Liang He

CSCI 3511: Hardware-Software Interface

CSCI 3515: Internet-of-Things: Sensing, Communication, and Control

CSCI 5575: Cyber-Physical Systems

CSCI 5800: Battery Management Systems

• Hojun Choi, CSE, since 2023 (Chancellor Scholarship 2023)
• Matthew Michaelis, CSE, since 2023 (EL of our NSF I-Corps team)
• Adarsh Thoke, CSE, since 2023
• Noorul Husssain Shaik, CSE, 2023
• John Marinelli, CSE, 2022-2023 (Outstanding Graduate of CSE Department)
• Keshav Miglani, CSE, 2022
• Samuel Wozinski, CSE, 2021-2022
• John Pace, CSE, 2020-2022 (Outstanding Graduate of Engineering College)
• Yiqin Wang, CSE, 2020-2021
• Debajit Kumar Sandilya, CSE, 2018-2020
• Aishwarya Mulkalwar, CSE, 2018-2019

• Ngoc Que Anh Tran, CSE, 2023-2024 (Outstanding Graduate of CSE Department)
• Daniel Rodriguez, CSE, 2023-2024 (Outstanding Graduate of CSE Department)
• Nathan Maas, CSE, since 2023 (Outstanding Graduate of CSE Department)
• Dennis Mills, CSE, Spring 2022 (Outstanding Graduate of CSE Department)
• John Pace, CSE, 2019-2020
• Andrew Gras, EE, 2018-2019
• Zachary Nye, EE, 2019
• Kevin Macfarlane, CSE, 2018-2019
• Devin Piner, CSE, 2018-2019
• Aaron Zapiler, ME, 2018

• 2022: e-Energy, VTC, ICPADS
• 2021: IoTDI, VTC, ICPADS
• 2020: RTCSA, ICCCN, MASS
• 2019: ICPADS, MASS, WCNC, ICNC, ICC, ICCCN, ICME, RCAR, EWSN-Poster
• 2018: ICCPS, GLOBECOM, ICNC, DSCT, VTC2018-Spring, VTC2018-Fall, ICC, MiSeNet, SNTA, WASA, CYBER
• 2017: GLOBECOM, RTAS-Demo, ICC, NAS, ICNC, MiSeNet, GLOBECOM-CQRM, NaNA, ICCC Workshops
• 2016: GLOBECOM, ICNC, NaNA, ICCVE
• 2015: ICNC, ICCVE, ICCC, IoT, E2IoT
• 2014: VTC2014-Fall, WCSP, ICNC, QShine, ICCC, IoT, ICCVE
• 2013: GLOBECOM, WCSP, ICNC, ICCC, ICCVE
• 2012: WiSARN 2012-Spring

• Regional Program Chair, The 8th Annual IEEE Int. Conf. on CYBER Technology in Automation, Control, and Intelligent Systems (IEEE-CYBER 2018)
• Publicity Co-Chair, The 7th International Workshop on Wireless Sensor, Actuator and Robot Networks (WiSARN 2013-SPRING)
• Publicity Co-Chair, The 6th International Workshop on Wireless Sensor, Actuator and Robot Networks (WiSARN 2012-Fall)

• Guest Editor: Concurrency and Computation: Practice and Experience

Toward Human-Transportation Interaction with Ubiquitous Sensing and Applied Machine Learning

Dr. Dongyao Chen, University of Michigan at Ann Arbor

Abstract: As the transportation ecosystem, e.g., vehicles, road infrastructures, becomes increasingly smarter, systems that can enhance the interaction between humans and transportation systems are of paramount importance to road safety and efficiency. Meanwhile, ubiquitous computing devices, such as smartphones and wearables, are empowered by ever-increasing sensing and communication capabilities. Although many existing applications have attempted to harvest the ubiquitous sensory data for facilitating transportation applications, e.g., navigation apps, they are often risk-prone, coarse-grained, and for special purposes. This talk will cover two representative studies that are designed for improving the safety and efficiency of the transportation ecosystem in a scalable and efficient manner. First, I will introduce VSense, a real-time data analytics pipeline for detecting a vehicle’s steering maneuver (i.e., left/right turn and lane change) only with commodity smartphone sensors. Second, I will present TurnsMap, a crowdsensing framework for analysis of risks at intersections. TurnsMap demonstrates a ubiquitous sensing + machine learning framework that is adaptive to numerous smart transportation applications/.

