Innopolis University - From Zero to Hero

This open access book describes the development of Innopolis, a young Russian university established in 2012 to focus on teaching excellence in computer science, engineering, and robotics. It reports on the problems that were faced in the first decade of its development, and the adopted solutions. It shows how the key aspects for the development of the faculty, the curricula, the university structure, and the challenge of internationalization have been successfully addressed by the university management and professors, and how the solutions are scalable for other newly founded research organizations. The book is divided in five parts: “The Beginning” describes the very early days in general, from the foundation and start-up of the university with the related processes. “The People” reports on the initial hiring of the faculty members, the selection of students, and the curriculum development. “The Activities” provide information about the creation of the single research institutions and labs, and their relation to industry. “The Future” gives an outlook on the planned internationalization and faculty strategy. Eventually, “A Visual Journey” shows a selection of photographs illustrating highlights of the whole process and the current achievements. The processes and the components described built the basis for the development of Innopolis, and many of them still have a big impact on its present and its future. The fewer mistakes are made at the beginning, the higher the probability to fully achieve the initial goals

Innopolis University - From Zero to Hero

This open access book describes the development of Innopolis, a young Russian university established in 2012 to focus on teaching excellence in computer science, engineering, and robotics. It reports on the problems that were faced in the first decade of its development, and the adopted solutions. It shows how the key aspects for the development of the faculty, the curricula, the university structure, and the challenge of internationalization have been successfully addressed by the university management and professors, and how the solutions are scalable for other newly founded research organizations. The book is divided in five parts: “The Beginning” describes the very early days in general, from the foundation and start-up of the university with the related processes. “The People” reports on the initial hiring of the faculty members, the selection of students, and the curriculum development. “The Activities” provide information about the creation of the single research institutions and labs, and their relation to industry. “The Future” gives an outlook on the planned internationalization and faculty strategy. Eventually, “A Visual Journey” shows a selection of photographs illustrating highlights of the whole process and the current achievements. The processes and the components described built the basis for the development of Innopolis, and many of them still have a big impact on its present and its future. The fewer mistakes are made at the beginning, the higher the probability to fully achieve the initial goals

Toward a Better Understanding of How to Develop Software Under Stress ??? Drafting the Lines for Future Research

The software is often produced under significant time constraints. Our idea is to understand the effects of various software development practices on the performance of developers working in stressful environments, and identify the best operating conditions for software developed under stressful conditions collecting data through questionnaires, non-invasive software measurement tools that can collect measurable data about software engineers and the software they develop, without intervening their activities, and biophysical sensors and then try to recreated also in different processes or key development practices such conditions.Comment: 8 page

A new architecture and implementation strategy for non-invasive software measurement systems

Despite that non-invasive software measurement tools have proven their usefulness in software production, their adoption in software industry is still limited. Reasons for the limited distributions have been studied and analysed recently. In this paper, we propose a new architecture for non-invasive software measurement systems that address the problems of the existing systems. The outcome of our early experimentation is quite promising and gives us the desired additional confidence on its successful distribution. ?? 2018 ACM

Towards non-invasive software measurement system: Architecture and implementation

Despite that non-invasive software measurement tools have proven their usefulness in software production, their adoption in software industry is still limited. Reasons for the limited distributions have been studied and analyzed in works like (Coman et al, Proceedings of 476 the 31st International Conference on Software Engineering (ICSE 2009), Vancouver 89???99, 2009) [1]. In this paper, we propose a new architecture for non-invasive software measurement systems that address the problems of the existing systems. The outcome of our early experimentation is quite promising and gives us the desired additional confidence on its successful distribution. ?? Springer International Publishing AG 2018

Unveiling the complex structure-property correlation of defects in 2D materials based on high throughput datasets

Abstract Modification of physical properties of materials and design of materials with on-demand characteristics is at the heart of modern technology. Rare application relies on pure materials—most devices and technologies require careful design of materials properties through alloying, creating heterostructures of composites, or controllable introduction of defects. At the same time, such designer materials are notoriously difficult to model. Thus, it is very tempting to apply machine learning methods to such systems. Unfortunately, there is only a handful of machine learning-friendly material databases available these days. We develop a platform for easy implementation of machine learning techniques to materials design and populate it with datasets on pristine and defected materials. Here we introduce the 2D Material Defect (2DMD) datasets that include defect properties of represented 2D materials such as MoS2, WSe2, hBN, GaSe, InSe, and black phosphorous, calculated using DFT. Our study provides a data-driven physical understanding of complex behaviors of defect properties in 2D materials, holding promise for a guide to the development of efficient machine learning models. In addition, with the increasing enrollment of datasets, our database could provide a platform for designing materials with predetermined properties