Artificial Intelligence
Deep reinforcement learning, multi-agent systems, and neural networks that learn to make intelligent decisions in complex environments.
Reinforcement LearningMulti-Agent SystemsDeep Learning
Research signal map
Live themes across our current tracks.
Research
What we're working on.
Our ongoing initiatives pushing the boundaries of AI, robotics, and control systems.
Robotics
Humanoid and quadruped robots with advanced perception and control systems that enable physical interaction with the real world.
Humanoid RobotsComputer VisionMotion Control
Autonomous Vehicles
From model predictive control to AI-powered decision making, we develop the intelligence that enables vehicles to navigate safely and efficiently through complex traffic environments.
Trajectory PlanningModel Predictive ControlTraffic Optimization
Large Language Models
Multimodal AI systems that combine vision and language understanding for intelligent perception and decision support.
Multimodal AIVision-LanguageDecision Support
Control Systems
Advanced model predictive control, robust control theory, and hybrid approaches for spacecraft, vehicles, and robots.
MPCRobust ControlSpacecraft
Research
What we're working on.
Our ongoing initiatives pushing the boundaries of AI, robotics, and control systems.
- Multi-Agent Traffic OptimizationDeveloping cooperative multi-agent reinforcement learning algorithms for intelligent traffic signal control.Reinforcement Learning
- Spacecraft Attitude ControlAdvanced model predictive control algorithms for precise spacecraft attitude stabilization.
- Comfort-Aware Autonomous DrivingTrajectory optimization balancing safety, efficiency, and passenger comfort.
- Vision-Language PerceptionMultimodal AI systems combining visual perception with language understanding.
At BrainUp, we envision a future where artificial intelligence and robotics operate as reliable partners to humans.
Our goal is to develop intelligent systems that not only perform complex tasks, but also understand context, adapt to uncertainty, and act safely in real-world environments.