香港中文大学信息工程系老师教授导师介绍简介-Guoliang Xing

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Professor, IEEE Fellow
Department of Information Engineering
The Chinese University of Hong Kong

Work E-mail: glxing AT ie.cuhk.edu.hk
Personal E-mail: guoliang.xing AT gmail.com

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Welcome to CUHK AIoT Lab! Our research lies at the interface between systems, embedded AI, data/information processing algorithms, and domain sciences, with a focus on interdisciplinary applications in health, environment, and energy. Our lab develops new technologies at the frontier of mobile health, Cyber-Physical Systems (CPS), Internet of Things (IoT), wireless networks, security and privacy. Several mobile health technologies developed in our lab have been commercialized and used by thousands of users. Prof. Xing led the development and field deployment of several large-scale cyber physical systems, including 20+ seismic monitoring systems on two live volcanoes in South America. He has been awarded 10 NSF grants, including 4 large multi-institute grants from major NSF interdisciplinary programs (Smart and Connected Health, Cyber Physical Systems, Cyber-Innovation for Sustainability Science and Engineering, and Cyber-Enabled Discovery and Innovation). Prof. Xing has served as the Steering Committee member, General Chair, and TPC Chair of several international conferences including IPSN – IEEE/ACM’s premier conference on information processing in sensor systems.

Awards & Recognitions

Withrow Distinguished Scholar Award, College of Engineering, MSU, 2014
Faculty Early Career Development (CAREER) Award, National Science Foundation, 2010.
Best Paper Award, “Nemo: A High-fidelity Noninvasive Power Meter System for Wireless Sensor Networks”, SPOTS Track, the 12th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), 2013.
Best Paper Award, “Beyond Co-existence: Exploiting WiFi White Space for ZigBee Performance Assurance”, the 18th IEEE International Conference on Network Protocols (ICNP), 2010.
Best Paper Finalist, “Aquatic Debris Monitoring Using Smartphone-Based Robotic Sensors”, the 13th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), 2014.
Best Paper Finalist, “Imaging Volcano Seismic Tomography in Sensor Networks”, the 10th Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON), 2013.
Mark Weiser Best Paper Award Runner-up, “Supero: A Sensor System for Unsupervised Residential Power Usage Monitoring”, the 11th IEEE International Conference on Pervasive Computing and Communications (PerCom), 2013
Best Paper Finalist, “Passive Interference Measurement in Wireless Sensor Networks”, the 18th IEEE International Conference on Network Protocols (ICNP), 2010.
Mark Weiser Best Paper Award Runner-up, “Negotiate Power and Performance in the Reality of RFID Systems”, the 8th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom), 2010.
Best Mobile Application, Silver Award, “SPOT – a smartphone-based platform to tackle heterogeneity in smart-home systems”, the Third Mobile App Competition, the 21st International Conference on Mobile Computing and Networking (MobiCom), 2015
Best Mobile Application, Third Place, “iBreath: A Smartphone Application for Breathing Monitoring during Running”, the Second Mobile App Competition, 20th Annual International Conference on Mobile Computing and Networking (MobiCom), 2014.
Best Mobile Application, Third Place, “iSleep: A Smartphone Application for Unobtrusive Sleep Quality Monitoring”, the First Mobile App Competition, 19th Annual International Conference on Mobile Computing and Networking (MobiCom), 2013.

Research Projects

💡 Smart Mobile Health Systems: A key global challenge today is to deliver high quality yet economically efficient healthcare solutions. The prominence of mobile technologies holds the promise of fundamentally transforming today’s reactive, hospital-centered healthcare practice to proactive, individualized care, and shifting the focus from disease to wellbeing. Our work on mobile health focuses on 1) building novel mobile systems that can monitor holistic health data ranging from biological rhythms (heart/respiration rate, sleep quality etc.), daily activities (work, family routine, exercise, etc.), to social interactions in dynamic, challenging environments, 2) transforming health data to behavioral, psychological, and physiological models using novel sensing and data analytics techniques, and 3) developing motivational feedback systems to empower individuals to improve lifestyles and participate in their own health treatment.

Biological rhythm monitoring and regulation. Biological rhythms, including sleep/wakefulness cycle, heartbeat, and respiration, play a central role in maintaining our daily productivity and wellbeing. We develop novel systems that leverage off-the-shelf smartphones and wearables for long-term, continuous, accurate biological rhythm monitoring and regulation.

Integrated mobile sensing and motivational feedback for family and community wellness. We are developing integrated activity routine sensing and feedback systems that empower families and communities to actively engage in tackling chronic diseases such as obesity, depression, diabetes, and dementia. Our system can autonomously log family/community routines in an unobtrusive, privacy-preserving manner, and motivate members to work together toward improved wellness.

Unobtrusive sleep quality profiling. Over 40 million people in the US suffer from long-term sleep disorders. We developed mobile systems for unobtrusive, in-place sleep monitoring. We aim to go beyond the basic quantification of sleep quality to the provision of tailored behavioral feedback in the form of data-driven and clinician-approved actionable recommendations for improving sleep.

