[agents] [Call for Participation] IEEE MSN 2021 (Virtual) Exciting Keynotes, Panel and Tutorials (Dec. 13-15) Reg. DL: Dec. 11

[Li Ruidong]

*** Please accept our apologies if you receive multiple copies of this call
for participation***

It is our great pleasure to invite you to participate in the IEEE MSN 2021
this year. Due to the COVID-19 pandemic, MSN 2021 will be held virtually
during Dec. 13 – Dec. 15, 2021.
https://ieee-msn.org/2021/

The registration and program information is provided as follows.
*Register at*: https://ieee-msn.org/2021/registration.php
Non-author Registration Fee:  $50
*Registration Deadline: December 11*
Program At Glance: https://ieee-msn.org/2021/files/booklet.pdf
Online Program: https://msn2021.info/

MSN 2021 provides a forum to present research progress, exchange new ideas,
and identify future directions in the field of Mobility, Sensing and
Networking. The exciting program of MSN 2021 has arranged with *2 keynote
speeches, 1 panel, 3 tutorials, 17 sessions, 5 workshops, and 1 poster
session*. The technical program covers a wide range of topics, including
mobile/edge/fog computing, networking, algorithm, ubiquitous sensing, big
data and AI, security, trust and privacy, and experiments.

The information for the tutorials, keynotes, and panel of MSN 2021 is
provided as follows.
*Tutorials:* https://ieee-msn.org/2021/tutorials.php
*Tutorial 1: RFID and Backscatter Communications for Motion Capture and
Fine Scale Localization*
Instructor: *Prof. Gregory D. Durgin* (Georgia Tech., USA)
*How do you capture the choreography of a ballerina’s performance? How does
a drone navigate a vast, complex shipping yard to perform inventory? How do
you condition a large-aperture antenna so that it is capable of beaming
microwave power across long distances in space?* In this tutorial, we
answer these questions by exploring the emerging world of RFID-based motion
capture and fine-scale localization.

*Tutorial 2: Federated Analytics: A New Collaborative Computing Paradigm
towards Privacy Focusing World*
Instructor: *Prof. Dan Wang, Ms. Siping Shi* (The Hong Kong Polytechnic
University, Hongkong)
*In this tutorial, we present federated analytics, a new distributed
computing paradigm for data analytics applications with privacy
concerns.* Today’s
edge-side applications generate massive data. In many applications, the
edge devices and the data belong to diverse owners; thus data privacy has
become a concern to these owners. Federated analytics is a newly proposed
computing paradigm where raw data are kept local with local analytics and
only the insights generated from local analytics are sent to a server for
result aggregation. It differs from the federated learning paradigm in the
sense that federated learning emphasizes on collaborative model training,
whereas federated analytics emphasizes on drawing conclusions from data.

*Tutorial 3: Machine Learning Security and Privacy in Networking*
Instructor: *Prof. Yanjiao Chen* (Zhejiang University, China)
*Machine learning has gradually found its way into the networking area.
Unfortunately, the vulnerability of machine learning models also infects
the networking domain, raising alarming issues that may threaten the
privacy and security of critical applications. *In this tutorial, I will
give a systematic introduction of typical attacks against machine learning
models, including adversarial attacks, backdoor attacks, membership
inference attacks, model extraction attacks, model inversion attacks and so
on. The tutorial will cover a series of works on applying modern machine
learning to networking and analyze the potential risk of current
architectures of machine learning models and its impact on networking
applications.

*Keynote 1: IoT Security * https://ieee-msn.org/2021/keynote_1.php
Speaker:* Prof. Elisa Bertino (Purdue University, USA)*
*Keynote 2: Deep Reinforcement Learning for Control and Management of
Communications Networks * https://ieee-msn.org/2021/keynote_2.php
Speaker: *Prof. Kin K. Leung* (Imperial College London, U.K.)

*Panel Topic: Digital Twins and their Applications in CPS  *
https://ieee-msn.org/2021/panel.php
Panel Chair: *Wei Zhao *(Shenzhen Institute of Advanced Technology, Chinese
Academy of Sciences)
Panel Members:
•    *Tarek Abdelzaher*, University of Illinois Urbana-Champaign
•    *Jiannong Cao*, The Hong Kong Polytechnic University
•    *Chenyang Lu*, Washington University in St. Louis
•    *Raymond Lui Sha*, University of Illinois Urbana-Champaign

Looking forward to seeing you at the MSN 2021!

IEEE MSN 2021 Organizing Committee
TPC Co-Chairs:
Geyong Min, University of Exeter, U.K.
Baochun Li, University of Toronto, Canada

General Co-Chairs:
Mohammad Shojafar University of Surrey, U.K.
Ruidong Li, Kanazawa University, Japan

Steering Committee Co-Chairs:
Jiannong Cao, The Hong Kong Polytechnic University, HK
Xiaohua Jia, City University of Hong Kong, HK
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