Xiaoning Qian , Ph.D.

*Email: <xqian, ece.tamu.edu>

Associate Professor

Dept. of Electrical & Computer Engineering

Texas A&M University

MS 3128, TAMU

College Station, TX 77843

 

Office:   Wisenbaker Engineering Research Center (WERC) 205J

Phone:   +1-979-845-6268

 

https://people.engr.tamu.edu/xqian/xqian.png

Brief Biography

    I am currently in the Department of Electrical & Computer Engineering at Texas A&M University . Before joining the department, I was in the Department of Computer Science & Engineering at the University of South Florida (USF).   I worked on biomedical image segmentation and shape-based image databases using statistical shape analysis in the Image Processing and Analysis Group (IPAG) at Yale University. I received my Ph.D. degree from Yale University.

 

For more updated information, please check my always under-construction homepage.

News


·  I am organizing the Bio-Seminar for Biomedical Imaging, Sensing & Genomic Signal Processing in the Department of Electrical & Computer Engineering at Texas A&M. If you will be around College Station, I would certainly love to have you to give a talk and meet with our faculty and students.


·  My first edited book ``Emerging Research in the Analysis and Modeling of Gene Regulatory Networks'' can be found at Amazon.


Publication Errata

    The convergence proof in the recent retracted conference paper---Y Wang and X Qian, "Stochastic Coordinate Descent Frank-Wolfe Algorithm for Large-Scale Biological Network Alignment" in Proceedings of 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP'2014)---is not correct. Please consult the full paper at arXiv.

 

Research Interests

·  Bayeisan learning & experimental design:
    - Bayesian learning and analytic methods for large-scale data in life and materials science;
    - Bayesian computation for optimal experimental design with model and data uncertainty.

·  Bioinformatics:
    - Analysis and intervention in biological networks;
    - Functional data analysis on genomic and proteomic datasets.

·  Biomedical image processing and analysis:
    - Image segmentation and robust boundary finding;
    - Shape-based similarity retrieval in multimedia databases.

I am currently recruiting for graduate students. Research Assistantship (RA) positions will be offered to outstanding students who are hard-working and motivated. Interested candidates should email their CVs, transcripts, and brief research statements. [Note] I apologize but I may not have time to reply to all the inquiry emails. However, I do reply to the students who have applied for admissions to our department if you have all the requested documents in your inquiry emails.

Teaching

At TAMU

    ECEN 303.501 Random Signals and Systems:  Fall 2013 -- 2015; Spring 2017

·         Introduction to fundamental concepts of probability theory and their applications in engineering problems

    ECEN 333.501 At the Interface of Engineering and Life Sciences :  Spring 2015 -- 2019

·         Overview of electrical and computer engineering principles that are being applied to various areas in life sciences to address emerging grand challenges

    ECEN 765.600 Machine Learning with Networks :  Spring 2014, 2015; Fall 2016 -- 2018

·         Introduction to basics of machine learning, focusing on state-of-the-art research with structured data

At USF

    CISE 6930.002 Computational Molecular Biology:  Spring 2010

·         Introduction to major topics in bioinformatics and computational biology

    CISE 4930.007/6930.002 Data Mining in Bioinformatics:  Spring 2011

·         Introduction to basic data mining and machine learning techniques and their applications

    GMS 7930 Bioinformatics (I & II):  Fall 2011, 2012

·         Introduction to basic topics in bioinformatics (lead lecturer: Dr. Vladimir N. Uversky)

    CISE 4930.007/6930.002 Biological Network Analysis:  Spring 2012

·         Introduction to basic methods to analyze topology and dynamics of network systems

    CISE 6930.002 Machine Learning:  Spring 2013

·         Introduction to Bayesian learning methods in statistical learning

 

Current Students

    - Siamak Zamani Dadaneh (PhD student 2014 – present);
    - Meltem Apaydin (PhD student 2015 – present);
    - Kai He (PhD student 2015 – present);
    - Ehsan Hajiramezanali (PhD student 2016 – present);
    - Guang Zhao (PhD student 2016 – present);
    - Randy Ardywibowo (PhD student 2017 – present; REU student 2016 – 2017);

    - Xiaoqian Jia (MS student 2017 – present);
    - Xueting Liu (MS student 2017 – present);

Alumni

    - Seyed Javad Sajjadi (PhD – defended summer 2014, co-advising with Dr. Bo Zeng; Current employment: Data scientist at Precima, Inc.; LoyaltyOne);
    - Yijie Wang (PhD – defended summer 2015; First employment: Post-doc at NIH/NCBI);
    - Amin Ahmadi Adl (PhD – defended summer 2015; Current employment: Data scientist at Microsoft);
    - Meng Lv (PhD – defended fall 2015; First employment: Assistant professor at Tianjin University);
    - Shaogang Ren (PhD – defended fall 2017; First employment: Baidu Research Lab.);
    - Chung-Chi "Charles" Tsai (PhD – defended spring 2018; First employment: Qualcomm);

    - Zhou Wang (MS – defended fall 2016; First employment: FactSet Research System);
    - Fan Liu (MS – defended fall 2018);
    - Qing Jin (MS – defended fall 2018).

