General Lab Information

Xiaoning Qian

Joint Appointment, Applied Math, Computational Science Initiative

Xiaoning Qian

Brookhaven National Laboratory

Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000

Dr. Xiaoning Qian received the B.S.E. and M.S.E. degrees from Shanghai Jiaotong University, Shanghai, China, and the M.Ph. and Ph.D. degrees from Yale University, New Haven, CT, in Electrical Engineering. He is currently a Professor in the Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. He is also affiliated with the Department of Computer Science and Engineering and serves in the Faculty Advisory Committee in the Texas A&M Institute of Data Science (TAMIDS) as well as the Executive Committee in the Texas A&M TRIPODS Research Institute for Foundations of Interdisciplinary Data Science (FIDS). Dr. Qian holds a joint appointment in the Applied Math group in Computing and Data Sciences (CDS) at Brookhaven National Laboratory (BNL).

He received the National Science Foundation (NSF) CAREER Award, the Texas A&M Engineering Experiment Station (TEES) Senior Faculty Fellow, and the Montague-Center for Teaching Excellence Scholar from the Texas A&M University System. He holds the Segers Family Dean’s Excellence Professorship II in the College of Engineering at Texas A&M. He has also been a J. T. Oden Faculty Fellow in the Oden Institute for Computational Engineering and Sciences at the University of Texas, Austin. 

Dr. Qian’s research focuses on developing mathematical models and computational algorithms in signal processing, machine learning, Bayesian methods, especially in learning, uncertainty quantification, as well as experimental design. He has actively applied probabilistic models and optimization algorithms for applications in life and materials sciences. 

Expertise | Education | Appointments | Publications | Awards

Expertise

  • Bayesian learning
  • Bayesian experimental design
  • Bioinformatics and computational biology
  • Signal and image processing

Education

  • M.Ph., Ph.D.; Yale University
  • B.S.E., M.S.E.; Shanghai Jiaotong University

Professional Appointments

  • 2021 - present: Scientist, Applied Math, Computational Science Initiative, Brookhaven National Laboratory (by Joint Appointment)
  • 2022 - present: Professor, Department of Electrical and Computer Engineering, Texas A&M University
  • 2018 - 2022: Associate Professor, Department of Electrical and Computer Engineering, Texas A&M University
  • 2013 - 2018: Assistant Professor, Department of Electrical and Computer Engineering, Texas A&M University
  • 2009 - 2013: Assistant Professor, Department of Computer Science and Engineering, University of South Florida

Selected Publications

  • Liao H, Qian X, Huang JZ, Li P (2025) Rare Event Detection by Acquisition-Guided Sampling. IEEE Transactions on Automation Science and Engineering 22:7979–7991. https://doi.org/10.1109/tase.2024.3475951
  • Zadeh SH, Brown TD, Qian X, et al (2025) A composition-based predictive model for the transformation strain of NiTi shape memory alloys. Acta Materialia 289:120861. https://doi.org/10.1016/j.actamat.2025.120861
  • Lin F, Zhao C, Qian X, et al (2025) Fair Collaborative Learning (FairCL): A Method to Improve Fairness amid Personalization. INFORMS Journal on Data Science 4:67–84. https://doi.org/10.1287/ijds.2024.0029
  • Niyakan S, Sheng J, Cao Y, et al (2024) MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance. Patterns 5:100986. https://doi.org/10.1016/j.patter.2024.100986
  • Boluki S, Dadaneh SZ, Dougherty ER, Qian X (2024) Bayesian Proper Orthogonal Decomposition for Learnable Reduced-Order Models With Uncertainty Quantification. IEEE Transactions on Artificial Intelligence 5:1162–1173. https://doi.org/10.1109/tai.2023.3268609
  • Qian X, Yoon B-J, Arróyave R, et al (2023) Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery. Patterns 4:100863. https://doi.org/10.1016/j.patter.2023.100863
  • Lei B, Kirk TQ, Bhattacharya A, et al (2021) Bayesian optimization with adaptive surrogate models for automated experimental design. npj Computational Materials 7:. https://doi.org/10.1038/s41524-021-00662-x
  • Maddouri O, Qian X, Alexander FJ, et al (2022) Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning. Patterns 3:100428. https://doi.org/10.1016/j.patter.2021.100428
  • Yoon B-J, Qian X, Dougherty ER (2021) Quantifying the Multi-Objective Cost of Uncertainty. IEEE Access 9:80351–80359. https://doi.org/10.1109/access.2021.3085486
  • Boluki S, Qian X, Dougherty ER (2021) Optimal Bayesian supervised domain adaptation for RNA sequencing data. Bioinformatics 37:3212–3219. https://doi.org/10.1093/bioinformatics/btab228
  • Zhao G, Qian X, Yoon B-J, et al (2020) Model-Based Robust Filtering and Experimental Design for Stochastic Differential Equation Systems. IEEE Transactions on Signal Processing 68:3849–3859. https://doi.org/10.1109/tsp.2020.3001384

Awards & Recognition

  • 2025: Segers Family Dean’s Excellence Professorship II, College of Engineering, Texas A&M University
  • 2024: Faculty Impact Fellow, Department of Electrical & Computer Engineering, Texas A&M University
  • 2023: Finalist of the 2023 INFORMS QSR Best Paper
  • 2023: TEES (Texas A&M Engineering Experiment Station) Senior Faculty Fellow, Texas A&M University
  • 2020: College of Engineering Excellence Faculty Award, Texas A&M University.
  • 2020: Finalist of Best Student Paper Awards (6) at the 45th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
  • 2019: J. T. Oden Faculty Fellow, The Oden Institute for Computational Engineering and Sciences, University of Texas, Austin.
  • 2017: TEES (Texas A&M Engineering Experiment Station) Faculty Fellow, Texas A&M University.
  • 2017: Outstanding Professor, Department of Electrical and Computer Engineering, Texas A&M University.
  • 2016: Montague-Center for Teaching Excellence Scholar,  Texas A&M University.
  • 2016: Faculty Early Career Development (CAREER) Award. National Science Foundation (NSF), USA.
  • 2016: Best Paper Award at the International Conference on Intelligent Biology and Medicine (ICIBM).
  • 2013: Best Paper Award at the 11th Asian Pacific Bioinformatics Conference (APBC).
Xiaoning Qian

Brookhaven National Laboratory

Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000

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