Valeria Vlasova researches innovations and how they affect the economy and society. Here, she tells the HSE University Young Scientists project when she first got the idea to go into science, where to read about trends in the development of Russian science and innovation and what her everyday life is like.
Research & Expertise
Based on the results of a project competition, two new laboratories are opening at HSE University’s Faculty of Computer Science. The Laboratory for Matrix and Tensor Methods in Machine Learning will be headed by Maxim Rakhuba, Associate Professor at the Big Data and Information Retrieval School. The Laboratory for Cloud and Mobile Technologies will be headed by Dmitry Alexandrov, Professor at the School of Software Engineering.
One of the winning projects of a competition held by HSE University’s Mirror Laboratories last June focuses on the use of machine learning technologies to predict the outcomes of acute coronary syndrome. It is implemented by HSE University’s International Laboratory of Bioinformatics together with the Research and Educational Centre of the Medical Institute at Surgut State University. Maria Poptsova, Head of the International Laboratory of Bioinformatics and Associate Professor at HSE University’s Faculty of Computer Science, talks about how this joint project originated, how it will help patients, and how work to implement it will be organised.
Optimising a city's transportation system requires insights into the dynamics of urban traffic to understand where, how, when, and to what extent people travel within the city. The rationale behind route selection and the choice of transportation mode are also of importance. The primary source of this data is the travel diary, a tool designed to survey people's transport behaviour. Based on a paper by Maria Sergienko, a master's student of the HSE Faculty of Urban and Regional Development, IQ.HSE examines how people's daily travel can be described in detail and why an automated diary cannot yet completely replace its manual counterpart.
Experts from Russia and China will discuss new challenges and opportunities for business cooperation between the two countries, including those using advanced digital technologies. The event will take place on September 28 at the HSE building on Pokrovsky Bulvar. The forum is expected to be held annually.
International academic and educational cooperation is a vital aspect of activities for Russian universities. At the beginning of the new academic year, Vice Rector Victoria Panova addresses HSE's initiatives in this area.
HSE University’s Institute for Public Administration and Governance (IPAG) has conducted a proactive independent study of digital travel services. Based on the results of this, a rating of 40 tourism platforms was compiled. The platforms were assessed according to 75 parameters. The ratings include those platforms that, in addition to hotel booking services, provide a set of additional options for tourists, are also present in various industry lists, and are often mentioned in media reviews.
An international consortium of research organisations from China, India, and Russia, including HSE University’s Faculty of Urban and Regional Development represented by experts from the Vysokovsky Graduate School of Urban Studies and Planning and the Centre for Social Research and Technological Innovation (CITY), is developing an index of technological and spatial urban development (the Urban & Innovation Environment Index). Recently, a list of the top 10 largest cities of the BRICS countries was published on the project’s website. The Russian capital took the first place in the ranking, followed by Beijing, Shanghai, Sao Paulo, and Guangzhou.
HSE researcher Frol Sapronov believes that doing science, for all its complexity and seriousness, should be fun. He told the HSE Young Scientists project how he researches dyslexia in adults and why he tries not to be offended by criticism of his work.
A team of researchers from HSE University, jointly with the Yandex School of Data Analysis and Yandex Cloud, have developed a neural network for anticipating El Niño climate anomalies. The new algorithm enables more precise predictions of changes in the average surface temperature of oceanic waters that can trigger natural disasters in specific regions of the world. At present, the model is capable of predicting El Niño events one and a half years in advance, and the researchers are working towards extending the forecast period to two years.