Du, Lan

Faculty of Information Technology

Room 142, Building 63 - 25 Exhibition Walk

Monash University, Clayton, VIC 3800

Tel: +61 3 9905 9971

Email: given_name.surname@monash.edu

Intro

Dr. Lan Du is a lecturer (equivalent to assistant professor) at Monash University, and affiliated with the machine learning group in Centre of Data Science. He is a teaching and research academic (a core faculty member) in the Faculty of IT, Monash Clayton Campus. He is also a course director of master of data sceince degree at Monash. Before joining Monash, he was a post-doc research fellow afflicated with the language technology group in Macquarie University. He recieved his Ph.D. degree in computer science from the Australian National University, under the supervision of Prof Wray Buntine and Dr. Huidong Jin.

He is interested in statistical modelling and learning from discrete data, such as texts. His research area broadly covers statistical machine leaning, natural language processing, data mining, and social network analysis.

Particularly, his research touches on

  • Deep generative modells
  • (Non-)parametric Bayesian methods
  • Probsblistic matrix factorization
  • Statistical ranking models:
and their applications in the related fields, such as relational learning, recommender systems, etc.

I am looking for self-motivated Ph.D. stduents in statistical machine learning, NLP or data mining, who are funded by (click the hyperlink for more information)

If you are interested in pursuing your Ph.D. with Monash, and if you think you are competitive enough (E.g., the WAM of your master study is above 85, equivalent to H1 honour, and you have gained some research experience) to apply for the scholarship, then
  • Read how to apply, and review your own eligibility
  • If you are eligible, send me your CV, both the bachelor and the master transcripts, and a list of publications if any.

Research highlights

  • "Two-phase linear reconstruction measure-based classification for face recognition" co-authored with Gou et al., is published in Information Science(NEW!)
  • "Sparsity and Geometry Preserving Graph Embedding for Dimensionality Reduction" co-authored with Gou et al., is published in IEEE Access(NEW!)
  • "Dirichlet Belief Networks as Structured Topic Prior" co-authored with H. Zhao, W. Buntine, and M. Zhou, is accepted for publication in NIPS 2018. (NEW!)
  • "Inter and Intra Topic Structure Learning with Word Embeddings” co-authored with He Zhao, Wray Buntine and Mingyuan Zhou, is accepted for publication in ICML 2018.
  • "Leveraging Label Category Relationships in Multi-class Crowdsourcing" co-authored with Yuan Jin, Ye Zhu, and Mark Carman is accepted for publication in PAKDD 2018.
  • "Leveraging external information in topic modelling" co-authored with He Zhao, Wray Buntine and Gang Liu is published in KAIS 2018.
  • “Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences” co-authored with He Zhao, Piyush Rai, and Wray Buntine is published in AISTATS 2018

Grants

Education Background

  • Post-doc Research Fellow, Department of Computing, Macqaurie University, 2012 - 2015, working with Prof. Mark Johnson
  • Ph.D. Computer Science, The Australian National University, Australia, 2008 - 2011
    Supervisors: Prof. Wray Butine, Dr. Huidong Jin
  • B.S. Information Technology with 1st class honours, The Australian National University, Australia, 2007
    Supervisor: Dr. Huidong Jin
  • B.S. Information and Communication Technology, Flinders University, Australia, 2006