The Actionable Intelligence Lab
Ever tried. Ever failed. No matter.
Try again. Fail again. Fail better.
- Samuel Beckett -
Who we are
The Actionable Intelligence Lab at Korea University aims to develop cutting-edge machine learning and artificial intelligence theories and methods, with the goal of making "better" decisions.
Led by Prof. Changhee Lee, the Actionable Intelligence Lab’s research team is developing a wide range of machine learning approaches including self- and semi-supervised learning, causal inference, automated ML, and many more to address unsolved real-world problems in healthcare, manufacturing, and other domains where critical decision making is the key.
Join Us
For prospective students: Prof. Lee will be accepting applications from highly motivated MS/Ph.D. students who are interested in solving real-world problems in healthcare.
Apply via this application form!
Preferred skillsets: Linear algebra / Probability and Statistics / Programming Skills (Python / Tensorflow / Pytorch)
Recent News
(09/2024) Our paper on contrastive learning-based survival analysis has been accepted to NeurIPS 2024. Great job! Dongjoon & Hyeryn :)
(09/2024) Prof. Lee will give a talk on DL-based feature selection at the CCAIM Summer School 2024.
(08/2024) Prof. Lee will join Korea University as an assistant professor in the Department of Artificial Intelligence starting Sep. 2024!
(07/2024) Our paper on the group-sparse feature selection method has been accepted to IEEE Access. Great job! Hyeryn :)
(07/2024) Our paper on domain-agnostic anomaly detection has been accepted to CIKM 2024. Great job! Hyuntae :)
(05/2024) Our paper on synergistic feature selection has been accepted to ICML 2024. Great job! Chohee :)
(01/2024) Our paper on time-series imputation has been accepted to ICLR 2024. Great job! MinGyu :)
(01/2024) Our paper on Predictive HO with Time-series Forecasting has been accepted to IEEE Network Magzine (Impact Factor: 9.6).
(09/2023) Our paper on active sensing under cost pressure has been accepted to NeurIPS 2023.
(04/2023) Our paper on time-series forecasting using SDEs has been accepted to ICML 2023.
(04/2023) We signed MOU with Incheon Fire Headquarters for the development of the AI System "119 Amigo"
(01/2023) Our paper on temporal clustering has been accepted to AISTATS 2023.
(12/2022) Chohee Kim, Hyuntae Kim, and Dongjoon Lee won the Grand Prize at the 2nd KAMP Contest sponsored by the Ministry of SMEs and Startups!
(11/2022) Our work in collaboration with Aivis and Nuri Eye Hospital won the Grand Prize at Digital Innovation Award 2022!
(07/2022) Our paper on the longitudinal time-to-event analysis and temporal clustering in non-metastatic prostate cancer patients has been accepted to npj Digital Medicine (Impact Factor: 15.357). Again, we are making real clinical impacts!
(01/2022) Our paper on self-supervised learning for feature selection has been accepted to ICLR 2022. We got a spotlight :)
(01/2022) Our paper on predicting good sleep based on physical activity and light exposure has been accepted to the Journal of Clinical Sleep Medicine.
(10/2021) Our paper on treatment effect estimation on time-to-event outcomes has been accepted to NeurIPS 2021.
(08/2021) I have joined Chung-Ang University (Department of Artificial Intelligence) as an assistant professor starting on Sep. 1st, 2021.
(01/2021) Our paper on applying AutoML for time-to-event analysis in non-metastatic prostate cancer patients has been accepted to the Lancet Digital Health (Impact Factor: 36.615). We are making real clinical impacts!
(01/2021) Our paper on integrating multi-omics data under various omics-missing patterns has been accepted to AISTATS 2021.
(11/2020) Our paper on applying temporal clustering to Stage III breast cancer patients has been accepted to IEEE Transactions on Biomedical Engineering.
(06/2020) Our paper on temporal clustering of heterogeneous disease progression patterns has been accepted to ICML 2020.