Lucian Gonçales is Ph.D. on Applied Computing at University of Vale do Rio dos Sinos (2022). In 2017, Lucian received his M.Sc. degree on Applied Computing from the Interdisciplinary Post Graduate Program on Applied Computing (PPGCA) at Unisinos. He obtained his BSc on Computer Science on 2014 at University of Vale do Rio dos Sinos (UNISINOS) under the supervision of Jorge Luis Victória Barbosa, Ph.D.
Your main research interests are related to the Software Engineering research field, specifically on: Experiments on Software Engineering, Object Oriented Software Development, Software Architectures, and Neuroscience applied on Software Engineering activities.
PhD on Applied Computing, 2022
University of Vale do Rio dos Sinos
Master of Science on Applied Computing, 2017
University of Vale do Rio dos Sinos
B.Sc. on Computer Science, 2014
University of Vale do Rio dos Sinos
Model composition plays a key role in many Software Engineering activities, for example, in the evolution of software models to add new features. Given the context, many techniques for composition of software models have arisen to support the integration of design models, enhance the maintainability of software artifacts, and minimize the effort invested by developers. However, there are many problems related to the composition of software design models such as, the imprecision and rigity of model composition assessment, and the lack of effectiveness on composition. For this, this project has the objective of (i) defining a flexible way of evaluating the composition of models effectively; and (ii) producing empirical evidence on the development of software systems.
The study of similar outcrops is one of the main tools used to characterize the heterogeneity of oil reservoirs. For this purpose, it is possible to use the Laser Scanner who captures three-dimensional points as well as images of the surface of the outcrop. This new technique of digital mapping allows the acquisition of an enormous amount of points. Thus, the main objective of the project is to develop a digital geological modeler based on GPU (Graphics Processing Unit), capable of reading huge volumes of data from the Laser Scanner, rendering them and visualizing them in real time. In addition, techniques for 3D projection, measurement, interpretation and data sharing with other tools will be studied and developed, as well as the utilization of mobile devices to analyze geologic assets. Another challenge of the project is to recover voids in the cloud of points, caused by occlusion of vegetation and shadows.