Resume

Dr. Florian Baumann
Ravensburg, Germany

Dr. Florian Baumann received his PhD in the area of Machine Learning applied to Scene Understanding in 2015. He is addicted to Machine Learning since over 10 years and published more than 20 publications. His main research area is visual recognition and solving high-demanding learning problems. Since December 2016, Florian is the Technical Director of ADASENS Automotive GmbH. He is in charge of delivering and creating the company’s products and targets as well as pre-development and research topics. This includes Machine Learning techniques and Computer Vision algorithms to solve the automotive industry's high demands.

Employment

01/2019 - today     - CTO, Dell Technologies | UDS 12/2016 - 12/2018 - Technical Director, Adasens Automotive GmbH 04/2016 - 11/2016 - Vision Systems Lead, Adasens Automotive GmbH 10/2015 - 03/2016 - Technical Team Lead, Adasens Automotive GmbH 09/2015 - 09/2015 - Development Engineer, Adasens Automotive GmbH 05/2012 - 08/2015 - PhD Student, Project Engineer, Leibniz University of Hannover 2011 - 2012 - Development Engineer, Robert Bosch Car Multimedia GmbH 2009 - 2012 - Development Engineer, Viscom AG

Awards and Grants

2014, Scientific grant  for the best business idea of a Start-Up contest. 2014, Best Student Paper Award by ICPRAM’2014. 2010, Student price for outstanding, voluntary and social engagement.

Talks

TU-Automotive Japan - Leveraging a Multi-Cloud Infrastructure for ADAS/AD CarIT Kongress Frankfurt IAA - Challenges of Deep Learning in the Development of ADAS/AD Autonomous Vehicle Test & Development Symposium 2019 - Challenges of Deep Learning in the Development of ADAS/AD Autonomous Vehicles 2019 Detroit- Chairman, opening and closing talks, Q&A session, leading the audience Image Sensors America'2019 - tbc Image Sensors EU'2019 - tbc Image Sensors Asia'2019 - tbc CarIT Kongress Berlin - Challenges of Deep Learning in the Development of ADAS/AD Connected Vehicles'2019 - tbc AVTD 2019 - Opening Keynote presentation Autosens 2019 - Synthetic Scenario Generation Automated Driving '2019 - Solving the storage conundrum Autonomous Vehicles 2019 Santa Clara - Chairman, opening and closing talks, Q&A session, leading the audience VDI'2019 - Lane Changes Assistant System for Mirrorless Cars AVTD'2018 - Unified System of Tools for ADAS AVTD'2018 - Effects of simulated Scenario on Machine Vision Algorithms CVT'2018 - Lane Change Assistant System for Commercial Vehicles IS Auto'2018 - Unified System of Tools for ADAS VDI'2018 - Making Cameras self-aware for autonomous Driving M³-UK'2017 - Machine Learning in the Automotive Industry TNT'2015 - Random Forests and its Applications to Scene Understanding WACV'2015 - Sequential Boosting for Learning a Random Forest Classifier ICIAR'2014 - Multi-Sensor Acceleration-based Action Recognition ISVC'2014 - Thresholding a Random Forest Classifier AVSS'2014 - Computation Strategies for VLBPs ICPRAM'2014 - Motion Binary Patterns SCIA'2013 - Exploiting Object Characteristics using Custom Features ISVC'2010 - Symmetry Enhanced Boosting

Program Committee

02/2019 - Advisory Board of Autonomous Vehicles 2019 Santa Clara 08/2019 - Advisory Board of Autonomous Vehicles 2019 Detroit 01/2019 - Advisory Board of IS Auto Asia 2019 01/2019 - Advisory Board of Cognitive Vehicles 2019 10/2018 - today - Advisory Board of IS Auto EU 2019 03/2018 - today - Program Committee of M³ UK 10/2017 - today - Program Committee of M³ Germany

Other Qualifications

Project management, Operational management Innovation management Patent law and Intellectual property rights Leadership skills Organizing an industry-student fair 2006 - 2012 KISS ME (Supporting students to get in contact with industry partners)

Development Skills

MS Excel, MS Word, Latex, Pages, Keynote C/C++, Obj-C, Java, MISRA HTML, PHP, SQL, XML MATLAB, R, Python

Skills
Advanced Driver Assistance Systems
Machine Learning
Computer Vision
Autonomous Driving