Journal Club

Presentation 40: Qinghe Dong - 2026.07.15

Multi-objective Reinforcement Learning in Disassembly Line Balancing.

Presentation 39: Zhicheng Chen - 2026.07.01

SAM-Based Gradient Perturbation for Federated Learning.

Presentation 38: Man Li - 2026.06.24

Improved Physical Structure Constraints for Inverse Dynamics Robustness Under Uncertainties.

Presentation 37: Jinghao Liu - 2026.06.10

Temporal Data Representation Based on Quantum Spectrum Encoding.

Presentation 36: Mohan Niu - 2026.06.03

Complex Dynamic Environment Information Aggregation for Multi-Agent Reinforcement Learning.

Presentation 35: Junnan He - 2026.05.20

First-prediction-time approach for time-series degradation prediction.

Presentation 34: Jiarong Du - 2026.05.06

Solving Distributed Flexible Job-Shop Scheduling Problem based on deep reinforcement learning and GNN.

Presentation 33: Guoyang Bian - 2026.04.22

Reinforcement Learning for Dynamic Disassembly Line Scheduling.

Presentation 32: Ce Duan - 2026.03.25

Advanced Flow Matching Algorithms for Fast Inference and Stable Generation.

Presentation 31: Yixi Wei - 2026.03.11

Conditional-based Diffusion Model for Time Series Imputation.

Presentation 30: Zhicheng Chen - 2025.01.13

Gradient Perturbation-Based Federated Optimization.

Presentation 29: Man Li - 2025.12.30

Enhancing Physics-Informed Neural Networks via Advanced Deep Learning Architectures.

Presentation 28: Qinghe Dong - 2025.12.16

Reinforcement Learning for Dynamic Disassembly Line Scheduling.

Presentation 27: Jinghao Liu - 2025.12.02

Control of uncertain quantum systems in quantum entanglement-driven creation and evolution.

Presentation 26: Mohan Niu - 2025.11.18

Information-Efficient Representation in Reinforcement Learning: A Unified Perspective.

Presentation 25: Ruichong Ma - 2025.11.04

Disassembly Scheduling Problem Based on Reinforcement Learning.

Presentation 24: Jinyi Liu - 2025.10.21

Efficient Communication in Large-Scale Multi-Agent Systems.

Presentation 23: Junnan He - 2025.10.08

Fault Prediction and Health Management for Low-Quality Data Conditions.

Presentation 22: Jiarong Du - 2025.09.24

Solving Heterogeneous Distributed Job-Shop Scheduling Problem (DFJSP ) based on deep reinforcement learning.

Presentation 21: Man Li - 2025.06.16

Design of a Solver based on Physics-Informed Neural Networks.

Presentation 20: Qinghe Dong - 2025.06.02

Knowledge Transfer and Adaptive Learning Strategies in Reinforcement Learning.

Presentation 19: Zhicheng Chen - 2025.05.19

Optimizing and Protecting Gradients in Federated Learning for Privacy, Efficiency, and Personalization.

Presentation 18: Jinghao Liu - 2025.05.05

Description: Quantum Stochastic Gradient Descent Methods (QSGD) in the Distributed Perspective.

Presentation 17: Mohan Niu - 2025.04.21

Description: Efficient Representation of Multi-Agent State Spaces.

Presentation 16: Junnan He - 2025.04.14

Description: Relationship between Feature Extraction Capability and Model Structure for Time Series Data.

Presentation 15: Jinyi Liu - 2025.03.31

Description: Improve Sample Efficiency in Multi-agent Reinforcement Learning by Exploration and state representation.

Presentation 14: Ruichong Ma - 2025.03.17

Description: Job Shop Scheduling based on Hierarchical/Multi-agent Reinforcement Learning.

Presentation 13: Jiarong Du - 2025.02.28

Description: Optimization Methods for Distributed Scheduling Problems.

Presentation 12: Man Li - 2025.02.13

Description: Physics-Informed Neural Networks (PINNs) Capable of Learning from Noisy Data.

Presentation 11: Qinghe Dong - 2025.01.20

Description: Distributed Multi-agent Reinforcement Learning.

Presentation 10: Zhicheng Chen - 2025.01.09

Description: Gradient-based Acceleration for Federated Learning Convergence.

Presentation 9: Jinghao Liu - 2024.12.25

Description: Design of Distributed Filter Based on Linear Matrix Inequality.

Presentation 8: Junnan He - 2024.12.13

Description: Multi-view Representation Learning Based on Information Bottleneck.

Presentation 7: Ruichong Ma - 2024.11.28

Description: Dynamic Multi Objective Job Shop Scheduling Based on Reinforcement Learning.

Presentation 6: Jinyi Liu - 2024.11.14

Description: Improve Sample Efficiency in Multi-agent Reinforcement Learning by Exploration.

Presentation 5: Mohan Niu - 2024.10.31