💡 Cyber-physical Systems and Internet of Things. CPS and IoT interact with the physical world by tightly integrating sensing, actuation, computation, and physical objects. As a key enabling technology for many critical domains such as environment, smart cities, transportation, and smart grids, CPS and IoT have been recognized as a top national research priority in several US presidential reports. Many CPS and IoT systems must process large volume of data from dynamic environments under tight energy and real-time constraints. We have developed new systems and computing paradigms for such data-intensive CPS/IoT applications. My group has developed new systems and computing paradigms for such data-intensive CPS applications.

Real-time 4D volcano tomography. We developed new wireless sensor systems for real-time and long-lived volcano monitoring, and deployed 20+ nodes on two live volcanoes in Ecuador and Chile. These systems can analyze seismic signals and compute real-time, full-scale three-dimensional tomography of the volcano conduit system within the network in a distributed manner.

Robotic sensor systems for aquatic monitoring. We developed an aquatic robot system that integrates an off-the-shelf smartphone and a gliding robotic fish for debris monitoring, fish tracking, and harmful algae blooms (HABs) detection. We also developed new aquatic diffusion process profiling and spatiotemporal aquatic field reconstruction algorithms.

Data center thermal/energy management. We developed a novel cyber-physical approach for thermal management in data centers, which integrate enables more efficient thermal/power management. It predicts the temperature evolution of a data center in real time, and then finds the temperature setpoints, cold air supply rates, and the speeds of server internal fans to minimize the expected total energy consumption of cooling and circulation system.

Networked Vehicular Systems: Driver Sensing and Wireless Networking. We propose a novel cross-layer wireless design approach that leverages signatures of upper-layer vehicular protocols to improve PHY and link layer performance. We also develop a system based on smartwatches and smartphones, which detects the driver's unsafe driving behaviors in a real-time manner.

CPS platforms and performance control frameworks. We develop a smartphone-based platform for data-intensive cyber-physical applications, which has been adopted in several large-scale volcano-monitoring sensor systems and aquatic robotic systems. We also proposed a unified sensing fidelity and real-time performance control framework for cyber-physical systems whose operations are subject to uncertainties from physical environments.

💡Security and Privacy for Internet of Things. Internet of Things (IoT) involves the increasing prevalence of objects and entities that are usually wirelessly connected and communicate within short distances. Our work focuses on identifying critical security and privacy vulnerabilities of and developing novel, practical counter measures for Near Field Communication (NFC), Bluetooth, and visible light communication (VLC).

Practical Bluetooth sniffing and identification systems. Bluetooth has become the de facto wireless interface for mobile and IoT devices. We developed the first practical Bluetooth traffic sniffing and identification systems, and proposed countermeasures. Our results have significant implications on IoT security, localization and tracking.

Near Field Communication (NFC) security. NFC has enjoyed drastic penetration in mobile payment, wearable devices, smart appliance, logistics, and smart objects and tags. We are among the first to systematically study the eavesdropping vulnerability of NFC, and design a hardware security system against passive eavesdropping based on wireless energy harvesting.

Secure Visible Light Communication (VLC) for IoT. VLC is a promising connectivity technology for IoT thanks to its extreme scalability and pervasive lighting infrastructure. We have developed the first practical VLC system for smartphones and IoT devices based on new 2D barcodes, formally analyzed the security of VLC systems, and proposed physical security enhancement mechanisms.

💡Wireless Coexistence in Open Radio Spectrum: Curses and Blessings. We are among the first to systematically study the issue of co-existence between Wi-Fi and ZigBee networks. We also demonstrate the significant benefits of exploiting cross-technology wireless interference. We develop new systems that utilize ZigBee radios to identify the existence of Wi-Fi networks which have been used for WiFi discovery on mobile devices and time synchronization in large ZigBee networks.

Group

Mohammad-Mahdi Moazzami (MSU, Ph.D, 2017, Samsung Research)
Dennis Philips (MSU, Ph.D candidate)
Wahhab Al Bazrqaoe (MSU, Ph.D candidate)
Alireza Ameli (MSU, Ph.D candidate)
Chongguang Bi (MSU, Ph.D candidate)
Deliang Yang (MSU, Ph.D candidate)
Linlin Tu (MSU, Ph.D candidate)
Fatme El-Moukaddem (Ph.D, 2012, co-advised with Eric Torng)
Jun Huang (Ph.D, 2012, Assistant Professor at Peking University, China)
Ruogu Zhou (Ph.D, 2014, Postdoc, 2014-2015)
Jinzhu Chen (Ph.D, 2014, GM Research)
Yu Wang (Ph.D, 2015, Samsung)
Tian Hao (Ph.D, 2015, Postdoc, 2015-2016, IBM Research)
Rui Tan (Postdoc, 2011-2013, Assistant Professor at Nanyang Technological University, Singapore) `

Education

Washington Univ. in St. Louis, St. Louis, MO

D.Sc. Computer Science & Engineering, 2006
M.S. Computer Science & Engineering, 2003

Xi'an JiaoTong University, Xi'an, China

M.S. Computer Science & Technology, 2001
B.S. Electrical Engineering, 1998

Employment

Department of Information Engineering, Chinese University of Hong Kong

2018 - present, Professor

Department of Computer Science and Engineering, Michigan State University

2013 - 2018, Associate Professor
2008 - 2013, Assistant Professor

Department of Computer Science, City University of Hong Kong

2006 - 2008, Assistant Professor

Palo Alto Research Center (PARC), CA

5/2004-8/2004, Research Intern