Publication

Journal

H.Y. Jo, M.-J. Kim*, "Evolutionary Sampling for Knowledge Distillation in Multi-Agent Reinforcement Learning," Mathematics, 13(17):2734, Aug. 2025. (IF: 2.2, 5.9%, JCR 2024)

T. Kim, M.-J. Kim*, CW Ahn*, "PF2N: Periodicity–Frequency Fusion Network for Multi-Instrument Music Transcription," Mathematics, 13(11):1708, May. 2025. (IF: 2.2, 5.9%, JCR 2024)

T. Kim, M.-J. Kim*, CW Ahn*, “Multi-Task Learning based Temporal Pattern Matching Network for Guitar Tablature Transcription,” Neural Computing and Applications, 37, pp. 12083–12102, Mar. 2025. (IF:4.5, 26.1%, JCR2023)

Y.K. Jwa, C.W. Ahn*, M.-J. Kim*, "EGNAS: Efficient Graph Neural Architecture Search Through Evolutionary Algorithm," Mathematics, 12(23):3828, Dec. 2024. (IF: 2.3, 4.2%, JCR 2023)

C.M. Lee, C.W. Ahn*, M.-J. Kim*, "Feature Optimization and Dropout in Genetic Programming for Data-Limited Image Classification," Mathematics, 12(23):3661, Nov. 2024. (IF: 2.3, 4.2%, JCR 2023)

T. Kim, D Lee, M.-J. Kim*, CW Ahn*, “Polyphonic Piano Music Transcription System Exploiting Mutual Correlations of Different Musical Note States,” IEEE Access, vol. 12, pp. 93689 - 93700, Jul. 2024. (IF: 3.4, 34.7%, JCR 2023)

M.-J. Kim, D Lee, JS Kim, and CW Ahn, “Surrogate-assisted Monte Carlo Tree Search for real-time video games,” Engineering Applications of Artificial Intelligence, vol. 133, part B pp. 108152, Jul. 2024. (IF: 7.5, 2.5%, JCR2023)

M.-J. Kim, JS. Kim, and CW Ahn, “Evolving Population Method for Real-time Reinforcement Learning,” Expert Systems with Applications, vol. 229, pp. 120493, Nov. 2023. (IF: 8.5, 6.4%, JCR2022)

M.-J. Kim, H. Park, and CW Ahn, “Nondominated Policy-guided Learning in Multi-objective Reinforcement Learning,” Electronics,11(7), 1069, Mar. 2022. (IF: 2.690, 50.3%, JCR2021)

D.H. Lee, M.-J. Kim and CW Ahn, “Predicting combat outcomes and optimizing armies in StarCraft II by deep learning,” Expert Systems with Applications, vol. 185, pp. 115592, Dec. 2021. (IF: 6.954, 8.6%, JCR 2020)

M.-J. Kim, JS Kim, S.J. Kim, M. Kim and CW Ahn, “Genetic State-Grouping Algorithm for Deep Reinforcement Learning,” Expert Systems with Applications, vol. 161, pp. 113695, Dec. 2020. (IF: 5.452, 1.8%, JCR 2019)

S. Lim, M.-J. Kim, CW Ahn, “A Genetic Algorithm (GA) Approach to the Portfolio Design Based on Market Movements and Asset Valuations,” IEEE Access, vol. 8, pp.140234-140249, Jul. 2020. (IF: 3.745, 22.1%, JCR 2019)

M.-J. Kim, K.-J. Kim, S.-J. Kim and A. K. Dey, “Performance Evaluation Gaps in a Real-Time Strategy Game between Human and Artificial Intelligence Players,” IEEE Access, Jan. 2018.(IF:3.557, 15.8%, JCR 2017)

S. Farooq, I.-S. Oh, M.-J. Kim, and K.-J. Kim, “StarCraft AI Competition: A Step Toward Human-Level AI for Real-Time Strategy Games,” AI Magazine, Summer, 2016. (IF: 0.628, 82.6%, JCR 2015)

Conference

K.-J. Chang, G. Cho, W. Song, M.-J. Kim, C. Ahn, and M. Song, “Personalized EV Driving Sound Design Based on the Drivier’s Total Emotion Recognition,” The 12th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference, 2022. 

M.-J. Kim, J.-H. Lee, and C. Ahn, “Genetic Optimizing Method for Real-time Monte Carlo Tree Search Problem,” The 9th International Conference on Smart Media and Applications (SMA 2020), 2020. 

D. Lee, M.-J. Kim and C. Ahn, “BattleNet: Capturing Advantageous Battlefield in RTS Games,” The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020, Student Abstract), 2020. 

M.-J. Kim, J. Kim, D. Lee, and CW. Ahn, “Genetic Action Sequence for Integration of Agent Actions,” The 14th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2019), 2019. 

M.-J. Kim, J. Kim, D. Lee, S. Kim, M. Kim and CW. Ahn, “Integrating agent actions with genetic action sequence method,” ACM Genetic and Evolutionary Computation Conference Companion(GECCO 2019), 2019. 

M.-J. Kim, and C. W. Ahn, “Hybrid fighting game AI using a genetic algorithm and Monte Carlo tree search,” ACM Genetic and Evolutionary Computation Conference Companion(GECCO 2018), Kyoto, Japan, 2018.

M.-J. Kim and K.-J. Kim, “Opponent Modeling based on Action Table for MCTS-based Fighting Game AI,” IEEE Conference on Computational Intelligence and Games(CIG 2017), 2017. 

M.-J. Kim, K.-J. Kim, S.-J. Kim, and A. K. Dey, “Evaluation of StarCraft Artificial Intelligence Competition Bots by Experienced Human Players,” ACM CHI Conference Extended Abstracts on Human Factors in Computing Systems(CHI 2016), pp. 1915-1921, 2016.