Advanced topics in mobile and social computing (AToMSC) (Winter 2019/2020)

Details

Workload/ECTS Credits:	5 ECTS
Module:	Please refer to below univz.
Lecturer:	Prof. Xiaoming Fu; Dr. Yali Yuan
Teaching assistant:	[]
Time:	Thu. 14:00-16:00
Place:	IfI 0.101
UniVZ	[1]

Course Overview

The purpose of this seminar is to discuss some advanced topics in Mobile computing, big data and social computing. This course is a theory-oriented but with practical implications research seminar (5 ECTS), held on a weekly base and comprising the following components:

• Weekly Presentation + Weekly Paper Reading and Discussion
• Final Presentation
• Final Report

The material in the seminar is mainly drawn from the research literature in top journals/conferences, like ToN, JSAC, TMC, TPDS, TKDD, TKDE, ACM Transactions on Social Computing, SIGCOMM, CoNEXT, SIGMETRICS, INFOCOM, USENIX ATC, MOBICOM, MOBIHOC, MobiSys, Middleware, WWW, KDD, WSDM, ICWSM, SIGIR, CIKM, ASONAM, CIKM, NIPS, AAAI, IJCAI, ICDM, PERCOM, UbiComp, CSCW, ICIS, or from practical systems and case studies.

Requirements

• Each participant is required to read the assigned paper before the seminar and prepare the review of the paper, which should include the following parts:
  • Summary of the paper
  • Pros AND cons of the paper (your conclusion)
  • NOTE!! Every participant should provide the paper review BEFORE the seminar (23:59 Wednesday). => the review form is available at [Paper_Review_Form_ATCN_WS201112.doc]
• During each weekly seminar, one participant is assigned for presenting the paper (each presentation for ~30 minutes). And the list of pros and cons is discussed by all the participants.
• In the middle of the semester, everyone is requested to pick a topic and prepare:
  • Final report: prepare an essay (8~9 pages, single column) for your chosen research topic, which contains a comprehensive literature survey + a detailed discussion of some key enabling technologies
  • Final presentation: each presentation for ~20 minutes, plus ~10 minutes Q&A

Schedule

• 24 Oct. 2019
  • Informational Meeting

• 7 Nov. 2019
  • Object detection in autonomous driving
    • Ngiam, Jiquan, et al, StarNet: Targeted Computation for Object Detection in Point Clouds, 2019. (Presented by )

• 14 Nov. 2019
  • Object detection in autonomous driving
    • Liang, Ming, et al, Multi-Task Multi-Sensor Fusion for 3D Object Detection, IEEE CVPR 2019. (Presented by )

• 21 Nov. 2019
  • Object detection in autonomous driving
    • Zhou, Yin, et al, End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds, 2019. (Presented by )

• 28 Nov. 2019
  • Object detection in autonomous driving
    • Deng, Jian, et al, MLOD: A multi-view 3D object detection based on robust feature fusion method, 2019. (Presented by )

• 05 Dec. 2019
  • • No Lecture

• 12 Dec. 2019 (Final topics release)
  • • No Lecture

• 19 Dec. 2019 Course time starts at 14:00pm
  • Deep Learning For Anomaly Detection
    • Soteris Demetriou, Puneet Jain, Kyu-Han Kim, CoDrive: Improving Automobile Positioning via Collaborative Driving, IEEE INFOCOM 2018. (Presented by Yuhan Wang)

• 09 Jan. 2020
  • Cameras Everywhere (Each student selects one topic for review and submit the review report to StudIP)
    • Georgios Kaiafas, Georgios Varisteas, Sofiane Lagraa, Radu State, Cu D Nguyen, Thorsten Ries, Mohamed Ourdane, Detecting malicious authentication events trustfully, IEEE IFIP 2018. (Presented by Rezai, Masoud)
    • Anhong Guo, Anuraag Jain, Shomiron Ghose, Gierad Laput, Chris Harrison, Jeffrey P. Bigham, Crowd-AI Camera Sensing in the Real World, IEEE UbiComp 2018. (Presented by Ding-Ze Hu)

• 16 Jan. 2020
  • Cameras Everywhere
    • Erin Griffiths, Salah Assana, Kamin Whitehouse, Privacy-preserving Image Processing with Binocular Thermal Cameras, IEEE UbiComp 2018. (Presented by Cong Li)

• 23 Jan. 2020
  • Dynamic Adaptive Streaming over QUIC (Each student selects one topic for review and submit the review report to StudIP)
    • Bastian Alt, Trevor Ballard, Ralf Steinmetz, Heinz Koeppl, Amr Rizk, CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming, IEEE INFOCOM 2019. (Presented by Adhatarao, Sripriya Srikant)
    • Gadaleta, Matteo, et al., D-DASH: A Deep Q-Learning Framework for DASH Video Streaming, IEEE Transactions on Cognitive Communications and Networking 2017. (Presented by Adhatarao, Sripriya Srikant)

Final Presentations & Report

• Final Registration in FlexNow: Time TBD.

• Final Presentation:
  • Each for ~20 minutes, plus ~5 minutes Q&A

• Final Presentation Slots:
• 30 Jan. 2020 and 6 Feb. 2020
  • Object detection in autonomous driving
  • Differential Privacy in networks
  • Dynamic Adaptive Streaming over QUIC

• Final Report:
  • Essay ( 8~9 pages, single column, IEEE format)
  • Due by 23:59pm 30 March 2020