IEEE International Conference on Sensing, Communication and Networking
22-25 June 2020 // Virtual Conference

Program

IEEE SECON 2020 Schedule at a Glance
(times are UTC+2)
Monday
22 June 2020
Tuesday
23 June 2020
Wednesday
24 June 2020
Thursday
25 June 2020
09:00
09:30
Opening Remarks
09:30
10:00
Workshops Session 1
Channel and Wireless
Session 5
Learning
Session 9
RFID
10:00
10:30
10:30
11:00
Break Break Break Break
11:00
11:30
Workshops Session 2
Crowdsensing and Edge
Session 6
IoT and LoRa
Session 10
Localization and Tracking
11:30
12:00
12:00
12:20
Lunch Lunch
12:20
14:00
Lunch Lunch
14:00
14:30
Workshops Session 3
Road Traffic and Urban Sensing
Session 7
Light, Image, and Water
Session 11
Crowdsensing and Learning
14:30
15:00
15:00
15:30
Break Break Break Break
15:30
16:00
Workshops Session 4
Sensing and AR
Session 8
Edge IoT and Wireless
Keynote 3
Patrick Baudisch
16:00
16:30
16:30
16:50
Break Closing Remarks
16:50
17:00
Break Break
17:00
17:30
Workshops Keynote 1
Shyam Gollakota
Keynote 2
Lama Nachman
17:30
18:00

Detailed Schedule (times are UTC+2)

Keynotes

Keynote 1: Shyam Gollakota – University of Washington, US – show biography

TBD

TBD – show abstract

TBD

(Tuesday 23 June 2020 17:00-18:00 UTC+2)

Keynote 2: Lama Nachman – Intel Labs, US – show biography

Lama Nachman is an Intel fellow and Director of Anticipatory Computing Lab in Intel Labs. Her research is focused on creating contextually aware experiences that understand users through sensing and sense making, anticipate their needs and act on their behalf. She leads a multi-disciplinary team of researchers that explore new user experiences, sensing systems, algorithms and applications and transfer these capabilities to biz units to impact future Intel products. Lama has 24 years of experience in the areas of context aware computing, multi-modal interactions, sensor networks, computer architecture, embedded systems and wireless technologies. One of the most notable achievements of Nachman’s career is an Intel collaboration with Professor Stephen Hawking. Beginning in 2012, she led a team of researchers who developed a new software platform and sensing system to help Hawking communicate. Subsequently, she also led the effort to take that technology to the open source community, enabling people with disabilities worldwide to communicate using limited input and live as independently as possible. Prior to joining Intel, Lama has held senior positions at Ubicom Inc, Weave Innovations and Microsoft Corporation. Lama received her MS and BS in computer engineering at the University of Wisconsin-Madison.

Amplifying Human Potential with AI – show abstract

While AI brings great potential to improve many aspects of our lives, it also raises concerns regarding employment, privacy, safety and many others. It is time to change the narrative from human / AI competition to human / AI collaboration. AI can be utilized to amplify human potential, to assist people in everyday life, from education to manufacturing to supporting our most vulnerable population. However, to enable AI to venture into the real world and work closely with people, we need to develop contextually aware technologies that are built on robust and ethical AI. In this talk we will discuss our research in different applications as well as robust and ethical perception utilizing multi-modal sensing and sensemaking and probabilistic computing.

(Wednesday 24 June 2020 17:00-18:00 UTC+2)

Keynote 3: Patrick Baudisch – Hasso Plattner Institute, Germany – show biography

Patrick Baudisch is a professor in Computer Science at Hasso Plattner Institute at Potsdam University and chair of the Human Computer Interaction Lab. After working on mobile devices, touch input, and natural user interfaces for several years, his current research focuses on personal fabrication, i.e., how to world will change as a result of 3D printers, laser cutters, and the like. Previously, Patrick Baudisch worked as a research scientist in the Adaptive Systems and Interaction Research Group at Microsoft Research and at Xerox PARC. He holds a PhD in Computer Science from Darmstadt University of Technology, Germany. He was inducted into the CHI Academy in 2013 and has been an ACM distinguished scientist since 2014. Since 2019, he has been the chair of the SIGCHI Research and Practice Awards subcommittee.

