration Strategies for Distributed Estimation," IEEE ComSoc MMTC E-letter, Special Issue on "Energy efficiency management for distributed computation and applications in sensor networks", Mar. 2016

S. Liu, S. P. Chepuri, M. Fardad, E. Masazade, G. Leus and P. K. Varshney, "Sensor Selection for Estimation with Correlated Measurement Noise," IEEE Transactions on Signal Processing, vol. 64, no. 13, pp. 3509-3522, July 2016

S. Liu, S. Kar, M. Fardad and P. K. Varshney, "Sparsity-Aware Sensor Collaboration for Linear Coherent Estimation, IEEE Transactions on Signal Processing, vol.63, no.10, pp. 2582-2596, May 2015

S. Liu, A. Vempaty, M. Fardad, E. Masazade and P. K. Varshney, "Energy-Aware Sensor Selection in Field Reconstruction," IEEE Signal Processing Letters, vol.21, no.12, pp.1476-1480, Dec. 2014

X. Shen, S. Liu and P. K. Varshney, "Sensor Selection for Nonlinear Systems in Large Sensor Networks," IEEE Transactions on Aerospace and Electronic Systems, vol.50, no.4, pp.2664-2678, October 2014

S. Liu, M. Fardad, E. Masazade and P. K. Varshney, "Optimal Periodic Sensor Scheduling in Networks of Dynamical Systems," IEEE Transactions on Signal Processing, vol.62, no.12, pp.3055-3068, June, 2014

Conferences

S. Liu, A. Ren, Y. Wang and P. K. Varshney, "Ultra-Fast Robust Compressive Sensing Based on Memristor Crossbars," ICASSP, 2017

S. Liu, P.-Y. Chen and A. O. Hero, "Distributed Optimization for Evolving Networks of Growing Connectivity," ICASSP, 2017

S. Liu, S. P. Chepuri, G. Leus and A. O. Hero, "Distributed Sensor Selection for Field Estimation," ICASSP, 2017

S. P. Chepuri, S. Liu, G. Leus and A. O. Hero, "Learning Sparse Graphs Under Smoothness Prior," ICASSP, 2017

A. Ren, S. Liu, R. Cai, P. K. Varshney and Y. Wang, "Algorithm-Hardware Co-Optimization of Memristor Crossbar-Based Framework for Solving SOCP and Homogeneous QCQP Problems," The 22nd Asia and South Pacific Design Automation Conference (ASPDAC), 2016

S. Liu, V. Sharma and P. K. Varshney, "Towards An Online Energy Allocation Policy for Distributed Estimation with Sensor Collaboration Using Energy Harvesting Sensor," GlobalSIP, 2016

S. Liu, N. Cao and P. K. Varshney, "Sensor Placement for Field Estimation via Poisson Disk Sampling," GlobalSIP, 2016

S. Liu, Y. Wang, M. Fardad and P. K. Varshney, "Optimal Energy Allocation and Storage Control for Distributed Estimation with Sensor Collaboration," CISS, 2016

S. Liu, S. Kar, M. Fardad and P. K. Varshney, "On Optimal Sensor Collaboration for Distributed Estimation with Individual Power Constraints," Asilomar, 2015

V. Gupta, B. Kailkhura, T. Wimalajeewa, S. Liu and P. K. Varshney, "Joint Sparsity Pattern Recovery with 1-bit Compressive Sensing in Sensor Networks," Asilomar, 2015

S. Liu, F. Chen, A. Vempaty, M. Fardad and P. K. Varshney, "Sparsity-Promoting Sensor Management for Estimation: An Energy Balance Point of View," FUSION, 2015

Nadendla, V. S. S., S. Liu and P. K. Varshney, "On Enhancing Secrecy in Centralized Detection using Transmit-Beamforming with Artificial Noise," Allerton, 2015

S. Liu, E. Masazade, M. Fardad and P. K. Varshney, "Sensor Selection with Correlated Measurements for Target Tracking in Wireless Sensor Networks," ICASSP, 2015 (IEEE SPS Travel Grant Award)

S. Liu, E. Masazade, M. Fardad and P. K. Varshney, "Sparsity-Aware Field Estimation via Ordinary Kriging," ICASSP, 2014

S. Liu, M. Fardad, S. Kar and P. K. Varshney, "On Optimal Sensor Collaboration Topologies for Linear Coherent Estimation," ISIT, 2014

S. Liu, M. Fardad, E. Masazade and P. K. Varshney, "On Optimal Periodic Sensor Scheduling for Field Estimation in Wireless Sensor Networks," GlobalSIP, 2013

S. Liu, E. Masazade, X. Shen and P. K. Varshney, "Adaptive Non-Myopic Quantizer Design for Target Tracking in Wireless Sensor Networks," Asilomar, 2013 (Finalist Best Student Paper Award)

S. Liu, E. Masazade and P. K. Varshney, "Temporally Staggered Sensing for Field Estimation with Quantized Data in Wireless Sensor Networks," SSP, 2012



PATENTS

K. Yang and S. Liu, "System and Method for Analyzing A Root Cause of Anomalous Behavior Using Hypothesis Testing," US Patent Application, Serial No. 14/991685, 2016



Last updated March 10, 2016