Research Assistant

E-Mail	xiebing.wang@in.tum.de
Room	MI 03.07.059
Phone	+49.89.289.18128
Fax	+49.89.289.18107
Address	Institut für Informatik VI Technische Universität München Boltzmannstraße 3 85748 Garching bei München Germany
Homepage	http://www6.in.tum.de/Main/Wangxie

Xiebing Wang

Curriculum Vitæ

2015.9 - present	Research Assistant at Institut für Informatik VI, Technische Universität München
2012.9 - 2015.6	M.Eng. in Computer School at Wuhan University, China
2008.9 - 2012.6	B.Eng. in Computer School at Wuhan University, China

Thesis Topics

Proposal:
- Bachelor, Master Thesis: Topic 1: Multi-ROI based lane detection in heterogeneous systems
- Bachelor, Master Thesis: Topic 2: Direct data communication in heterogeneous systems
- Bachelor, Master Thesis: Topic 3: Using FPGA to implement computer vision applications
- Bachelor, Master Thesis: Topic 4: Use deep learning to evaluate performance of parallel ADAS applications with OpenCL
- Bachelor, Master Thesis: Topic 5: Using machine learning to implement vehicle identification in heterogeneous systems
- Bachelor, Master Thesis: Topic 6: Real-time and efficient vehicle tracking by using CNN and PHD filter
- Bachelor, Master Thesis: Topic 7: Fast pedestrian detection in heterogeneous systems via deep learning

On going:
- Jait Dixit: Efficient, real-time pedestrian detection with GPU-accelerated feature extraction and pattern classification (Master Thesis).

Finished:
- Christopher Kiwus: Multi-ROI based lane detection in heterogeneous systems (Master Thesis).
- Tobias Kick: Pedestrian tracking with GM-PHD Filters for heterogeneous system (Bachelor Thesis).
- Bodeit Tim: Comparing high- and low-level implementation of FPGA based lane detection (Bachelor Thesis).

Teaching and Experience

8 days intensive practical training on building eCars at SMIE 2016, SYSU, Zhuhai, China
Hardware/Software Co-Design with a LEGO car (SS 2016)
Hardware/Software Co-Design with a LEGO car (WS 2016)
Hardware/Software Co-Design with an autonomous driving car (SS 2017)

Publications

[1]	Xiebing Wang, Mingyue Cui, Kai Huang, Alois Knoll, and Long Chen. Improving the performance of adas application in heterogeneous context: a case of lane detection. In International Conference on Intelligent Transportation Systems (ITSC), October 2017. [ .bib ]
[2]	Xiebing Wang, Linlin Liu, Kai Huang, and Alois Knoll. Exploring fpga-gpu heterogeneous architecture for adas: Towards performance and energy. In International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), August 2017. [ .bib ]