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Cristian Axenie
Munich, Germany
After earning a PhD in Neuroscience and Robotics from TUM in 2016, Dr. Cristian Axenie spent one more year with the TUM Center of Competence Neuroengineering before joining Huawei Research Center in Munich. Since 2017 Dr. Axenie is a Senior AI and ML Research Engineer with Huawei's largest research center outside China. At the same time, Dr. Axenie leads the Audi Konfuzius-Institut Ingolstadt Lab, a Sino-German research initiative focused on combining modern AI and VR technology for applications ranging from sports technology to medical rehabilitation. Each term, Dr. Axenie teaches AI and ML for undergrads in TH Ingolstadt.
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265.5
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List your work history, including any contracts or internships
Audi Konfuzius-Institut Ingolstadt Microlab
Oct 2017 - Aug 2020 (2 years 10 months)
Principal Investigator / Head of laboratory
The AKII Microlab is a joint technical research initiative focused on developing and applying modern Artificial Intelligence and Machine Learning techniques in human-centered interactive systems. From human motion tracking and biomechanics to personalized virtual reality avatars, we target applications with impact in sports technology and medical rehabilitation.
Part of the AKII Microlab is the vision to build a strong multidisciplinary ecosystem among universities in China and Germany as well as industrial partners in our partner regions in Germany and China. The focus is on applying cutting edge technologies in real-world applications.
Practically we design and implement intelligent software modules along with proper hardware acceleration for solving formulated problems for data processing, reasoning and learning.
Part of the AKII Microlab is the vision to build a strong multidisciplinary ecosystem among universities in China and Germany as well as industrial partners in our partner regions in Germany and China. The focus is on applying cutting edge technologies in real-world applications.
Practically we design and implement intelligent software modules along with proper hardware acceleration for solving formulated problems for data processing, reasoning and learning.
Technische Hochschule Ingolstadt
Oct 2017 - Aug 2020 (2 years 10 months)
Lecturer in Artificial Intelligence and Machine Learning
Undergrad course with focus on modern methods of artificial intelligence and their applications in the area of big data analytics and real-time control for technical systems. The lecture offers an introduction to theory and application of neuronal (deep) networks, fuzzy control techniques, support-vector machines, evolutionary and genetic algorithms for optimization, reinforcement learning, distributed agent-based learning and on-line streaming machine learning.
Huawei Technologies
Apr 2017 - Aug 2020 (3 years 4 months)
Senior Research Engineer
Senior Research Engineer
AI & ML Big Data Solutions
German Research Center
AI & ML Big Data Solutions
German Research Center
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Mobile robotics - Embedded Linux Control, Artificial Intelligence, Environment mapping
Apr 2009 - May 2011
Development process:
Stage 1 : Real time fault tolerant control application
Stage 2 : Offline SLAM algorithm module design
Stage 3 : Fuzzy System for Robot Trajectory Tracking Controller Tuning
Stage 1 : Real time fault tolerant control application
Stage 2 : Offline SLAM algorithm module design
Stage 3 : Fuzzy System for Robot Trajectory Tracking Controller Tuning
Synthesis of Distributed Cognitive Systems - Learning and Development of Multisensory Integration
Oct 2011 - Mar 2016
This research interest is in developing sensor fusion mechanisms for robotic applications. In order to extend the interacting areas framework a second direction in my research focuses on learning and development mechanisms. Learning processes which take place during the development of a biological nervous system enable it to extract mappings between external stimuli and its internal state. Precise egomotion estimation is essential to keep these external and internal cues coherent given the rich multisensory environment. In this work we present a learning model which, given various sensory inputs, converges to a state providing a coherent representation of the sensory space and the cross-sensory relations.
Synthesis of Distributed Cognitive Systems - Interacting Cortical Maps for Environmental Interpretation
Oct 2011 - Mar 2016
The core focus of my research interest was in developing sensor fusion mechanisms for robotic applications. These mechanisms enable a robot to obtain a consistent and global percept of its environment using available sensors by learning correlations between them in a distributed processing scheme inspired by cortical mechanisms.
This section lets you add any degrees or diplomas you have earned.
Technical University Munich
Doctor of Philosophy (PhD), Neuroscience and Robotics
Dec 2010 - Dec 2015
"Mihail Kogalniceanu" National High-School
Junior Programmer, Mathematics and Informatics
Dec 2000 - Dec 2004
Programming
Universitatea „Dunărea de Jos” din Galați
BSc., Automation and Industrial Informatics
Dec 2004 - Dec 2008
Control Engineering and Robotics
Universitatea „Dunărea de Jos” din Galați
MSc., Advanced Control
Dec 2008 - Dec 2010
Applied Informatics in Advanced Control Programme
TELC Deutsch B1
Apr 2018
TOEFL