Lancaster Autonomous Systems and Artificial Brain Lab is at the forefront of Novel Computing, a revolutionary domain that redefines computational paradigms to solve complex global challenges with advanced, intelligent solutions. Novel Computing goes beyond conventional methods, embracing technologies like Quantum AI, Neural and Cognitive Computing, Privacy-Preserving Architectures, and Federated Learning. It includes pioneering Post-Quantum Security and Quantum Cryptography to future-proof data security, while Cognitive-inspired systems and decentralized AI approaches offer secure, scalable, and ethically aligned technology. Our lab drives this field forward with research in Neural Computing, Quantum AI, Privacy Computing, and Autonomous Systems, seamlessly integrating foundational principles with artificial cognition and cutting-edge intelligence to address pressing issues in wellbeing, sustainability, and mobility. This work includes the advancement of Explainable, Ethical, and Private AI, embedding ethics, transparency, and data security into intelligent systems essential for socially impactful applications.
Pioneering Novel Computing for the Future of AI
Our research encompasses several high-impact areas of novel computing:
- Quantum and Post-Quantum Computing: We are at the forefront of Quantum AI and Quantum Cryptography, exploring how quantum mechanics can exponentially increase computational power to tackle challenges once thought intractable. Our Post-Quantum Secure Computing research is developing cryptographic solutions that safeguard data in a quantum-enabled future, providing resilience against emerging quantum threats.
- Neural and Cognitive Computing: Leveraging principles from artificial cognition, our work in Neural Computing is building pathways toward Artificial General Intelligence (AGI). By integrating insights from human cognition and advanced digital simulations, including the Metaverse, we aim to create systems that approach human-like understanding and intelligence, redefining cognitive modeling and AI-driven intelligence.
- Privacy and Federated Learning: In line with the highest standards of data privacy, our Privacy-Preserving AI and Federated Learning initiatives enable collaborative learning without compromising sensitive data. This approach supports decentralized AI applications with built-in privacy, especially valuable for applications in healthcare, finance, and autonomous systems.
- Explainable and Ethical AI: We are advancing Explainable AI and Ethical AI to promote transparency, fairness, and accountability in machine-driven decisions. These initiatives are critical for AI’s adoption in sensitive and high-stakes environments, such as autonomous systems and interactive robotics.
- Intelligent Autonomous Systems: In autonomous systems, our research pushes the boundaries of robotics, human-centered vehicles, and AI-powered drones. We are developing advanced 5G/6G-enabled connected systems for transparent, human-AI collaboration and autonomous solutions capable of intelligent tasks in challenging environments, from disaster response to remote exploration.
Driving Innovation and Strategic Impact
Through interdisciplinary collaboration and cutting-edge projects, the Lancaster AutoBrain Lab is laying the groundwork for next-generation AI solutions that redefine computational intelligence, privacy, and security. Our commitment to Novel Computing positions us as a global leader, presenting forward-looking investment opportunities for industry partners seeking to drive meaningful impact through transformative, ethical, and high-impact technology.
| Fundamentals: | ||
| Human-Centred Computing | Ethical Computing | Quantum Informatics |
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| Artificial Brain: | ||
| Brain Theory | Neural Computation | Metaverse & Data |
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| Auto Systems: | ||
| Interactive Robotics | Internet of Vehicles | Federated Drones |
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