Graph reduction for hierarchical control of energy integrated process networks. - Seongmin Heo; Sujit S. Jogwar; Srinivas Rangarajan; Prodromos Daoutidis (CDC, 2012)

Control structure design for complex energy integrated networks using graph-theoretic methods. - Seongmin Heo; Dimitrios Georgis; Prodromos Daoutidis (MED, 2013)

Input/output hierarchical clustering in process networks based on relative degrees. - Seongmin Heo; Prodromos Daoutidis (ACC, 2015)

Time scale decomposition in complex reaction systems: A graph theoretic analysis. - Udit Gupta; Seongmin Heo; Aditya Bhan; Prodromos Daoutidis (Comput. Chem. Eng., 2016)

Parallel neural networks for improved nonlinear principal component analysis. - Seongmin Heo; Jay H. Lee (Comput. Chem. Eng., 2019)

Dynamic analysis and linear model predictive control for operational flexibility of post-combustion CO2 capture processes. - Howoun Jung; Dasom Im; Seongmin Heo; Boeun Kim; Jay H. Lee (Comput. Chem. Eng., 2020)

An iterative constrained least squares method for continuous piecewise linear approximation. - Ji Hee Kim; Naeun Choi; Seongmin Heo (Comput. Chem. Eng., 2022)

Mean squared error criterion for model-based design of experiments with subset selection. - Boeun Kim; Kyung Hwan Ryu; Seongmin Heo (Comput. Chem. Eng., 2022)

Feature variance regularization method for autoencoder-based one-class classification. - Boeun Kim; Kyung Hwan Ryu; Ji Hee Kim; Seongmin Heo (Comput. Chem. Eng., 2022)

Attention Mechanism for Lithium-Ion Battery Lifespan Prediction: Temporal and Cyclic Attention. - Jaewook Lee; Seongmin Heo; Jay H. Lee (CoRR, 2023)

Noninvasive inline imaging and computer vision-based quality variable estimation for continuous slug-flow crystallizers. - Derrick Adams; Jay H. Lee; Shin Hyuk Kim; Seongmin Heo (Comput. Chem. Eng., 2025)

Extracting key temporal and cyclic features from VIT data to predict lithium-ion battery knee points using attention mechanisms. - Jaewook Lee; Seongmin Heo; Jay H. Lee (Comput. Chem. Eng., 2025)