The Leipzig School of Computing and Communications (LZSCC) includes a varied group of researchers.
Research results of our team can take on many different forms, ranging from theoretical breakthroughs to proof-of-concept implementations of novel algorithmic approaches to exciting industry-driven real-world applications.
Our academic output is not only reflected by research-driven teaching, but also frequently published in highly-regarded scholarly journals and internationally recognized research conferences. Currently, members of LZSCC conduct research on the following five key topics:
Artificial intelligence and machine learning research aims to create smart computer systems that can mimic human-like thinking. The goal is to develop algorithms that learn from data, design neural networks inspired by the brain, and advance technologies for language processing, computer vision, and robotics. They also explore how these systems can make decisions autonomously and consider the ethical implications of increasingly intelligent machines in our society.
Research Projects:
[2024-2029] EPSRC: National Edge AI Hub [Suri, link]
[2024-2026] GCHQ: Cyber-MALCULT Countering Malicious Online Security Cultures [Suri]
[2023-2024] GCHQ: AISEC AI Security Vulnerabilities [Suri]
[2023-2023] INNOVATE UK: PINCH: End-to-end Cyber Security Technology to Better Understand the Risks of Deep Learning Model Stealing [Suri]
[2022-2023] DSTL: The Security Gene: Discovering Embedded Commonalities within Adversarial Machine Learning [Suri]
[2021-2024] EPSRC: TAS-S: EPSRC Trustworthy Autonomous System Node on Security [Suri, link]
Cyber security research focuses on protecting digital systems, networks, and data from unauthorized access and attacks. It involves developing techniques to identify vulnerabilities, create robust defenses, and respond to threats. Researchers study encryption methods, design secure software, analyze malware, and explore human factors in security. They also investigate emerging challenges like protecting IoT devices and countering sophisticated cyber-attacks that could impact critical infrastructure and personal privacy.
Research Projects:
[2024-2029] EPSRC: Programme Grant, SCULI: Securing Convergent Ultra Large-Scale Infrastructures [Suri, link]
[2024-2029] EPSRC: National Edge AI Hub [Suri, link]
[2024-2026] GCHQ: Cyber-MALCULT Countering Malicious Online Security Cultures [Suri]
[2024-2026] Leverhulme Trust: Securing Self-Aware Autonomous Power Networks [Suri, link]
[2023-2024] GCHQ: AISEC AI Security Vulnerabilities [Suri]
[2023-2023] INNOVATE UK: PINCH: End-to-end Cyber Security Technology to Better Understand the Risks of Deep Learning Model Stealing [Suri]
[2022-2023] DSTL: The Security Gene: Discovering Embedded Commonalities within Adversarial Machine Learning [Suri]
[2021-2024] EPSRC: TAS-S: EPSRC Trustworthy Autonomous System Node on Security [Suri, link]
[2019-2023] EC-H2020: CONCORDIA: Cyber Security Competence for Research and Innovation [Suri, link]
Formal methods research focuses on using mathematical techniques to design and verify computer systems and software. It aims to create error-free, reliable programs by applying rigorous logical reasoning. Researchers develop tools and languages to precisely specify system behavior, prove correctness, and detect flaws. This approach is crucial for critical systems where failures could have severe consequences, like in aerospace or medical devices.
Human-computer interaction research explores how people engage with technology, aiming to make digital systems more user-friendly and efficient. It involves studying user behavior, designing intuitive interfaces, and developing new interaction methods like voice commands or gesture controls. Researchers also investigate accessibility, user experience, and the psychological and social impacts of technology on individuals and society.
Interdisciplinary Computing research combines computer science with other fields to solve complex problems. It explores how computing can enhance areas like biology, physics, or social sciences. Researchers develop algorithms and tools to analyze vast datasets, model complex systems, and simulate scenarios across various disciplines. This field aims to leverage computational power and techniques to drive innovation and discoveries in diverse domains, from climate modeling to personalized medicine.
Software engineering research focuses on improving methods for designing, developing, and maintaining high-quality software systems. It explores efficient coding practices, project management techniques, and tools for testing and debugging. Researchers study ways to enhance software reliability, scalability, and security. They also investigate agile methodologies, user-centered design, and strategies for managing large-scale software projects in diverse domains, from mobile apps to complex industrial systems.
Thomas Schmid is a Lecturer in Computing at Lancaster University in Leipzig and a founding member of the LZSCC department. His research focuses on developing novel algorithms and applications for machine learning, deep learning and hybrid artificial intelligence. Thomas is chair and co-founder of the LEISYS conference, co-author of the book “Künstliche Intelligenz managen und verstehen” and engages frequently with international conferences and journals in the area of AI and medical applications of AI.
