Strategiske, tværgående forskningsprojekter, ledet af DIREC-forskere – og ofte i samarbejde med eksterne samarbejdspartnere – har til formål at levere værdi for både den videnskabelige verden og samfundet.Explore-projekterne er små agile forskningsprojekter med det formål at screene nye ideer.
Constructing cyber-physical systems with humans in the loop is important in many application areas to enable a close co-operation between humans and machines. However, there are also many challenges to overcome when constructing such systems with current software technologies and human-centered design approaches.
En robotdatabase med information om tidligere robotløsninger kan spare produktionsvirksomheder tid og penge og gøre det muligt også for mindre firmaer at automatisere deres produktion. Det er konklusionen i ReRoPro-projekt. Det lyder måske lige til, men der er en række udfordringer forbundet med at lave en robotdatabase. Med input fra industrien og internationale eksperter, har forskerne nu fået en langt bedre forståelse af udfordringerne.
A recurring problem of digitalised industries is to design and coordinate hybrid systems that include IoT (Internet of Things), edge, and cloud solutions. Currently adopted methods and tools are not effective to this end, because they rely too much on informal specifications that are manually written and interpreted by humans.
Several highly popular YouTube channels for mathematics and other scientific content (e.g., 3blue1brown, Numberphile, Veritasium) with millions of views indicate that learners may respond very positively to professionally produced educational videos. This project aims at creating and evaluating an initial library of such videos to supplement teaching in algorithms.
We will investigate how to combine secure multiparty computation and blockchain techniques to obtain more efficient privacy-preserving computation with accountability.
As cyber-physical systems (CPSs) are becoming ever more ubiquitous, many of them are considered safetycritical. We want to help CPS manufacturers and regulators with establishing high levels of trust in automatically synthesized control software for safety-critical CPSs.
The overall purpose of this project is to define, investigate, and provide preliminary methodologies for scheduling and routing microliter-sized liquid droplets on a planar surface in the context of digital microfluidics.
Sensitivity measures how much program outputs vary when changing inputs. We propose exploring novel methodologies for specifying and verifying sensitivity properties of probabilistic programs.
This project will quantify the biases and uncertainties associated with human mobility data collected through digital means, such a smartphone GPS traces, cell phone data, and social media data.
Effect systems are currently a hot research subject in type theory. Yet many effect systems, whilst powerful, are very complicated to use, particularly by programmers that are not experts at type theory. Effect systems with inference can provide useful guarantees to programming languages, while being simple enough to be used in practice by everyday programmers.
Programs running on a general-purpose computer consume a considerable amount of energy. Some programs can be translated into hardware and executed on an FPGA. This project will explore the trade-offs between executing a program in hardware and executing it in software relative to energy consumption.
The challenge to the research community is how to extend existing verification technologies to cope with software systems comprising AI components. This is an unchartered territory and one of the most pressing research challenges in AI. The industrial importance of this topic is closely related to the question of liability in case of malfunctioning products. Over a 4-month period the explore project will provide a state-of-the-art survey and identify research directions to be followed.
Artificial Intelligence brings the promise of technological means to solve problems that previously were assumed to require human intelligence, and ultimately provide human-centered solutions that are both more effective and of higher quality in a synergy between the human and the AI system than solutions that are provided by humans or by an AI system alone.
