Personal profile


Muhammad Aamir Cheema is currently a Lecturer (since Nov-2013) at Monash University, Melbourne. Prior to this, he was a Research Fellow (2011-2013) at School of Computer Science and Engineering at The University of New South Wales (UNSW), Australia. He obtained his Ph.D. degree (2008-2011) under the joint supervision of Prof. Xuemin Lin and Dr. Wei Wang from UNSW, Australia.

His Ph.D. thesis studied efficient processing of proximity-based spatial queries such as reverse k nearest neighbors queries, range queries and k-closest pairs queries. The thesis was awarded 2012 Malcolm Chaikin Prize for Research Excellence in Engineering. His current research interests include spatial databases, uncertain databases, data privacy and data quality.

Before he started his Ph.D., he served as Associate Lecturer at School of Computer Science and Engineering, University of New South Wales, Australia. He taught Database Systems (COMP9311) in 07s2. He received his Masters by Research degree in Computer Science and Engineering from UNSW, Australia (2005-2007) under the supervision of Prof. Xuemin Lin. The research problem addressed in the thesis was related to Nearest Neighbor Queries in Spatio-Temporal Databases. Interested readers can read this thesis (in the form of HTML pages) or as a pdf file. He completed his Bachelor of Electrical Engineering (specialisation in Computers) from UET Lahore, Pakistan, from 2001 to 2005.

Related Links:

Research interests

My current research interests include spatial databases, mobile and pervasive computing, computational geometry and uncertain databases. Currently, I am working on two research projects related to location-based services (LBS).

1. Next-Generation Spatial Keyword Search

The exponentially growing interest in location-based services and the availability of geo-tagged data call for a highly usable, spatial keyword search system that efficiently answers various location-based keyword queries. The aim of the project is to build the next-generation spatial keyword search system that addresses several limitations in the current systems by allowing more meaningful distance measures, modeling uncertainty in data sources and queries, and exploiting rich information from several data sources. The outcome of the project will be new theories, models, methodologies, and a prototype system that is highly usable and efficient, hence enabling more effective and efficient location-based applications.

2. Efficiently Querying Uncertain Spatial Space

Location-based services are becoming increasingly popular due to exponentially increased usage of smartphones and cheap wireless network. This project aims to provide effective and efficient techniques to solve the most representative location-based queries in uncertain spatial space with probabilistic constraints. The constraints can be modified to model various important travelling domains such as road networks, Euclidean space with obstacles and indoor space etc. The project also takes into account the uncertainty present in the real world data. The successful completion of the project will enhance the location-based services used by a broad class of users and applications.

Monash teaching commitment

Dr Aamir Cheema has experience as the Lecturer for the following units in the Faculty of IT:

  • FIT1004 Data management
  • FIT3107 Advanced programming for database applications


  • Databases
  • uncertain data
  • computational geometry
  • spatial databases

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2013 2020

Research Output 2009 2018

Reverse Approximate Nearest Neighbor Queries

Hidayat, A., Yang, S., Cheema, M. A. & Taniar, D. 1 Feb 2018 In : IEEE Transactions on Knowledge and Data Engineering. 30, 2, p. 339-352 14 p., 8081813

Research output: Contribution to journalArticle

Social-Aware Spatial Top-k and Skyline Queries

Sohail, A., Cheema, M. A. & Taniar, D. 2018 In : Computer Journal. p. 1-19 19 p.

Research output: Contribution to journalArticle

Trip Planning Queries in Indoor Venues

Shao, Z., Cheema, M. A. & Taniar, D. 2018 In : Computer Journal. 61, 3, p. 409 426 p.

Research output: Contribution to journalArticle

Continuous monitoring of range spatial keyword query over moving objects

Salgado, C., Cheema, M. A. & Ali, M. E. 11 Aug 2017 (Accepted/In press) In : World Wide Web-Internet and Web Information Systems. 26 p.

Research output: Contribution to journalArticle

Efficient Landmark-Based Candidate Generation for kNN Queries on Road Networks

Abeywickrama, T. N. & Cheema, M. A. 2017 Database Systems for Advanced Applications: 22nd International Conference, DASFAA 2017, Suzhou, China, March 27-30, 2017. Candan, S., Chang, L., Chen , L., Hua , W. & Pedersen , T. B. (eds.). Cham Switzerland: Springer, Vol. 10178 , p. 425-440 16 p. (Lecture Notes in computer Science ; vol. 10178) (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Research output: Chapter in Book/Report/Conference proceedingConference Paper

Activities 2016 2016

  • 1 Committees and working groups