Projects per year
Personal profile
Biography
Muhammad Aamir Cheema is currently an ARC Future Fellow and Associate Professor at Monash University. He was a Lecturer at Monash from Nov-2013 to Dec-2015 and Senior Lecturer from 2016-2018. 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 Prof. Wei Wang from UNSW, Australia. He received Masters by Research degree in Computer Science and Engineering from UNSW, Australia (2005-2007) under the supervision of Prof. Xuemin Lin. He completed Bachelor of Electrical Engineering from UET Lahore, Pakistan, from 2001 to 2005.
He is the recipient of 2012 Malcolm Chaikin Prize for Research Excellence in Engineering, 2013 Discovery Early Career Researcher Award, 2014 Dean's Award for Excellence in Research by an Early Career Researcher, 2018 ARC Future Fellowship, 2018 Monash Student Association Teaching Award, and 2019 Victorian Young Tall Poppy Science Award. He has also won two CiSRA best research paper awards (in 2009 and 2010), two "one of the best papers of ICDE" (in 2010 and 2012), and two best paper awards at WISE 2013 and ADC 2010, respectively. He is an Associate Editor of IEEE Transactions on Knowledge and Data Engineering (TKDE). Some of his other service roles include PC co-chair for ADC 2015, ADC 2016, ACM SIGSPATIAL Workshop ISA 2016 & 2018, and International Workshop on Social Computing (IWSC) 2017, proceedings chair for ICDE 2019 and DASFAA 2015, tutorial chair for APWeb 2017 and publicity co-chair for ACM SIGSPATIAl 2017 & 2018.
If you are interested in doing research with me, read "A guide for prospective PhD students" .
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).
Indoor data management
A large part of modern life is lived indoors such as in homes, offices, shopping malls, universities, libraries and airports. However, almost all of the existing location-based services (LBS) have been designed only for outdoor space. This is mainly because the global positioning system (GPS) and other positioning technologies cannot accurately identify the locations in indoor venues. Some recent initiatives have started to cross this technical barrier, promising huge future opportunities for research organisations, government agencies, technology giants, and enterprising start-ups -- to exploit the potential of indoor LBS. Consequently, indoor data management has gained significant research attention in the past few years and the research interest is expected to surge in the upcoming years. This will results in a broad range of indoor applications including emergency services, public services, in-store advertising, shopping, tracking, guided tours, and much more. In this project, we are interested in developing efficient query processing techniques for indoor location data considering textual keywords associated with objects, and data uncertainty. Some additional details are given here .
This project is supported by Australian Research Council (ARC Future Fellowship FT180100140).
Location-based Social Networks
This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in three unique aspects: utilizing the geographical locations of queries and social network data to provide more relevant results; acknowledging and handling inherent uncertainties in the data; and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project include a next-generation social network search system and enhanced international collaborations. The success of this project will support and enhance a wide range of applications such as law enforcement, health, national security, marketing, and advertisement.
Some additional details are given here . This project is supported by Australian Research Council (ARC Discovery Project DP180103411).
Location-based Social Networks
This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in three unique aspects: utilizing the geographical locations of queries and social network data to provide more relevant results; acknowledging and handling inherent uncertainties in the data; and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project include a next-generation social network search system and enhanced international collaborations. The success of this project will support and enhance a wide range of applications such as law enforcement, health, national security, marketing, and advertisement.
Some additional details are given here . This project is supported by Australian Research Council (ARC Discovery Project DP180103411).
Monash teaching commitment
Dr Aamir Cheema has taught the following units in the Faculty of IT:
- FIT2004 Algorithms and Data Structures
- FIT1045 Algorithms and Programming Fundamentals in Python
- FIT1004 Data management
- FIT3107 Advanced programming for database applications
Education/Academic qualification
Computer Science and Engineering, Doctor of Philosophy, University of New South Wales
Award Date: 11 Nov 2011
Computer Science and Engineering, Master of Engineering, University of New South Wales
Award Date: 31 Aug 2007
Electrical Engineering, Bachelor of Science in Electrical Engineering, University of Engineering and Technology Lahore
Award Date: 16 Aug 2005
Research area keywords
- Databases
- uncertain data
- computational geometry
- spatial databases
Network
Projects
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Data Management Foundations for Indoor LBS
Lu, H., Shou, L. & Cheema, A.
