Data is our capital for innovation. Twinner makes use of very different forms of Machine learning. These include, in particular, Deep learning in order to achieve massive simplification of production and work processes.
Data science and Machine learning not only help to automate work steps, but also to make more accurate and faster decisions. First of all our data engineers process the different sensor data (2D, 3D, etc.) into machine-readable clusters. These workflows are then automated, so that the systems for training and execution are continuously supplied with data.
Our Data scientists then design models, e.g. with Deep learning frameworks, in order to gain insights from these data in a matter of seconds, that would otherwise only be possible with disproportionate effort. Our Twinner Data doctors thus participate in the digital measurement of the world, and increase the efficiency of a wide range of applications to an unprecedented extent.
From the raw data of the sensors of a vehicle digitization, we generate almost 2 GB of data, which are available for further processing. Building on this, Machine learning is indispensable, for example, for the fully automatic classification of motor vehicles in all their individual details. From these multi-dimensional data structures, we can make very accurate statements about vehicle damage, accident history, authenticity of mileage, market value of used vehicles, and possible repair costs.
Maxim leads the Artificial intelligence team at Twinner. He is an expert in Machine learning and multidimensional data analysis. Together with his team he is responsible for all processes necessary for the analysis of large data models.
Maxim holds a PhD in physics, and did research in the field of astrophysics at Twinner in Novosibirsk, at HU Berlin, and at the Max Planck Institute for Physics in Munich before working at Twinner. At the Deutsches Elektronen-Synchrotron (DESY) he led the development of AI algorithms for the analysis of large amounts of data, as well as Monte-Carlo simulations for optimizing the MAGIC telescope performance. His knowledge of different disciplines of Machine learning, such as Transfer learning and Single shot object detection, make Maxim a true Twinner professional.
#Caffe #Kibana #OpenAI #TensorFlow #Python #DecisionTrees #NeuralNetworks #DeepLearning #Football #Art #IceHockey
Simone is also an expert in the analysis of complex data, generated in multi-layered digitization processes. Big data in the upper Petabyte range is not a buzzword for Simone, but is part of the daily business of a Data scientist at Twinner.
Simone studied physics in Rome and received his PhD in astrophysics in Potsdam. At DESY (Deutsches Elektronen-Synchrotron) he was responsible for the evaluation of complex astrophysical data, and developed an algorithm for the parallel deconvolution of large amounts of data. He did design systems with classical statistical evaluation methods, as well as with modern methods of data engineering, in order to generate corresponding semantics from a large amount of raw data. Simone is an enthusiastic Data scientist and pragmatic Senior software engineer, who masters the entire software stack. Prior to Twinner, he worked in NLP on the development of Chat bots for recruiting processes.
When it comes to leading strong interdisciplinary teams, and turning an idea into a marketable product, you profit form an experienced Project manager like Ceyhun.
A special preference for new software stacks is responsible for the fact, that new approaches are often carried out into internal workshops as prototypes, in order to test their potential for Twinner. He studied mechantronics in Istanbul, and had several patent applications in his mid-20s. But Ceyhun is a strong engineer, who is not satisfied with academic prototypes. His first Tech Startup developed a novel carbon-based battery type for solar energy and mobile devices, which won numerous international awards. Already before the end of his studies, he sold his technology company, in order to devote himself to software development in the field of renewable energies in Germany.
Already before the end of his studies, he sold his technology company in order to devote himself to software development in the field of renewable energies in Germany. Prior to Twinner, Ceyhun was CTO of a Fintech Startup, and was responsible for building the backend software for a blockchain-based trading platform for crypto currencies.
#Docker #Heroku #AgileDev #Blockchain #Python #TensorFlow #DeepLearning