Exploratory: Social Impact of AI and Explainable ML
Exploratory: Network Medicine
Genes disease associations have been identified by genome-wide association studies (GWAS). Unluckily, our knowledge of the mechanisms underlying these associations that are responsible for the diseases remains largely undefined. There is increasing evidence that a set of proteins associated with a disease do not work in an isolated way, but they interact with each other to form a distinct networkmodule representing perturbed and dysfunctional pathways.
Exploratory: Migration studies
Scientific migration has aroused growing interest in recent years due to its impact on governments' policies and institutions. We analyse the traits of highly-skilled people who emigrate to understand the movements' factors. Also, we focus on the evolution of researchers' collaborative network by measuring the tendency to collaborate with researchers belonging to institutions of the same country of affiliation or not and relating it to changes in affiliation to find out the factors related to scientific mobility.
Modern high-performance computing facilities (HPCs) generate a colossal amount of data. Recent studies have shown that a significant percentage (up to 3.41% of total storage capacity) of the data HPCs produce might never be used again — for reasons as mundane as improper labelling. Given that it’s often the case that large amounts of public money go into the production of that data, this is obviously hugely problematic.
Exploratory: Demography, Economy and Finance 2.0
Could data revolution help the measurement of peacefulness? Data Scientists for Social Good and Social Good organisations, such as the United Nations (UN), highlight the importance of harnessing the data revolution [1] to put the best available tools and methods to work for the well-being and its dimensions [2] or in achieving the Sustainable Development Goals [3], such as peacefulness.
Iknoor Singh, UIET, Panjab University, India | iknoor.ai@gmail.com
TransNational Access @ GATE - University of Sheffield
Exploratory: Sports Data Science
Exploratory: Social Impact of AI and Explainable ML