Selected work

Representative Papers

Technology interactions reshape the economics of China's coal power decarbonization

Aug 11, 2026

This study identifies the cost-optimal decarbonization pathway for China’s coal-fired power system under the synergistic deployment of multiple emission reduction technologies. To this end, an optimization model incorporating plant-level heterogeneity and shared resource constraints—specifically biomass availability and CO₂ storage capacity—is developed to systematically quantify, for the first time, the interaction effects among energy efficiency retrofits, biomass co-firing, and carbon capture on marginal abatement costs and technology portfolios. The results indicate that approximately 1.2 Gt CO₂ per year of emissions reductions can be achieved at negative marginal cost, with a marginal cost of $56 per ton CO₂ for achieving carbon neutrality. In deep decarbonization phases, the optimal pathway shifts from efficiency improvements to biomass co-firing and ultimately relies on biomass-integrated carbon capture to deliver net-negative emissions.

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Convex Regression with a Penalty

Sep 24, 2025

Convex regression often suffers from overfitting near the boundary of the domain. Method: This paper proposes a constrained least-squares estimator with subgradient penalization—jointly regularizing both the convex regression function and its subgradient under a data-driven error bound (s_n). Grounded in convex analysis and nonparametric regression theory, the method imposes shape constraints while controlling estimation error. Contribution/Results: It establishes, for the first time, almost-sure uniform consistency of both the convex function and its subgradient over the entire domain in high-dimensional settings, with explicit convergence rates. Theoretical analysis confirms global consistency and optimal-order convergence. Empirical evaluation on modeling waiting times in a single-server queueing system demonstrates substantial improvements in boundary stability and estimation accuracy, effectively mitigating the boundary bias inherent in existing approaches.

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A novel association and ranking approach identifies factors affecting educational outcomes of STEM majors

Mar 16, 2025

This study identifies actionable, intervention-sensitive factors influencing undergraduate STEM graduation rates to enable evidence-based policy design. Method: Leveraging integrated administrative data—including academic transcripts, demographic attributes, institutional records, and, for the first time, National Student Clearinghouse (NSC) transfer-tracking data—from two four-year institutions in the U.S. Northeast, we apply the D-basis formal concept analysis algorithm to uncover causal associations, explicitly incorporating post-transfer degree completion outcomes. Contribution/Results: We reveal a counterintuitive positive association between STEM-to-non-STEM major switching and higher overall graduation rates. Key predictive factors include introductory biology/chemistry/mathematics course performance, initial mathematics course difficulty selection, and institutional flexibility in major changes. Variables such as Pell Grant eligibility significantly reflect structural inequities in time-to-degree and retention. Findings provide empirically grounded, operationally actionable insights for targeted STEM education interventions.

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Recent publications

Latest Papers

Technology interactions reshape the economics of China's coal power decarbonization

Aug 11, 2026

This study identifies the cost-optimal decarbonization pathway for China’s coal-fired power system under the synergistic deployment of multiple emission reduction technologies. To this end, an optimization model incorporating plant-level heterogeneity and shared resource constraints—specifically biomass availability and CO₂ storage capacity—is developed to systematically quantify, for the first time, the interaction effects among energy efficiency retrofits, biomass co-firing, and carbon capture on marginal abatement costs and technology portfolios. The results indicate that approximately 1.2 Gt CO₂ per year of emissions reductions can be achieved at negative marginal cost, with a marginal cost of $56 per ton CO₂ for achieving carbon neutrality. In deep decarbonization phases, the optimal pathway shifts from efficiency improvements to biomass co-firing and ultimately relies on biomass-integrated carbon capture to deliver net-negative emissions.

0 citationsRead paper

Convex Regression with a Penalty

Sep 24, 2025

Convex regression often suffers from overfitting near the boundary of the domain. Method: This paper proposes a constrained least-squares estimator with subgradient penalization—jointly regularizing both the convex regression function and its subgradient under a data-driven error bound (s_n). Grounded in convex analysis and nonparametric regression theory, the method imposes shape constraints while controlling estimation error. Contribution/Results: It establishes, for the first time, almost-sure uniform consistency of both the convex function and its subgradient over the entire domain in high-dimensional settings, with explicit convergence rates. Theoretical analysis confirms global consistency and optimal-order convergence. Empirical evaluation on modeling waiting times in a single-server queueing system demonstrates substantial improvements in boundary stability and estimation accuracy, effectively mitigating the boundary bias inherent in existing approaches.

0 citationsRead paper

A novel association and ranking approach identifies factors affecting educational outcomes of STEM majors

Mar 16, 2025

This study identifies actionable, intervention-sensitive factors influencing undergraduate STEM graduation rates to enable evidence-based policy design. Method: Leveraging integrated administrative data—including academic transcripts, demographic attributes, institutional records, and, for the first time, National Student Clearinghouse (NSC) transfer-tracking data—from two four-year institutions in the U.S. Northeast, we apply the D-basis formal concept analysis algorithm to uncover causal associations, explicitly incorporating post-transfer degree completion outcomes. Contribution/Results: We reveal a counterintuitive positive association between STEM-to-non-STEM major switching and higher overall graduation rates. Key predictive factors include introductory biology/chemistry/mathematics course performance, initial mathematics course difficulty selection, and institutional flexibility in major changes. Variables such as Pell Grant eligibility significantly reflect structural inequities in time-to-degree and retention. Findings provide empirically grounded, operationally actionable insights for targeted STEM education interventions.

0 citationsRead paper