How do artificial intelligence (AI) algorithms learn to predict and make decisions? Can we entrust them with decisions that affect our lives and societies? Are they neutral and as immune to societal imperfections as commonly thought? Nello Cristianini at the University of Bristol investigated challenges emerging from data-driven AI, addressing issues such as gender biases in AI algorithms, and shifts in people’s emotions reflected in social media content.
ERC grantee Martin Vechev, originally from Bulgaria, is a computer science professor at ETH Zurich and the leader of its research lab working in the field of artificial intelligence (AI). His ERC-funded project was the first to combine advanced programming languages with machine learning technics, aiming to fundamentally change how developers build software. Based on the results of his ERC project, he co-founded a start-up that was recently acquired by a leading cybersecurity company. In this interview, Vechev talks about his ERC-funded work, AI breakthroughs, and Europe’s future in the field of AI.
Quantum computers are the Holy Grail of information theorists. For years, scientists have been trying to crack their mysteries, to harvest their interesting applications. They are predicted to have tremendous computational power, exponentially larger than the computers available today. However, so far, they have been difficult to actually build. Prof. Ashley Montanaro will investigate the path from the theoretical foundations of quantum computing their applications to real-life problems.
ELECTION SERIES #3
The traditional pencil-and-paper method to mark your vote in the polling booth has been gradually replaced by electronic voting machines in many countries, in Europe and beyond. Ensuring the security of electronic voting machines and quelling fears of vote-rigging have become ever more important. One ERC-funded researcher has been working tirelessly to develop such an e-voting system through two projects, SEEVS and its follow-up SEEVCA.
The increasing development of wearable technology sparks the need for new, innovative ways to interact with our shiny gadgets. Deviating from the conventional approach based on touch-sensitive devices, Prof. Jürgen Steimle aims at producing body-worn user interfaces that can be applied directly on the skin. Highly personalised, biocompatible and ultrathin, these devices will seamlessly blend with the human skin to create a technological extension of our body.
The amount of currently available biomedical data is overwhelming. Large databases exist at different scales, from genes, to proteins, to patients' histories. But what do scientists do with all this information? Serbian-born Professor Nataša Pržulj, from University College London, works with Big Data to establish patterns and gain knowledge that could revolutionise how we treat diseases.
Group theory, functional analysis and ergodic theory – three distinct areas of mathematics that meet within the theory of von Neumann algebras. The RIGIDITY project, funded by the ERC, aims to classify families of von Neumann algebras.
Understanding complex structures means separating irrelevant information to get to something simpler and easier to understand. When you look at something from a distance – although you don’t see all the details, you can still describe what you see. ERC grantee Balázs Szegedy has developed several mathematical tools for providing a compressed yet useful view of complex structures.
How does one infer the dynamics of a DNA minicircle in solution? How does one align the neuronal firing patterns of several neurons across individuals? These questions are intrinsically statistical, but nevertheless escape the traditional tools of statistics. The ComplexData project investigated such questions from a mathematical and an applied context.