Security and Privacy of Tomorrow’s Connected Vehicles

Mr. Mert Dieter Pese, University of Michigan at Ann Arbor

Abstract: Modern connected and autonomous vehicles (CAVs) are equipped with an increasing number of Electronic Control Units (ECUs) that produce large amounts of data. The data is exchanged between ECUs via an in-vehicle network. Furthermore, CAVs do not only have physical interfaces, but also increased data connectivity to the Internet via their Telematic Control Units (TCUs) which make them accessible remotely just like mobile phones. As a result, an increasing number of attack vectors make vehicles an attractive target for hackers. Automotive cyber-security research is a relatively novel field which tries to respond to constantly rising threats with countermeasures. In this talk, we will give a primer on cyber-security in the automotive domain as well as discuss privacy concerns of the big data generated by cars.

Cyber-Physical Systems for Smart Cities: a Mobility Perspective

Dr. Desheng Zhang, Rutgers University

Abstract: For the first time ever, we have more people living in urban areas than in rural areas. Based on this inevitable urbanization, the research in my group is aimed at addressing sustainability challenges related to urban mobility (e.g., energy consumption and traffic congestion) by data-driven modeling and applications with a Cyber-Physical-Systems (CPS) approach in the vision of Smart Cities. In this talk, I will focus on mobility modeling and resultant applications based on large-scale cross-domain CPS, e.g., cellular networks, payment systems, social networks, and transportation systems (including electric vehicles, taxis, buses, subway, private vehicles, Ubers). I will first show how cross-domain CPS systems can be collaboratively utilized to capture real-time urban mobility by a set of model integration techniques. Then I will show how the captured mobility can be used to design various urban mobile services to close the “loop”, from urban-scale ridesharing to for-hire vehicle dispatching, electric toll collection management, electric-vehicle charging recommendation, and emergency response under mobility anomaly. Finally, I will present some research challenges related to future cross- domain CPS in the context of the smart cities research.

Self-organizing UAV Networks for Providing On-demand Sensing and LTE Connectivity to First Responders

Dr. Eugene Chai, NEC Lab America

Abstract: Autonomous multi-UAV networks will revolutionize the design of systems solutions for civil, entertainment, public services, security and other critical application areas. At NEC Labs, we are particularly interested in the application of such multi-UAV networks to public safety networks. Our goal is simple: how do we design, implement and deploy a reliable and flexible multi-UAV network that can meet the demands of first-responder networks? In this talk, I will introduce SkyLiTE, our multi-UAV network that is designed for public safety applications. SkyLiTE is one of the first efforts at a fully autonomous, untethered multi-UAV network that can be deployed on demand in challenging scenarios to achieve public safety mission objectives. Our SkyLiTE prototype consists of three important components: SkyHAUL, which is a high bandwidth, millimeter wave backhaul network that achieves 1Gbps of bandwidth across the entire multi-UAV network; SkyCORE, a UAV-optimized, lightweight LTE Evolved Packet Core network; and SkyRAN, a full-fledged LTE radio access network. SkyLiTE is deployed either to complement and augment existing terrestrial cellular networks in public safety scenarios, or as a standalone LTE network in areas not covered by fixed infrastructure.

All Your GPS Are Belong To Us: Towards Stealthy Manipulation of Road Navigation Systems

Dr. Yuanchao Shu, Microsoft Research

Abstract: Mobile navigation services are used by billions of users around globe today. While GPS spoofing is a known threat, it is not yet clear if spoofing attacks can truly manipulate road navigation systems. In this work, we explore the feasibility of a stealthy manipulation attack against road navigation systems. The goal is to trigger the fake turn-by-turn navigation to guide the victim to a wrong destination without being noticed. Our key idea is to slightly shift the GPS location so that the fake navigation route matches the shape of the actual roads and trigger physically possible instructions. To demonstrate the feasibility, we perform controlled measurements by implementing a portable GPS spoofer and testing on real cars. The complete attack is validated by extensive trace-driven simulation and real-world driving tests. Deceptive user studies using a driving simulator also show that 95% of the participants follow the navigation to the wrong destination without recognizing the attack.