Muhammad Asif Naeem

PhD, Postdoc, FHEA

HEC Approved PhD Supervisor

 

Director ORIC

National University of Computer & Emerging Sciences

Professor

Department of Computer Science National University of Computer & Emerging Sciences

Founder

Data Science Research Centre

Director

Data Insight Research Lab  

Postal Address

3 A.K. Brohi Road, H-11/4,
Islamabad, Pakistan.


Profile

Dr Muhammad Asif Naeem is a Professor in Department of Computer Science, National University of Computer & Emerging Sciences. He is Director ORIC, National University of Computer & Emerging Sciences. He is a founder of Data Science Research Centre (DSRC) at Auckland University of Technology. He is a Founder and Director of Data Insight Research Lab at National University of Computer & Emerging Sciences. Before that he has served as a Senior Lecturer in School of Computer and Mathematical Sciences, Auckland University of Technology (AUT) and Associate Professor in NCBA&E. He received his PhD degree in Computer Science from The University of Auckland and has been awarded a best PhD thesis of the year. Before that he has recieved his Master’s degree in Computer Science with distinction. He has about twenty years research, industrial and teaching experience. As an outcome of his research, he published one book and more than 100 peer reviewed journals, conferences and workshops papers in top level venues such as ACM Computing Surveys, TKDE, VLDB, and ICDM. He has received a number of funding grants including international grants like  Callaghan Innovation Fund (CIF) and Strategic Research Innovation Fund (SRIF). Recently, he has received funding of National Research Program for Universities (NRPU) from Higher Education Commission, Pakistan Government. He have been finalised for the Vice Chancellor Emerging Research Award twice. He has received the Faculty Best Teaching and Emerging Researcher Awards. He has been invited as a keynote speaker to a number of conferences in his area. He is an Associate Editor in IEEE Access Journal. He is organising an IEEE workshop IWDS since 2013. He have been reviewing for well-known journals and conferences in his area. His research interests include Generative AI, Data Science, Data Mining and Machine Learning, Active Databases and Data Warehousing.


Qualifications

  • PhD in Computer Science (with best PhD Award) – The University of Auckland
  • MS in Computer Science (with distinction) – BUITMS, Pakistan
  • MSc in Computer Science – BZU, Pakistan
  • BSc – BZU, Pakistan


Fellowships

  • Postdoc – The University of Auckland
  • Fellow of The Higher Education Academy (FHEA), UK


Research Group Founder


Research Interests

My primary research interests are:

  • Generative AI
  • Data Science
  • Data Mining and Machine Learning
  • Big Data Management
  • Active Databases
  • Real-time Data Warehousing


Research Funding

  • National Research Program for Universities (NRPU 2022) (PKR 7,108,500)
  • NESCOM (PKR 2,000,000) (in process of approval).
  • Faculty Research Support (Rs. 500,000) for project A Deep Level Shopping Cart Analysis (2020).
  • 2. Capacity Building Grant for IKMA Lab (PKR 1,375,000) (The project is co-funded with IKMA Lab members)
  • Callaghan Innovation ($100,000) for project Novel Methods for Case Classification from Natural Language Descriptions (2019).
  • Callaghan Innovation (~$100,000) for project Narrative extraction and synthesis to make sense of visual media coming from a camera (2018).
  • SRIF AUT (~$900,000), involve in INTERACT Centre of Technology Excellence Establishment Project (2016)
  • SRIF AUT ($50,000) for project Real-time Streaming Analyticst (2016)
  • Mid-career Research Grant ($25,000) for project Bridging the Gap between Real-time Big Data and Persistent Big Data (2016)
  • DCT Contestable Research Grant ($20,000) for project Smart Shopping with Real-time Shopping Cart Analysis (2016)
  • DCT SRIF Strategic Research Grant ($20,000) for project Forecasting Frequency and Time Synchronization Fluctuations in Electrical Signals (2016)
  • Orion Precision Driven Health Grant ($5,500) for project Post Discharge Application
  • The Digital Mobility Research Group Grant ($3,000) for project A Novel Technique for Processing of Live Mobile Streaming Data with Persistent Big Data (2016)
  • DCT SRIF Strategic Research Grant ($50,000) for project Supporting Real-time Pro- cessing of Gaze Data in a Brick-and-Mortar BaM 2.0 (2015)
  • Summer Scholarship ($5,000) for project Similarity Joins for Semi-Stream Data (2014)


Funding and Awards

  • Finalist for VC Research Excellence Award (2018)
  • Dean's Research Excellence Award (2016)
  • Finalist VC Research Excellence Award (2016)
  • Best Faculty Teaching Award (2015)
  • Mid-career Research Award (2015)
  • Best PhD thesis award, Department of Computer Science, The University of Auckland (2012)
  • In-time PhD completion award, The University of Auckland (2011)
  • Best poster award in CS Department, The University of Auckland (2011)
  • Best poster award, Faculty of Science, The University of Auckland (2009)
  • Distinction award in MS. Computer Science, BUITMS, Pakistan (2006)


Teaching

The key objective of my teaching is to enhance the skills of the students at both academic and professional level. In my opinion the major outcome of teaching is to provide a sound knowledge of the domain area to the students. This is important for their further qualifications and to compete with today’s industry requirements. I always enjoy teaching as my profession and I believe a teacher can play an important role in the society.

A list of undergrad and postgrad level courses which I have taught in recent few years.

