Long Wang

PhD student

Karlsruhe Institute of Technology (KIT)
Campus Süd
Institute of Telematics
Vincenz-Prießnitz-Straße 1
76131 Karlsruhe
Germany
Building 07.07 Room 210

Mobil: +49-15202689785
Email: wanglong(at)teco.edu

Short CV:

2015-now: PhD student at TECO, Karlsruhe Institute of Technology

2010-2013: Master in Communication and Information System, School of Communication Engineering, PLA University of Science and Technology

2006-2010: Bachelor of Engineering, Department of Electronic Engineering of Tsinghua University

Research Interests:

  • Signal processing/data mining in wireless sensor networks & mobile wireless Internet
  • Human Computer Interaction
  • Context recognition

Projects:

2017-now: Data Scientist @ Smart Data Solution Center (SDSC) – Smart Data Analytics for KIT Infrastrcture

Bachelor and Master’s Thesis:

  • Josef Roth, Bachelor Thesis: Indoor Outdoor Detection via Active Sound Probing, Oct. 2015- Mar. 2016
  • Meng Zhang, Master Thesis: Anomaly Detection in Building Energy Data: a machine learning method, ongoing
  • Tobias King, Bachelor Thesis: Unlock your smartphone via audio grip sensing, ongoing
  • Lennard Sommer, Bachelor Thesis: Applying Neural Network models for indoor-outdoor detection of smartphones, ongoing
  • Jianqiao jin, Master Thesis in corperation with SAP:  Anomaly Detection and Exploratory Causal Analysis with SAP XXX System, ongoing

Publications:

  • Long Wang et al, SoundGrip: Using build-in speakers and microphones to detect hand postures on smartphones, submitted to Ubicomp.
  • Long Wang et al, NeuralIO: Indoor Outdoor Detection via Multimodal Sensor Data Fusion on Smartphones, Invited paper to Sensors and Materials.
  • Long Wang et al, Point and contextual anomaly detection in building load profiles of a university campus, submitted to PSCC 2020.
  • Long Wang et al, NeuralIO: Indoor Outdoor Detection via Multimodal Sensor Data Fusion on Smartphones, submitted to Urb-IoT 2019.
  • Long Wang, Till Riedel, Markus Scholz, Michael Beigl, Panlong Yang, Phascope: Fine-grained, Fast, Flexible Motion Profiling based on Phase Offset in Acoustic OFDM Signal, Mobile Networks and Applications, accepted.
  • Long Wang, Josef Roth, Till Riedel, Michael Beigl, and Junnan Yao, AudioIO: Indoor Outdoor Detection on smartphones via Active Sound Probing, Urb-IoT 2018, Guimarães, Portugal
  • Long Wang, Till Riedel, Markus Scholz, Michael Beigl, Panlong Yang, Phascope: Fine-grained, Fast, Flexible Motion Profiling based on Phase Offset in Acoustic OFDM Signal, MobiQuitous 2018, New York City, United States
  • Long Wang, Yong Ding, Till Riedel, Andrei Miclaus, Michael Beigl. Data Analysis on Building Load Profiles: a Stepping Stone to Future Campus, 2017 International Smart Cities Conference (ISC2), Wuxi, China.
  • Long Wang , Qihui Wu, et. al. Less is More: Creating Spectrum Reuse Opportunities via Power Control for OFDMA Femtocell Networks, IEEE Systems Journal ( Volume: 10, Issue: 4, Dec. 2016 ).
  • Long Wang , Panlong Yang, et. al. Less is More: creating spectrum reuse opportunities via power control for OFDMA femtocell networks, 22nd Wireless and Optical Communications Conference (WOCC 2013), Chongqing, China, May 2013, pp. 23–27.
  • Long Wang, Jinlong Wang, et. al. A Survey of Cluster-Based Cooperative Spectrum Sensing in Cognitive Radio Networks, 2011 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC 2011), Harbin, China, July 2011, pp. 247-251.