Vlad Constantinescu, Mr.
Vlad is a senior software engineer (with more than 12 years experience), who has been involved in commercial projects for various partners in the EU, USA, Canada, and having a variety of roles in design, engineering and research. He has worked in automotive development for Novero GmbH / Laird plc (through TotalSoft SA) since 2009, and has been involved in the commercial Machine Learning / Big Data field since 2011 (mainly in automotive - fleet management, complex system modeling). Since 2015, his interest has risen towards more academic/research topics and he has been involved more and more in applied research in machine learning (AITIA One group), focused on complex systems, statistical machine learning/deep learning and application of these concepts to medical science and biology. In 2017, he has joined the Computational Biology of Aging Group at the Institute of Biochemistry. Vlad is academically interested in statistical machine learning, focusing on the theory of emerging complexity/intelligence, approached with methods from probability theory, information theory, computer science and statistical mechanics.
. "Learning flat representations with artificial neural networks", Applied Intelligence(51): 2456–2470, (2021)
IF: 5.09AI: 0.69
. "LRRpredictor-A New LRR Motif Detection Method for Irregular Motifs of Plant NLR Proteins Using an Ensemble of Classifiers", Genes (Basel) 11(3): 286, (2020)
Starting 02.09.2016, the Institute of Biochemistry of the Romanian Academy is implementing the project “Multi-omics prediction system for prioritization of gerontological interventions”, co-funded through European Fund for Regional Development, in accordance with the funding contract signed by the Ministry of National Education and Scientific Research. The total funding for the project is 8.524.757,50 lei, of which 8.502.557,50 lei represent non-reimbursable funding. The project’s duration is 48 months.
The Systems Biology of Aging team is grateful for the "Microsoft Azure for Research" sponsorship awarded to our group. We have received cloud computing resources worth the equivalent of 20,000$ credits, and this has greatly helped us to speed up some of our research projects.