The six challenges for personal fabrication – show abstract

Fabrication tools, such as 3D printers, laser cutters, and milling machines have been used widely in industry for over 30 years. When the original patents expired, however, these technologies started to hit a new user base—the makers. Today, we are about to witness another transition as the first fabrication devices are trying to target at an even less techsavvy audience—consumers. This spreading of technology from industry to enthusiasts to consumers suggests that fabrication could be steering for a future in which hundreds of millions of users with no technical background have access to this class of technology. The key question is: how much impact will this evolution really create—and based on what exact promise? In this talk, Patrick Baudisch will argue that 3D printing and personal fabrication in general are about to bring massive, disruptive change to interactive computing, as well as to computing as a whole. He discusses the six challenges that need to be addressed for this change to take place, and explain why he think researchers in HCI will play a key role in it.

(Thursday 25 June 2020 15:30-16:30 UTC+2)

Monday 22 June 2020

Workshops

  • IoTSenCity 2020 – The schedule for the workshop program will be available shortly
  • IUAV 2020 – The schedule for the workshop program will be available shortly
  • IEEE STP-CPS – The schedule for the workshop program will be available shortly

Tuesday 23 June 2020

Session 1: Channel and Wireless – (09:30-10:30 UTC+2)

  • c-Chirp: Towards Symmetric Cross-technology Communication over Asymmetric Channels
    D. Xia (Beijing University of Posts and Telecommunications), X. Zheng (Beijing University of Posts and Telecommunications), L. Liu (Beijing University of Posts and Telecommunications), C. Wang (Beijing University of Posts and Telecommunications), H. Ma (Beijing University of Posts and Telecommunications)
    Best paper
    candidate
  • CoHop: Quantitative Correlation-based Channel Hopping for Low-power Wireless Networks
    Y. Wang (Beijing University of Posts and Telecommunications), X. Zheng (Beijing University of Posts and Telecommunications), L. Liu (Beijing University of Posts and Telecommunications), H. Ma (Beijing University of Posts and Telecommunications), Y. Wang (Beijing University of Posts and Telecommunications)
  • mMuxing: Pushing the Limit of Spatial Reuse in Directional Millimeter-wave Wireless Networks
    Y. Yang (Beijing University of Posts and Telecommunications), A. Zhou (Beijing University of Posts and Telecommunications), D. Xu (Beijing University of Posts and Telecommunications), S. Yang (Beijing University of Posts and Telecommunications), L. Wu (Beijing University of Posts and Telecommunications), H. Ma (Beijing University of Posts and Telecommunications), T. Wei (University of Wisconsin – Madison), J. Liu (OPPO)

Session 2: Crowdsensing and Edge – (11:00-12:00 UTC+2)

  • CHASTE: Incentive Mechanism in Edge-Assisted Mobile Crowdsensing
    C. Ying (Shanghai Jiao Tong University), H. Jin (Shanghai Jiao Tong University), X. Wang (Shanghai Jiao Tong University), Y. Luo (Shanghai Jiao Tong University)
  • Combinatorial Multi-Armed Bandit Based User Recruitment in Mobile Crowdsensing
    H. Wang (Jilin University), Y. Yang (Jilin University), E. Wang (Jilin University), W. Liu (Jilin University), Y. Xu (Jilin University), J. Wu (Temple University)
  • Learn to Optimize: Adaptive VNF Provisioning in Mobile Edge Clouds
    Q. Xia (Dalian University of Technology), W. Ren (Dalian University of Technology), Z. Xu (Dalian University of Technology), P. Zhou (Huazhong University of Science and Technology), W. Xu (Sichuan University), G. Wu (Dalian University of Technology)

Session 3: Road Traffic and Urban Sensing – (14:00-15:00 UTC+2)

  • A Multi-modal Graph Neural Network Approach to Traffic Risk Forecasting in Smart Urban Sensing
    Y. Zhang (University of Notre Dame), X. Dong (University of Notre Dame), L. Shang (University of Notre Dame), D. Zhang (University of Notre Dame), D. Wang (University of Notre Dame)
  • Cellular Network Traffic Prediction Incorporating Handover: A Graph Convolutional Approach
    S. Zhao (New Jersey Institute of Technology), X. Jiang (New Jersey Institute of Technology), G. Jacobson (AT&T Labs), R. Jana (AT&T Labs), W. Hsu (AT&T Labs), R. Rustamov (AT&T Labs), M. Talasila (AT&T Labs), S. A. Aftab (AT&T Labs), Y. Chen (New Jersey Institute of Technology), C. Borcea (New Jersey Institute of Technology)
  • TransRes: A Deep Transfer Learning Approach to Migratable Image Super-Resolution in Remote Urban Sensing
    Y. Zhang (University of Notre Dame), R. Zong (University of Notre Dame), J. Han (University of Notre Dame), D. Zhang (University of Notre Dame), T. Rashid (University of Notre Dame), D. Wang (University of Notre Dame)

