Resume

Fangqi Liu

fangqil2@uci.edu & Mobile Phone: + (1)9492471668

EDUCATION:       

University of California, Irvine                                                                        USA

 PhD Candidate in Networked Systems                                                     Sep.2017-present 

 GPA: 3.846                                        

Jilin University, College of Software                                                              Jilin, China

Master of Software Engineering                                                           Sep.2014 – Jun.2017

CPA: 93.2        Rank: 2/100;

Jilin University, College of Software                                                              Jilin, China

Bachelor of Software Engineering                                                        Sep.2010 - Jun.2014

Overall GPA: 3.3/4.0           Major GPA: 3.51/4.0 

EXPERIENCE: 

Research Intern in SRI International Research Lab:                                           June—Sep. 2021 

·       Experimenting with 5G networks using Free5GC. 

·       Exploring the 5G Authentication and Key Agreement (AKA) process and formulating this process using Maude Language.    

·       Designing the test cases to test the 5G AKA procedures in scenarios with malicious attackers and mal operations. 

PhD Candidate, Distributed Systems Middleware Group (ics.uci.edu/~dsm): UC, Irvine Sep.2017—present 

·       Research on IoT mobile data collection and exchange based on vehicles, public transportation and drones in smart city and emergency scenarios, evaluation using small scale implementation and via network simulators for scalability studies. 

·       Collaboration with external research teams, e.g., NSML in NTHU, Taiwan to explore diverse smart city settings. 

·       Mentoring undergraduate students. 

·       TA for courses: Computer and Communication Networks, Networking Lab. 

TECHNICAL SKILLS:

·       Programming: Python, C/C++ .

·       System building: End-to-end system for drone-based monitoring applications.

·       Linux CLI tools, VMware. 

·       Networking Simulators: OMNET++, SUMO, NS-3, GNS3, Wireshark, The Opportunistic Network Environment (ONE) Simulator. 

·       Data Science: pandas, numpy, Matlab

·       Machine learning techniques: Tensorflow, Reinforcement learning.

·       Image Processing: OpenCV. 

·       Devices: Raspberry Pi with sensors, cameras and drones. 

PROJECTS:

SPARx:Smart Practices and Architectures for Rx fire in California (funded by UCRI 2020 Rewards): In this project, I focus on creating the IoT platform for monitoring Rx fire by combining in-situ and mobile IoT devices (drones) and designing control policies for multi-drone motion planning to improve situational awareness during Rx fire.                                                                                                                                                          Jun. 2020 – present 

SciFire Smart Firefighting Project (funded by NIST): Enabling Infrastructure and In- formation Resilience for Smart Firefighting. In this project, I focus on exploring real- time monitoring of high-rise buildings fire condition by using a group of drones mounted with thermal cameras and sensors.                                                       Nov. 2018-Oct.2019 

National Nature Science Foundation Project in China: The theoretical foundations and technical research on cross-layer combined optimizations of QoS and safety performance in Vehicular Ad Hoc Networks.                                                           Jan. 2016-Jun.2017 

PUBLICATIONS:

•        Fangqi Liu, Janine Baijnath-Rodino, Tung-Chun Chang, Tirtha Banerjee, Nalini Venkatasubramanian, “DOME: Drone-assisted Monitoring of Emergent Events for Wildland Fire Resilience”, in Proceedings of the 14th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2023 (Accepted in shepherding).

•        Tzu-Yi Fan, Fangqi Liu, Jia-Wei Fang, Nalini Venkatasubramanian and Cheng-Hsin Hsu, “Enhancing Situational Awareness with Adaptive Firefighting Drones: Leveraging Diverse Media Types and Classifiers”, ACM MMsys, 2022. 

•        Fangqi Liu, Tzu-Yi Fan, Casey Grant, Cheng-Hsin Hsu, and Nalini Venkatasubramanian, “ DragonFly: Drone-Assisted High-Rise Monitoring for Fire Safety”, in International Symposium on Reliable Distributed Systems (SRDS), 2021.

•        Fangqi Liu, Qiuxi Zhu, Yusuf Sarwar, Nalini Venkatasubramanian and Cheng-Hsin Hsu. “ Cost-Effective Sensor Data Collection from Internet-of-Things Zones Using Existing Transportation Fleets”,  in 2019 IEEE International Conference on Smart Computing (SMARTCOMP), 2019.

•        Jian Wang, Fangqi Liu, Yanheng Liu, Weiwen Deng, Lin Li. “ Distance-Driven Consensus Quantification”, IEEE Transactions on Intelligent Transportation Systems, 2018.05, 19(5): 1471-1484

•        Liu Fangqi, Liu Yanheng, Wang Jian, Deng Weiwen, Xu Shaoqing. “ ADMB: Application-driven multi-hop broadcast for vehicular networks”. International Journal of Communication System. 2017.12, 30(15): e3306

MISCELLANEOUS:

•       Area of Interests: IoT, Mobile and Vehicular Ad Hoc Networks, Flying Ad Hoc Networks, Drones

•       Patent:  Jian Wang, Fangqi Liu, Zhengxiang Wang. A control method, devices and vehicular equipment of transmitting power: China, application number: 201510702461. Open in Feb. 2017.