Dr. Xiaoli Liu received her PhD degree in mathematics from the University of Helsinki in December 2017. Her doctoral studies were supervised by Professor Mats Gyllenberg. After graduating she worked as a Postdoctoral researcher in the Biomimetics and Intelligent System Group (BISG) at the University of Oulu. She worked with Prof. Pan Hui’s group as a visiting scholar in 2019 and Polar Electro Oy with collaboration of University of Oulu in 2018. In November 2019, she joined the research group lead by Prof. Sasu Tarkoma in the Department of Computer Science at University of Helsinki as a Postdoctoral researcher. Dr. Xiaoli Liu currently works as a Postdoctoral fellow within Helsinki Institute for Information Technology (HIIT).
Dr. Xiaoli Liu’s research interests focus on distributed systems and edge intelligence, and her participated projects are related to IoT, federated learning, opportunistic learning, differential privacy, 5G and Augmented reality (AR). Dr. Xiaoli Liu has published 19 peer-reviewed journal and conference articles. She publishes papers in top venues, such as IEEE Internet Computing Magazine, IEEE Transactions on Intelligent Transportation Systems, and ACM Transactions on Sensor Networks.
Her recent research in 2021 contains providing solutions for scalable air quality monitoring by combing edge intelligence, 5G, and sensor calibration techniques [1]; utilizing context-aware AR together with 5G edge for path planning [2]; extending the previous Bayesian federated learning research work to have a model cluster instead of assuming a global model; opportunistic learning for air quality monitoring; and proving the feasibility of putting independent Component Analysis (ICA) under the distributed setting. Meanwhile, she also works for two survey papers: outdoor low-cost sensor and sensor calibration for air quality monitoring [3] and COVID-19 in Public Transportation: Transmission Risk, Mitigation and Prevention.
She is actively involved in funding application, workshop organizing, and teaching in 2021, for example, the participated project application “NSF joint call with the collaboration of Yale University” submitted in April 2021 has got the positive decision. She is the course advisor for bachelor thesis in the spring semester and co-teaching Advanced Course in Deep Learning (5cr) for in the autumn semester and she will be the main responsible teacher from 2022. Meanwhile, she serves as a board member of the Junior Faculty Club in University of Helsinki to provides support for PhD students and Postdoctoral researchers
Sample of publications in 2021:
[1] X. Su, X. Liu, N.H. Motlagh, J. Cao, P. Su, P. Pellikka, Y. Liu et al. “Intelligent and Scalable Air Quality Monitoring with 5G Edge.” IEEE Internet Computing 25, no. 2 (2021): 35-44.
[2] J. Cao, X. Liu, Xiang Su, Sasu Tarkoma, Pan Hui, “Context-Aware Augmented Reality with 5G Edge”, IEEE Global Communications Conference, Madrid, Spain, 7 -11 December 2021.
[3] C. Francesco, J. Mineraud, E. Lagerspetz, S. Varjonen, X. Liu, K. Puolamäki, P. Nurmi, and S. Tarkoma. “Low-cost outdoor air quality monitoring and sensor calibration: A survey and critical analysis.” ACM Transactions on Sensor Networks (TOSN) 17, no. 2 (2021): 1-44.
[4] Z. S. Liu, G. Xiong, Z. B. Wei, Y. Zhang, M. Zheng, X. Liu, S. Tarkoma, M. Huang, Y. S. Lv, C. H. Wu. “Trip Purposes Mining From Mobile Signaling Data.” IEEE Transactions on Intelligent Transportation Systems (2021).