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Zukui Li

Showing results (1-10 of 8) with videos related to

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Industrial & Engineering Chemistry Research|January 19, 2013
A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: II. Probabilistic Guarantees on Constraint SatisfactionZukui Li, Christodoulos A Floudas
Industrial & Engineering Chemistry Research|February 14, 2015
A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: III. Improving the Quality of Robust SolutionsZukui Li, Christodoulos A Floudas
Industrial & Engineering Chemistry Research|September 22, 2011
A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear OptimizationZukui Li, Ran Ding, Christodoulos A Floudas
Journal of Chromatography. A|April 24, 2022
Can a computer "learn" nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processesSai Gokul Subraveti, Zukui Li, Vinay Prasad, et al.
Journal of Chemical Information and Modeling|November 23, 2021
Structure-Preserving Joint Non-negative Tensor Factorization to Identify Reaction Pathways Using Bayesian NetworksAnjana Puliyanda, Kaushik Sivaramakrishnan, Zukui Li, et al.
Accounts of Chemical Research|August 22, 2023
How Can (or Why Should) Process Engineering Aid the Screening and Discovery of Solid Sorbents for CO<sub>2</sub> Capture?Arvind Rajendran, Sai Gokul Subraveti, Kasturi Nagesh Pai, et al.
Journal of Clinical Periodontology|November 30, 2012
Discovery of biomarker combinations that predict periodontal health or disease with high accuracy from GCF samples based on high-throughput proteomic analysis and mixed-integer linear optimizationRichard C Baliban, Dimitra Sakellari, Zukui Li, et al.
Journal of Clinical Periodontology|November 19, 2011
Novel protein identification methods for biomarker discovery via a proteomic analysis of periodontally healthy and diseased gingival crevicular fluid samplesRichard C Baliban, Dimitra Sakellari, Zukui Li, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Industrial & Engineering Chemistry Research|January 19, 2013
A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: II. Probabilistic Guarantees on Constraint SatisfactionZukui Li, Christodoulos A Floudas
Industrial & Engineering Chemistry Research|February 14, 2015
A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: III. Improving the Quality of Robust SolutionsZukui Li, Christodoulos A Floudas
Industrial & Engineering Chemistry Research|September 22, 2011
A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear OptimizationZukui Li, Ran Ding, Christodoulos A Floudas
Journal of Chromatography. A|April 24, 2022
Can a computer "learn" nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processesSai Gokul Subraveti, Zukui Li, Vinay Prasad, et al.
Journal of Chemical Information and Modeling|November 23, 2021
Structure-Preserving Joint Non-negative Tensor Factorization to Identify Reaction Pathways Using Bayesian NetworksAnjana Puliyanda, Kaushik Sivaramakrishnan, Zukui Li, et al.
Accounts of Chemical Research|August 22, 2023
How Can (or Why Should) Process Engineering Aid the Screening and Discovery of Solid Sorbents for CO<sub>2</sub> Capture?Arvind Rajendran, Sai Gokul Subraveti, Kasturi Nagesh Pai, et al.
Journal of Clinical Periodontology|November 30, 2012
Discovery of biomarker combinations that predict periodontal health or disease with high accuracy from GCF samples based on high-throughput proteomic analysis and mixed-integer linear optimizationRichard C Baliban, Dimitra Sakellari, Zukui Li, et al.
Journal of Clinical Periodontology|November 19, 2011
Novel protein identification methods for biomarker discovery via a proteomic analysis of periodontally healthy and diseased gingival crevicular fluid samplesRichard C Baliban, Dimitra Sakellari, Zukui Li, et al.
Pageof 1