Dr. Tingting Mu

 
 

Research:


I am a machine learning researcher. My research is focused on developing advanced mathematical modelling and large-scale optimisation techniques to (1) simulate human intelligence and (2) analyse real-world complex data. For (1), I aim at  constructing effective machine learning models to automate tasks such as matching, recognition, prediction, ranking, inference, characterisation, language and vision understanding, etc. For (2), I aim at developing algorithms to discover latent structure and extract information from large-scale, noisy and unstructured data, e.g., text, image, video, signal, network data, supporting development of text mining, language and vision systems and other related research areas and real-world applications.


Selected Publications:


  1. *X. Evangelopoulos, A. J. Brockmeier,  T.  Mu,  J. Y. Goulermas, Continuation methods for approximate large scale object sequencing, Machine Learning, 108(4)-595-626, 2019.

       This paper is selected to the 7th edition of "World Leading papers" In-Abstract series. [link]

  1. *T. Mu, J. Y. Goulermas and S. Ananiadou, Data visualization with structural control of global cohort and local data neighborhoods, IEEE Trans. on Pattern Analysis and Machine Intelligence, 40(6):1323-1337, 2018. [preprint, link] [demo video: COVA-E1, COVA-P1]

       This paper is selected to the 5th edition of "World Leading papers" In-Abstract series. [link]

  1. *A. J. Brockmeier, T. Mu, S. Ananiadou and J. Y. Goulermas, Quantifying the informativeness of similarity measurements, Journal of Machine Learning Research, 18(76):1-61, 2017. [link]

  2. *T. Mu, J. Y. Goulermas, I. Korkontzelos and S. Ananiadou, Descriptive document clustering via discriminant learning in a co-embedded space of multi-level similarities, Journal of the Association for Information Science and Technology, 67(1):106-133, 2016.  [preprint]

  3. * D. Bollegala, T. Mu, J. Y. Goulermas, Cross-domain sentiment classification using sentiment sensitive embeddings, IEEE Trans. on Knowledge and Data Engineering, 28(2):398-410, 2016. [link]

  4. * J. Y. Goulermas, A. Kostopoulos and T. Mu, A new measure for analyzing and fusing sequences of objects,  IEEE Trans. on Pattern Analysis and Machine Intelligence, 38(5):833-848, 2015. [preprint]

  5. * T. Mu and J. Y. Goulermas, Automatic generation of co-embeddings from relational data with adaptive shaping, IEEE Trans. on Pattern Analysis and Machine Intelligence, 35(10):2340-2356, 2013. [preprint]

  6. * T. Mu, J. Jiang, Y. Wang and J. Y. Goulermas, Adaptive data embedding framework for multi-class classification, IEEE Trans. on Neural Networks and Learning Systems, 23(8):1291-1303, 2012. [preprint]

  7. * T. Mu, J. Y. Goulermas, T. Tsujii and S. Ananiadou, Proximity-based frameworks for generating embeddings from multi-output data, IEEE Trans. on Pattern Analysis and Machine Intelligence, 34(11):2216-2232, 2012. [link]

Lecturer (Assistant Professor)

BEng (USTC), PhD (Liverpool), MIEEE


School of Computer Science

University of Manchester

Kilburn Building, Manchester, UK, M13 9PL

Email: tingting.mu@manchester.ac.uk

Telephone: +44 (0)161 275 6243

Room: 293


Links: REF, Ranking, Ph.D. Application, Ph.D. Projects, Ph.D. Funding


I received my B.Eng. degree from School of the Gifted Young, University of Science and Technology of China in 2004, and Ph.D. degree from Department of Electrical Engineering and Electronics, University of Liverpool in 2008. Before I joined the school in 2016, I was a lecturer in Department of Electrical Engineering and Electronics, University of Liverpool.

 

My Team:


  1. *Alessio Sarullo, Ph.D. student (2016-present),

  B.Sc. and M.Sc. in Computer Science, University of Florence, Italy,

  Working on visual scene understanding.


  1. *Arvid Fahlström Myrman, Ph.D. student (2017-present),

   B.Sc. and MSc. in Computer Science, KTH Royal Institute of Technology, Sweden,

   Working on generative models.


  1. *Rui Qin, Ph.D. student (2017-present),

  B.Eng. in Electronic Engineering, Tsinghua University, China,

  Working on data embedding and visualisation.


  1. *Huw Jones, Ph.D. student (2018-present),

  M.Sc. in Physics and Technology of Nuclear Reactors, University of Birmingham , UK,

  Working on machine learning for AGR reactor data analysis.


  1. *Mirantha Jayathilaka, Ph.D. student (2019-present),

  B.Sc. in Mechatronics Engineering, Asian Institute of Technology, Thailand,

  Working on visual scene understanding with the assist of ontology.


Past Students:


  1. *Dr. Jinmeng Wu, Thesis title “Question Answering Sentence Matching with Neural Networks”.

  (Ph.D. project funded by UoL scholarship for XJTLU graduates)

  1. *Dr. Yu Wu, Thesis title “Embedding Approaches for Relational Data”.

  (Ph.D. project funded by UoL departmental scholarship and Chinese scholarship council)

* Dr. L. Gong, Thesis title “Nonnegative Matrix Analysis for Data Clustering and Compression”.

  1. *Dr. Xinjian Gao, Visiting Ph.D. student, working on deep learning for multimodal image retrieval.

  (Funded by Chinese scholarship council)

  1. *Dr. Yanbin Hao, Visiting Ph.D. student, working on stochastic video hashing for retrieval.

  (Funded by Chinese scholarship council)

  1. *Weijie Fu, Visiting Ph.D. student, working on large-scale graph based learning.

  (Funded by Chinese national 111 project)

“You Know, Feynman used to say he didn’t do physics for the glory or the awards, but just for the fun of it.” –Big bang theory, Season 11, Episode 2