Luyi MO


Ph.D. Candidate

Rm 417, Chow Yei Ching Building
Department of Computer Science
The University of Hong Kong

Email: lymo at cs dot hku dot hk

[Curriculum Vitae]

I am currently a Ph.D. candidate in Department of Computer Science at HKU, supervised by Dr. Reynold Cheng and Prof. David Cheung. I received B.S. degree (Information and Computing Science) from Department of Mathematics, Zhejiang University in June 2011.

I was also the coach of HKU ACM-ICPC Team (ACM International Collegiate Programming Contest) from 2012 to 2013.

Research Interests

My main research area is database systems. I'm currently working on quality management of uncertain database and crowdsourcing systems. Current research projects I'm involved are described as follows.

  • Cleaning Probabilistic Data with Quality Guarantee: Data ambiguity exists in many applications, which can be handled by probabilistic databaes. In some cases, this ambiguity can be reduced, or cleaned. In this project, we propose an entropy-based quality metric to quantify the uncertainty of probabilistic query results, and develop efficient quality computation algorithms which can support range, max, and top-k queries. For the cleaning procedure, we model 3 aspects that may affect the cleaning result. We use the proposed quality metric to guide the cleaning process, and develop effective and efficient cleaning algorithms to improve data quality.
  • Improve Data Quality in Crowdsourcing Environments: We are working on the problem that improves the quality of resources' description in social network systems based on incentives. We propose a quality metric based on stability and a few incentive allocation strategies. We are also studying how to improve the quality of information obtained from crowdsourcing systems.


  1. L. Mo , R. Cheng, X. Li, D. Cheung, and X. Yang. Cleaning Uncertain Data for Top-k Queries. Intl. Conf. on Data Engineering (IEEE ICDE 2013), Brisbane, Apr 2013. (Acceptance rate: 92/460 = 20%) [Paper] [Talk] [Technical Report]
  2. X. Yang, R. Cheng, L. Mo, B. Kao, and D. Cheung. On Incentive-based Tagging. Intl. Conf. on Data Engineering (IEEE ICDE 2013), Brisbane, Apr 2013. (Acceptance rate: 92/460 = 20%) [Paper]
  3. L. Mo , R. Cheng, X. Yang, C. Ren, B. Kao, S. Lei, E. Lo, and D. Cheung. Optimizing Plurality for Human Intelligence Tasks. Intl. Conf. on Information and Knowledge Management (ACM CIKM 2013), San Francisco, USA, Oct 2013. (Acceptance rate: 143/848 = 17%) [Paper] [Talk] [Technical Report]
  4. C. Ren, L. Mo , B. Kao, R. Cheng, D. Cheung. CLUDE: An Efficient Algorithm for LU Decomposition Over a Sequence of Evolving Graphs. Intl. Conf. on Extending Database Technology (EDBT 2014), Athens, Greece, Mar 2014. (Acceptance rate: 20%) [Paper]
  5. S. Lei, X. Yang, L. Mo, S. Maniu, R. Cheng. iTag: Incentive-base Tagging. (Demo) Intl. Conf. on Data Engineering (IEEE ICDE 2014), Chicago, USA, Apr 2014.
  6. Y. Zheng, R. Cheng, S. Maniu, L. Mo. On Optimality of Jury Selection in Crowdsourcing. Intl. Conf. on Extending Database Technology (EDBT 2015).
  7. S. Lei, S. Maniu, L. Mo, R. Cheng, P. Senellart. Online Influence Maximization. ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining (ACM SIGKDD 2015).

Selected Awards

  • Google Hong Kong Anita Borg Scholarship, twice in 2013 and 2014. 4 awardees in Hong Kong each year.
  • HK & China Gas Company Limited Postgraduate Scholarship 2012-2013.
  • IEEE ICDE Student Travel Award, 2013.
  • Hong Kong PhD Fellowship, awarded by the Hong Kong RGC, 2011.
  • World Champion for 35th Annual World Finals of the ACM International Collegiate Programming Contest (ACM-ICPC), Orlando, 2011. The first and the only one female world champion in ACM-ICPC history. [Photo Tour]
  • Best Team Award (out of 17,000 teams) for China Undergraduate Mathematical Contest in Modeling, 2010.
  • China National Scholarship, awarded by the Ministry of Education in China, 2009.


Last update: 18 Nov, 2012