Liu, Tong, Dr

91ֱ��

Dr Tong Liu

School of Computer Science

Lecturer in Pervasive Data Science

Course Director for MSc Advanced Computer Science

T.Liu@sheffield.ac.uk

Regent Court (DCS)

Full contact details

Dr Tong Liu
School of Computer Science
Regent Court (DCS)
211 Portobello
91ֱ��
S1 4DP

Profile

Dr. Tong Liu holds the position of Lecturer in Pervasive Data Science at the Department of Computer Science, University of 91ֱ��, U.K. Previously, he served as a Research Associate at the Sargent Centre for Process Systems Engineering, Imperial College London (2022-2023) and University of 91ֱ�� (2021-2022). He also contributed as an AI researcher with the Shell during his time at Imperial. Before that, he was a visiting researcher at the School of Electronics and Computer Science, University of Southampton (2018-2019). Dr. Liu obtained his B.S. degree in Automation and Ph.D. degree in Control Theory and Engineering in 2016 and 2021, respectively, from Chongqing University, China.

He conducted research at the intersection of machine learning, data science, and decision-making. His primary focus lies in advancing sustainable and lifelong AI methodologies tailored for pervasive data analytics to support intelligent decision-making. His research spans various application domains including industrial automation, precision agriculture, and healthcare informatics. He has published 40+ journal and conference papers, including IEEE TSP, IEEE TKDE, IEEE TCYB, IEEE TNNLS, IEEE TCST, IEEE TIE, AAAI, CIKM.

Research interests: • Lifelong learning, online learning, transfer learning;
• Time series and streaming data analytics;
• Adaptive modeling and monitoring of dynamic processes;
• Safe learning and optimization, learning-based control;
• Applications in precision agriculture, smart healthcare and industrial automation.

Publications

Journal articles

Li Z, Chen B, Liu T, Zuo Z & Liang S (2025) . Engineering Applications of Artificial Intelligence, 144, 110128-110128.
Zuo Z, Zhang H, Li Z, Ma L, Liang S, Liu T & Mercangöz M (2024) . Computers in Industry, 159-160, 104102-104102.
Zuo Z, Zhang H, Ma L, Liu T & Liang S (2024) . IEEE Transactions on Industrial Electronics, 71(6), 6263-6273.
Kong X, He Y, Song Z, Liu T & Ge Z (2024) . IEEE Transactions on Neural Networks and Learning Systems, 1-15.
Yu D, Liu T, Wang K, Li K, Mercangöz M, Zhao J, Lei Y & Zhao R (2024) . Energy and Buildings, 308, 114008-114008.
Li Z, Liu T, Peng X, Ren J & Liang S (2024) . Ocean Engineering, 293, 116694-116694.
He X, Liu T, Zhang Y & Xie R (2024) . IEEE Transactions on Industrial Informatics, 1-10.
Zhao Y, Liu T, Zhu Y-P, Liu Z, Han Q & Ma H (2024) . IEEE Transactions on Industrial Informatics, 1-10.
Liu T, Chen S, Li K, Gan S & Harris CJ (2023) . IEEE Transactions on Cybernetics, 53(12), 7906-7919.
Liu T, Chen S, Yang P, Zhu Y, Mercangoz M & Harris C (2023) . IEEE Transactions on Control Systems Technology.
Liu T, Tian Z, Chen S, Wang K & Harris CJ (2023) . IEEE Transactions on Cybernetics, 53(8), 4908-4922.
Liu T, Chen S, Liang S, Gan S & Harris CJ (2022) . IEEE Transactions on Neural Networks and Learning Systems, 33(5), 1867-1880.
Liu T, Chen S, Liang S, Du D & Harris CJ (2020) . Journal of Process Control, 93, 53-65.
Liu T, Chen S, Liang S & Harris CJ (2020) . IEEE Access, 8, 73278-73292.
Liu T, Chen S, Liang S, Gan S & Harris CJ (2020) . IEEE Transactions on Signal Processing, 68, 2015-2030.
Liu T, Liang S, Xiong Q & Wang K (2020) . Neural Processing Letters, 51(1), 167-191.
Liu T, Liang S, Xiong Q & Wang K (2020) . Neural Computing and Applications, 32(16), 12267-12280.
Liang S, Ye C, Xiong Q, Wang Z & Liu T (2019) . Journal of Microwave Power and Electromagnetic Energy, 53(2), 81-93.
Liu T, Liang S, Xiong Q & Wang K (2018) . IEEE Access, 6, 68839-68849.
Li Z, Liu T, Li S, You L, Liang S & Wang D () . Unmanned Systems, 1-15.
Liu T, Wang X, Yang P, Sheng C & Harris C () Unsupervised transfer aided lifelong regression for learning new tasks without target output. IEEE Transactions on Knowledge and Data Engineering.
Zhou M, Wang X, Liu T, Yang Y & Yang P () Integrating visualized automatic temporal relation graph into multi-task learning for Alzheimer’s disease progression prediction. IEEE Transactions on Knowledge and Data Engineering.

Research group: Pervasive Computing Group