machine learning

Distinguished Paper Award at USENIX Security Symposium 2022

The paper “Dos and Dont’s of Machine Learning in Computer Security”, co-authored by Dr. Fabio Pierazzi, member of the Cybersecurity Group (CYS) at the Department of Informatics at King’s College London, received a prestigious Distinguished Paper Award at the USENIX Security Symposium 2022, one of the flagship cybersecurity conferences

“Real Attackers Don’t Compute Gradients”: Bridging the Gap Between Adversarial ML Research and Practice

At the Dagstuhl Seminar on Security of Machine Learning in July 2022, experts from all over the world met to discuss research trends and future directions for research in protecting ML-based systems. The seminar featured a mix of academics, young researchers, and industry practitioners. Despite the relaxed atmosphere, the seminar inspired diverse questions—among which, a recurring theme entailed the practical relevance of related research. For example, should industry truly be worried about the attacks portrayed in research papers, and are the assumptions made in research truly representative of the real world?

Making Machines Better Learners

Helen Yannakoudakis from KCL Informatics is working on the next generation of machine learning models for natural language processing that can learn more effectively and with less training data. Along the way, she is also making existing approaches better from detecting hateful memes to supporting health diagnostics, the impact of her work is considerable.

King’s investigates the use of quantitative modelling to predict innovation programme success.

This work was motivated by Professor Elena Simperl’s experience of leading and supporting competitive EU-funded projects that offer business incubation and acceleration services to data-centric startups and SMEs (namely ODINE, DataPitch and DMS Accelerator projects). One of the key strengths of such programmes lies in their ability to attract, select and effectively allocate resources towards the most promising companies.

SAIS

SAIS (Secure AI assistantS) is a cross-disciplinary collaboration between the Departments of Informatics, Digital Humanities and The Policy Institute at King's College London, and the Department of Computing at Imperial College London, working with non-academic partners: Microsoft, Humley, Hospify, Mycroft, policy and regulation experts, and the general public, including non-technical users.

King's success in hateful memes challenge

King’s Lecturer in Computer Science, Dr Helen Yannakoudakis, was part of a team that enjoyed success in Facebook AI’s ‘Hateful Memes Challenge’ competition.