A possible extension to the RInChI as a means of providing machine readable process data. - Philipp-Maximilian Jacob; Tian Lan; Jonathan M. Goodman; Alexei A. Lapkin (J. Cheminformatics, 2017)

Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm. - Eric Bradford; Artur M. Schweidtmann; Alexei A. Lapkin (J. Glob. Optim., 2018)

Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm. - Eric Bradford; Artur M. Schweidtmann; Alexei A. Lapkin (J. Glob. Optim., 2018)

Noisy, sparse, nonlinear: Navigating the Bermuda Triangle of physical inference with deep filtering. - Carl Poelking; Yehia Amar; Alexei A. Lapkin; Lucy J. Colwell (CoRR, 2019)

Searching for optimal process routes: A reinforcement learning approach. - Ahmad Khan; Alexei A. Lapkin (Comput. Chem. Eng., 2020)

Computer-aided design of formulated products: A bridge design of experiments for ingredient selection. - Liwei Cao; Danilo Russo; Emily Matthews; Alexei A. Lapkin; David Woods (Comput. Chem. Eng., 2023)

Boosting autonomous process design and intensification with formalized domain knowledge. - Jan Raphael Seidenberg; Ahmad A. Khan; Alexei A. Lapkin (Comput. Chem. Eng., 2023)

Gibbs-Duhem-Informed Neural Networks for Binary Activity Coefficient Prediction. - Jan G. Rittig; Kobi C. Felton; Alexei A. Lapkin; Alexander Mitsos (CoRR, 2023)

Heuristic optimisation of multi-task dynamic architecture neural network (DAN2). - Sushen Zhang; Vassilios S. Vassiliadis; Zhimian Hao; Liwei Cao; Alexei A. Lapkin (Neural Comput. Appl., 2023)

ORDerly: Data Sets and Benchmarks for Chemical Reaction Data. - Daniel S. Wigh; Joe Arrowsmith; Alexander Pomberger; Kobi C. Felton; Alexei A. Lapkin (J. Chem. Inf. Model., 2024)

Machine learning-guided space-filling designs for high throughput liquid formulation development. - Aniket Chitre; Daria Semochkina; David C. Woods; Alexei A. Lapkin (Comput. Chem. Eng., 2025)

Automated generation of mechanistic models for chemical process digital twins using reinforcement learning part I: Conceptual framework and equation generation. - Mathis Heyer; Jiyizhe Zhang; Naoto Sugisawa; Jan-Frederic Laub; Alexei A. Lapkin (Comput. Chem. Eng., 2025)

Multi-objective reaction optimization under uncertainties using expected quantile improvement. - Jiyizhe Zhang; Daria Semochkina; Naoto Sugisawa; David C. Woods; Alexei A. Lapkin (Comput. Chem. Eng., 2025)