1/01/19 → 31/12/21
Project: Research
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A Ubiquitous System for Indoor Location-Based Services
Australian Research Council (ARC)
1/01/19 → 30/06/23
Project: Research
-
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Next-Generation Search on Social Networks
Wang, W., Cheema, A. & Mokbel, M.
1/01/18 → 31/12/20
Project: Research
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Detecting and Monitoring Events using Uncertain Geo-textual Data
Cheema, A. & Zufle, A.
Monash University – Internal University Contribution
1/01/16 → 1/01/18
Project: Research
Research Output
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Continuously monitoring alternative shortest paths on road networks
Li, L., Cheema, M. A., Ali, M. E., Lu, H. & Taniar, D., 2020, Proceedings of the VLDB Endowment. Balazinska, M. & Zhou, X. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 2243-2255 13 p. (Proceedings of the VLDB Endowment; vol. 13, no. 11).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Geo-Social Temporal Top-k Queries in location-based social networks
Sohail, A., Cheema, M. A. & Taniar, D., 2020, Databases Theory and Applications : 31st Australasian Database Conference, ADC 2020 Melbourne, VIC, Australia, February 3–7, 2020 Proceedings. Borovica-Gajic, R., Qi, J. & Wang, W. (eds.). Cham Switzerland : Springer, p. 147-160 14 p. (Lecture Notes in Computer Science; vol. 12008 ).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile -
Indoor mobility semantics annotation using coupled conditional Markov networks
Li, H., Lu, H., Cheema, M. A., Shou, L. & Chen, G., 2020, Proceedings - 2020 IEEE 36th International Conference on Data Engineering, ICDE 2020. Kantarcioglu, M., Gunopulos, D. & Sudarshan, S. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 1441-1452 12 p. (Proceedings - International Conference on Data Engineering; vol. 2020-April).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Online computation of Euclidean Shortest Paths in two dimensions
Hechenberger, R., Stuckey, P. J., Harabor, D., Le Bodic, P. & Cheema, M. A., 1 Jun 2020, Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling. Christopher Beck, J., Buffet, O., Hoffmann, J., Karpas, E. & Sohrabi, S. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 134-142 9 p. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS; vol. 30).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile -
Density-based reverse nearest neighbourhood search in spatial databases
Allheeib, N., Islam, M. S., Taniar, D., Shao, Z. & Cheema, M. A., 2019, (Accepted/In press) In : Journal of Ambient Intelligence and Humanized Computing. 12 p.Research output: Contribution to journal › Article › Research › peer-review
3 Citations (Scopus)
Prizes
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Best Paper of the Year Award - Canon Information Systems Research Australia
Cheema, Aamir (Recipient), 2009
Prize: National/international honour
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Best Paper of the Year Award - Canon Information Systems Research Australia
Cheema, Aamir (Recipient), 2010
Prize: National/international honour
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Best Research Paper Award - Australasian Database Conference
Cheema, Aamir (Recipient), 2010
Prize: National/international honour
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Best Research Paper Award - International Conference on Web Information System Engineering
Cheema, Aamir (Recipient), 2013
Prize: National/international honour
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Dean's Award for Excellence in Research by an Early Career Researcher - Faculty of Information Technology, Monash University
Cheema, Aamir (Recipient), 2014
Prize: National/international honour
Activities
- 1 Committees and working groups
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Member - Faculty Research Committee - Faculty of Information Technology, Monash University
Aamir Cheema (Member)
1 Jan 2016Activity: External Academic Engagement › Committees and working groups