    - Dario Avendano Ovalle (Undergraduate researcher – 2017 - 2018).

Selected Recent Publications

    Please check my Google Scholar page for a more complete list of publications.

·         Xiaoning Qian and Edward R. Dougherty,
"Bayesian regression with network prior: Optimal Bayesian filtering perspective," [Paper]
IEEE Transactions on Signal Processing, 64(23): 6243-6253, 2016.

·         Siamak Zamani Dadaneh and Xiaoning Qian,
"Bayesian module identification from multiple noisy networks," [Paper]
EURASIP Journal on Bioinformatics and Systems Biology, 2016:5, 2016.

·         Meltem Apaydin, Bo Zeng, Xiaoning Qian,
"Is OptKnock a reliable strategy for desirable mutants?," [Paper]
Workshops on Machine Learning in Computational Biology (MLCB) & Machine Learning in Systems Biology (MLSB) 2015, A Workshop at the Annual Conference on Neural Information processing Systems (NIPS 2015), Montreal, Canada, December, 2015.

·         Shaogang Ren, Shuai Huang, John Onofrey, Xenophon Papademetris, Xiaoning Qian,
"A scalable algorithm for structured kernel feature selection," [Paper]
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics (AISTATS), 781-789, San Diego, CA, May, 2015.

·         Yijie Wang and Xiaoning Qian,
"Functional module identification in protein interaction networks by interaction patterns," [Paper]
Bioinformatics, 30(1): 81-93, 2014.

·         Meng Lu, Hye-Seung Lee, David Hadley, Jianhua Z. Huang, and Xiaoning Qian,
"Supervised categorical principal component analysis for genome-wide association analyses," [Paper]
BMC Genomics, 15(Suppl 1):S10, 2014.

·         Byung-Jun Yoon, Xiaoning Qian, Edward R Dougherty,
"Quantifying the objective cost of uncertainty in complex dynamic systems," [Paper]
IEEE Transactions on Signal Processing, 61(9): 2256-2266, 2013.

·         Yijie Wang and Xiaoning Qian,
"A novel subgradient-based optimization algorithm for blockmodel functional module identification," [Paper]
BMC Bioinformatics, 14(Suppl 2): S23, 2013.

·         Shaogang Ren, Bo Zeng, and Xiaoning Qian,
"Adaptive bi-level programming for optimal gene knockouts for targeted overproduction under phenotypic constraints," [Paper]
BMC Bioinformatics, 14(Suppl 2):S17, 2013.

·         Byung-Jun Yoon, Xiaoning Qian, Sayed Mohammad Ebrahim Sahraeian,
"Comparative analysis of biological networks using Markov chains and hidden Markov models," [Paper]
IEEE Signal Processing Magazine, Special Issue on Genomic and Proteomic Signal Processing in Biomolecular Pathways, 29(1): 22--34, 2012.

·         Xiaoning Qian and Edward R Dougherty,
"Intervention in gene regulatory networks via phenotypically constrained control policies based on long-run behavior," [Paper]
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(1): 123--136, 2012.

·         Xiaoning Qian, Noushin Ghaffari, Ivan Ivanov and Edward R. Dougherty,
"State reduction for network intervention in probabilistic Boolean networks," [Paper]
Bioinformatics, 26(24): 3098-3104, 2010.

·         Xiaoning Qian, Ivan Ivanov, Noushin Ghaffari and Edward R. Dougherty,
"Intervention in gene regulatory networks via greedy control policies based on long-run behavior," [Paper]
BMC Systems Biology, 3(61): 16 pages, 2009.

·         Xiaoning Qian and Edward R. Dougherty,
"On the long-run sensitivity of probabilistic Boolean networks," [Paper]
Journal of Theoretical Biology, 257(4): 560-577, 2009.

·         Xiaoning Qian , Sing-Hoi Sze, Byung-Jun Yoon,
"Querying pathways in protein interaction networks based on hidden Markov models," [Paper]
Journal of Computational Biology, 16(2): 145-157, 2009.

·         Xiaoning Qian , Matthew P. Brennan, Donald P. Dione, Wawrzyniec L. Dobrucki, Marcel P. Jackowski, Christopher K. Breuer, Albert J. Sinusas, Xenophon Papademetris,
"A nonparametric vessel detection method for complex vascular structures," [Paper]
Medical Image Analysis, 13(1): 49-61, 2009.

·         Xiaoning Qian and Edward R. Dougherty,
"Effect of function perturbation on the steady state distribution of genetic regulatory networks: optimal structural intervention," [Paper]
IEEE Transactions on Signal Processing, 56(10): 4966-4976, 2008.

 

*To avoid spam, I use “<user, domain>” to represent the email address “user@domain”.