Session 4: Sensing and AR – (15:30-16:50 UTC+2)

  • CaraoKey: Car States Sensing via the Ultra-Wideband Keyless Infrastructure
    A. Kalyanaraman (University of Virginia), Y. Zeng (Bosch Research), S. Rakshit (Bosch Research), V. Jain (Bosch Research)

Best paper
candidate
    • MagStroke: Ubiquitous off-the-shelf Keyboard based on Magnetic Field
      H. Abdelnasser (Imperial College London), K. A. Harras (Carnegie Mellon University), M. Youssef (Alexandria University)
  • Characterization of Multi-User Augmented Reality over Cellular Networks
    K. Apicharttrisorn (University of California), B. Balasubramanian (AT&T Labs Research), J. Chen (University of California), R. Sivaraj (AT&T Labs Research), Y. Tsai (University of California), R. Jana (AT&T Labs Research), S. Krishnamurthy (University of California), T. Tran (AT&T Labs Research), Y. Zhou (AT&T Labs Research)

Best paper
candidate
  • Latency-aware Hybrid Edge Cloud Framework for Mobile Augmented Reality Applications
    A. Younis (Rutgers University), B. Qiu (Rutgers University), D. Pompili (Rutgers University)

Wednesday 24 June 2020

Session 5: Learning – (9:30-10:30 UTC+2)

  • Provisioning Edge Inference as a Service via Online Learning
    Y. Jin (Nanjing University), L. Jiao (University of Oregon), Z. Qian (Nanjing University), S. Zhang (Nanjing University), N. Chen (Nanjing University), S. Lu (Nanjing University), X. Wang (Nanjing University)
  • TrustServing: A Quality Inspection Sampling Approach for Remote DNN Services
    X. Hou (UNC), T. Han (UNC)
  • XHAR: Deep Domain Adaptation for Human Activity Recognition with Smart Devices
    Z. Zhou (University of Science and Technology of China), Y. Zhang (University of Science and Technology of China), X. Yu (University of Science and Technology of China), P. Yang (University of Science and Technology of China), X. Li (University of Science and Technology of China), J. Zhao (Illinois Institute of Technology), H. Zhou (University of Science and Technology of China)

Session 6: IoT and LoRa – (11:00-12:30 UTC+2)

  • AirSync: Time Synchronization for Large-scale IoT Networks Using Aircraft Signals
    S. Zhu (Beijing University of Posts and Telecommunications), X. Zheng (Beijing University of Posts and Telecommunications), L. Liu (Beijing University of Posts and Telecommunications), H. Ma (Beijing University of Posts and Telecommunications)
  • BLE2LoRa: Cross-Technology Communication from Bluetooth to LoRa via Chirp Emulation
    Z. Li (Harbin Institute of Technology), Y. Chen (University of Chinese Academy of Sciences)
  • FlipLoRa: Resolving Collisions with Up-Down Quasi-Orthogonality
    Z. Xu (Tsinghua University), S. Tong (Tsinghua University), P. Xie (Tsinghua University), J. Wang (Tsinghua University)
  • Hybrid Anomaly Detection Mechanisms for Integrated Electronic Systems
    Q. Qiao (East China Normal University), D. HE (East China Normal University), Y. Gao (East China Normal University), S. Zhu (Pennsylvania State University), J. Gao (East China Normal University), S. Chan (City University of Hong Kong), Q. Qiao (East China Normal University)

Session 7: Light, Image, and Water – (14:00-15:00 UTC+2)

  • Filtering Visible Light Reflections with a Single-Pixel Photodetector
    A. Galisteo (IMDEA Networks Institute), P. Marcocci (Department of Information Engineering), M. Zuniga (Delft University of Technology), L. Mucchi (Department of Information Engineering), B. G. Guzmán (IMDEA Networks Institute), D. Giustiniano (IMDEA Networks Institute), M. Zuniga (TU Delft)
  • Exploiting Color Sensors to Provide Optimal Lighting and Anonymous Tracking in Stores
    R. Zhang (TU Delft), M. Zuniga (TU Delft), V. Jelicic (Tridonic GmbH & Co KG), M. Siegel (Tridonic GmbH & Co KG)
  • Link Stability Analysis of Wireless Sensor Networks Over the Ocean Surface
    A. Shahanaghi (Virginia Tech), Y. Yang (Virginia Tech), R. M. Buehrer (Virginia Tech)

