Korea Advanced Institute of Science and Technology · Computer Science
Professor Donghwan Lee's research lab specializes in advanced control theory and optimization, with a strong focus on reinforcement learning, model predictive control (MPC), and stability analysis for complex dynamical systems. The lab develops novel optimization frameworks—such as semidefinite and bilinear matrix inequality-based methods—for solving challenging control problems in nonlinear and switched systems. Key research directions include theoretical foundations of Q-learning, exponential stabilization of switched systems, and efficient algorithms for non-convex optimization in control applications. The lab integrates theoretical rigor with practical algorithm design, aiming to bridge control theory with real-world engineering systems.
Figures are computed from collected data and may differ slightly.
Alkenes and alcohols are among the most abundant and commonly used organic feedstock in industrial processes. We report a selective catalytic alkylation reaction of alkenes with alcohols that forms a carbon-carbon bond between vinyl carbon-hydrogen (C-H) and carbon-hydroxy centers with the concomitant loss of water. The cationic ruthenium complex [(C(6)H(6))(PCy(3))(CO)RuH](+)BF(4)(-) (Cy, cyclohexyl) catalyzes the alkylation in solution within 2 to 8 hours at temperatures ranging from 75° to 11
The associations of Internet addiction (IA) and smartphone addiction (SA) with mental health problems have been widely studied. We investigated the effects of IA and SA on depression and anxiety while adjusting for sociodemographic variables. In this study, 4854 participants completed a cross-sectional web-based survey including socio-demographic items, the Korean Scale for Internet Addiction, the Smartphone Addiction Proneness Scale, and the subscales of the Symptom Checklist 90 Items-Revised.
We aimed to develop a machine learning (ML) classifier to detect and compare major psychiatric disorders using electroencephalography (EEG). We retrospectively collected data from medical records, intelligence quotient (IQ) scores from psychological assessments, and quantitative EEG (QEEG) at resting-state assessments from 945 subjects [850 patients with major psychiatric disorders (six large-categorical and nine specific disorders) and 95 healthy controls (HCs)]. A combination of QEEG parameter
As the feature size of NAND flash memory decreases, the threshold voltage signal becomes less reliable, and its distribution varies significantly with the number of program-erase (PE) cycles and the data retention time. We have developed parameter estimation algorithms to find the means and variances of the threshold voltage distribution that is modeled as a Gaussian mixture. The proposed methods find the best-fit parameters by minimizing the squared Euclidean distance between the measured thres
Abstract A mesoporous LTA zeolite (MP‐LTA)‐supported palladium catalyst was developed for the highly efficient Suzuki–Miyaura reaction of aryl and heteroaryl chlorides. The couplings of various aryl chlorides with arylboronic acids in aqueous ethanol were efficiently achieved in the presence of 1.0 mol% of the catalyst. Furthermore, the scope of this catalyst was extended to the coupling of heteroaryl chlorides. Regardless of the substituents, all of the coupling reactions were very clean and hi
Recently, reinforcement learning (RL) is receiving more and more attentions due to its successful demonstrations outperforming human performance in certain challenging tasks. The goal of this paper is to study a new optimization formulation of the linear quadratic regulator (LQR) problem via the Lagrangian duality theories in order to lay theoretical foundations of potentially effective RL algorithms. The new optimization problem includes the Q-function parameters so that it can be directly used
The new method has better performance than several existing methods, particularly in the estimation of the loading vectors.
A new β-diketiminatophosphane Pd catalyst was found to be highly effective in the mono and double Hiyama coupling reactions of unactivated aryl chlorides in water.
High-density NAND flash memory suffers from the data retention problem because even small charge leakage incurs a large threshold voltage shift as the transistor size shrinks. In this paper, we develop a decision directed estimation (DDE) algorithm to know the effects of charge leakage in NAND flash memory using the error pattern of the accessed data. While the conventional sensing directed estimation (SDE) method demands extra memory sensing to know the signal distribution, the proposed DDE alg
In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem. The local stability analysis, the estimation of the domain of attraction, an
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