NTU WASP Collaboration Projects

Adversarial Machine Learning in Big Data Era

Objective: Improve the security of existing machine learning algorithms against real-world attackers

PIs: Bo An (NTU), Chew Lock Yue (NTU), Christos Dimitrakakis (Chalmers), Devdatt Dubhashi (Chalmers)

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Co-evolutionary Reinforcement Learning for Multi-Agent Systems

Objective: To develop co-evolutionary algorithms for reinforcement learning in multi-agent systems

PIs: Mikael Johansson (KTH),  Chew Lock Yue (NTU), Bo An (NTU)

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Deep reinforcement learning of driving using virtual paths

Objective: Interactive training of deep networks for vision-based autonomous systems. Reproducible machine learning of navigation and path following in autonomous vehicles such as cars and drones

PIs: Michael Felsberg (LiU), Kai-Kuang Ma (NTU)

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Management beyond the edge

Objective: Computing capacity in edge locations and the wireless access are managed separately. However, delivering the full potential of MECs requires that edge locations and wireless networks be managed in concert

PIs: Erik Elmoroth (UmU), Kai-Kuang Ma (NTU)

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Scalable Multi-Robot Sensor Fusion, Localization, Navigation, and Control

Objective: Improved algorithms for sensor fusion, localization and coordination for search and rescue operations and surveillance applications

PIs: Fredrik Gustafsson (LiU), Dimos Dimarogonas (KTH), Hu Guoqiang (NTU)

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Visualization for understanding and developing machine learning

Objective: Develop advanced techniques and tools for visualizing different aspects of machine learning jointly in the same framework.

PIs: Anders Ynnerman (LiU), Jianmin Zheng (NTU)

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