Session 8: Edge IoT and Wireless – (15:30-17:00 UTC+2)

  • Instant AoI Optimization in IoT Networks with Packet Combination
    J. Lou (University of Louisiana at Lafayette), X. Yuan (University of Louisiana at Lafayette), N. Tzeng (University of Louisiana at Lafayette)
  • Dynamic Distributed Edge Resource Provisioning via Online Learning across Timescales
    W. You (University of Oregon), L. Jiao (University of Oregon), S. Bhattacharya (Samsung AI Center), Y. Zhang (Communication University of China)
  • Expressive ASL Recognition using Millimeter-wave Wireless Signals
    P. S. Santhalingam (George Mason University), Y. Du (George Mason University), R. Wilkerson (George Mason University), A. A. Hosain (George Mason University), D. Zhang (George Mason University), P. Pathak (George Mason University), H. Rangwala (George Mason University), R. Kushalnagar (Gallaudet University)

Thursday 25 June 2020

Session 9: RFID – (09:30-10:30 UTC+2)

    • RF-Mirror: Mitigating Mutual Coupling Interference in Two-Tag Array Labeled RFID Systems
      Z. Wang (University of Technology Sydney), M. Xu (University of Technology Sydney), N. Ye (Nanjing University of Posts and Telecommunications), H. Huang (Nanjing University of Posts and Telecommunications), R. Wang (Nanjing University of Posts and Telecommunications), F. Xiao (Nanjing University of Posts and Telecommunications), z. wang (University of Technology Sydney)
  • RFCamera: Identifying RFIDs in Pixel Dimensions
    Q. Lin (the Hong Kong Polytechnic University), L. Yang (the Hong Kong Polytechnic University), Z. An (the Hong Kong Polytechnic University), Y. Guo (Neocobot Technology Co.), P. Li (Nanjing University of Posts and Telecommunications)

Best paper
candidate
  • Robust RFID-based Respiration Monitoring in Dynamic Environments
    Y. Yang (The Hong Kong Polytechnic University), J. Cao (The Hong Kong Polytechnic University)

Session 10: Localization and Tracking – (11:00-12:30 UTC+2)

  • DeepNar: Robust Time-based Sub-meter Indoor Localization using Deep Learning
    O. Hashem (Alexandria University), K. A. Harras (Carnegie Mellon University), M. Youssef (Alexandria University)
  • HF RFID-based Book Localization via Mobile Scanning
    L. Xu (Nanjing University), J. Liu (Nanjing University), X. Wang (Nanjing University), H. Gong (Nanjing University), Y. Wang (Nanjing University), L. Chen (Nanjing University), L. Xu (Nanjing University)
  • Millidegree-Level Direction-of-Arrival (DoA) Estimation and Tracking for Terahertz Wireless Communications
    Y. Chen (Shanghai Jiao Tong University), L. Yan (Shanghai Jiao Tong University), C. Han (Shanghai Jiao Tong University)
  • FlagLoc: Localization Using a Flag for Mobile Wireless Sensor Networks with Measurement Errors
    H. Wu (Sun Yat-sen University), B. Xu (Sun Yat-sen University), J. Cao (Hong Kong Polytechnic University), Y. Wang (Sun Yat-sen University), Z. Yang (Sun Yat-sen University)

Session 11: Crowdsensing and Learning – (14:00-15:00 UTC+2)

  • Privacy-Preserving Reputation Management for Blockchain-Based Mobile Crowdsensing
    Z. Wenjing (National University of Defense Technology), L. Yuchuan (National University of Defense Technology), F. Shaojing (National University of Defense Technology), X. Tao (National University of Defense Technology)
  • FlyTera: Echo State Learning for Joint Access and Flight Control in THz-enabled Drone Networks
    S. K. Moorthy (University at Buffalo), Z. Guan (University at Buffalo)
  • Optimal Resource Allocation for Crowdsourced Image Processing
    K. S. Wheatman (The Pennsylvania State University), F. Mehmeti (The Pennsylvania State University), M. Mahon (The Pennsylvania State University), H. Qiu (University of Southern California), K. Chan (US CCDC Army Research Laboratory), T. La Porta (The Pennsylvania State University)