2023

  • DS3002 - Data Mining (Undergrad levl)  
  • DS3003 - Data Warehousing & Business Intelligence (Undergrad level)

2022

  • CS4033 - Data Warehousing (Undergrad levl)  
  • DS3003 - Data Warehousing & Business Intelligence (Undergrad level)
  • CS6025 - Advanced Machine Learning (PhD level)
  • AI503 - Advanced Machine Learning (Master level)
  • CS203 - Database Systems (Undergrad level)

2021

  • AI503 - Advanced Machine Learning (Postgrad)  
  • CS203 - Database Systems (Undergrad)

2020

  • CS624 - Special Topics in Very Large Databases (PhD Level)
  • DS506 - Data Stream Warehousing (Postgrad)  
  • CS203 - Database Systems (Undergrad)
  • CS408 - Data Warehousing (Undergrad)

2019

  • DS504 - Data Stream Management for Data Science (Postgrad)
  • CS408 - Data Warehousing (Undergrad)

2018

  • COMP810 - Data Warehousing and Big Data (Postgrad)

2017

  • INFS601- Logical Database Design (Undergrad)
  • COMP810 - Data Warehousing and Big Data (Postgrad)
  • STAT995 - Research Project (Postgrad)

2016

  • INFS601- Logical Database Design (Undergrad)
  • COMP810 - Data Warehousing and Big Data (Postgrad)
  • COMP713 - Distributed and Mobile Systems (Undergrad)

2015

  • INFS601 - Logical Database Design (Undergrad)
  • COMP810 - Data Warehousing and Big Data (Postgrad)
  • COMP610 - Dara Structure and Algorithm (Undergrad)
  • COMP713 - Distributed and Mobile Systems (Undergrad)

2014
  • INFS601- Logical Database Design (Undergrad)
  • ENSE800 - Software Engineering for Service (Postgrad)

2013
  • INFS601- Logical Database Design (Undergrad)
  • ENSE800 - Software Engineering for Service (Postgrad)

2012
  • INFS601- Logical Database Design (Undergrad)
  • INFS500 - Enterprise Information System (Undergrad)


Selected Research Publications

Books

  1. M. Asif Naeem, Web Content Mining from Hidden Web: A Methodical Web mining Approach from Automated Information Extraction from Dynamic Web Pages, LAP LAMBERT Academic Publishing, (2011). (URL)

Journal Publications

  1. Shareef, Farhana, humaira ijaz, Mohammad Shojafar, and M. Asif Naeem. Multi-Class Imbalanced Data Handling with Concept Drift in Fog Computing: A Taxonomy, Review, and Future Directions. ACM Computing Surveys,2024.(IF=23.8)(pdf)
  2. Amy Hai Yan Chan, Braden Te Ao, Christina Baggott, Alana Cavadino, Amber A Eikholt, Matire Harwood, Joanna Hikaka, Dianna Gibbs, Mariana Hudson, Farhaan Mirza, M. Asif Naeem, et al. Digipredict: physiological, behavioural and environmental predictors of asthma attacksa prospective observational study using digital markers and artificial intelligencestudy protocol. BMJ open respiratory research, 11(1), 2024.(IF=3.6)(pdf)
  3. Widana Kankanamge Darsha Jayamini, Farhaan Mirza, M. Asif Naeem, and Amy Hai Yan Chan. Investigating machine learning techniques for predicting risk of asthma exacerbations: A systematic review. Journal of Medical Systems, 48(1):49, 2024. (IF=3.5)(pdf)
  4. Saad Munir and M. Asif Naeem. Bil-fand: leveraging ensemble technique for efficient bilingual fake news detection. International Journal of Machine Learning and Cybernetics, pages 1–23, 2024.(IF=3.1)(pdf)
  5. Musa Dildar Ahmed Cheema, Mohammad Daniyal Shaiq, Farhaan Mirza, Ali Kamal, and M. Asif Naeem. Adapting multilingual vision language transformers for low-resource urdu Optical Character Recognition (OCR). PeerJ Computer Science, 10:e1964, 2024. (IF=3.8)(pdf)
  6. Benjamin Denham, Edmund MK Lai, Roopak Sinha, and M. Asif Naeem. Dynamic quantification with constrained error under unknown general dataset shift. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024. (IF=8.9)(pdf)
  7. UHWA Hewage, R Sinha, and M. Asif Naeem.Privacy-preserving data (stream) mining techniques and their impact on data mining accuracy: a systematic literature review. Artificial Intelligence Review, pages 1-38, 2023. (IF=10.7)(pdf)
  8. Benjamin Denham, Edmund MK Lai, Roopak Sinha, and M. Asif Naeem. Witan: Unsupervised labelling function generation for assisted data programming. Proceedings of the VLDB Endowment, 15(11):2334-2347, 2022. (IF=3.57)(pdf)
  9. Muhammad Usama, M. Asif Naeem, and Farhaan Mirza. Multi-class skin lesions classification using deep features. Sensors, 22(21):8311, 2022. (IF=3.4)(pdf)
  10. Widana Kankanamge Darsha Jayamini, Farhaan Mirza, M. Asif Naeem, and Amy Hai Yan Chan. State of asthma-related hospital admissions in new zealand and predicting length of stay using machine learning. Applied Sciences, 12(19), 2022. (IF=2.5)(pdf)
  11. M. Asif Naeem, Wasiullah Waqar, Farhaan Mirza, and Ali Tahir. Tinylfu-based semi-stream cache join for near-real-time data warehousing. Soft Computing, 2022. (IF=3.1)(pdf)
  12. Rashi Bhalla, Russel Pears, M. Asif Naeem, and Farhaan Mirza. Novel method for optimizing performance in resource constrained distributed data streams. Applied Intelligence, pages 1-19, 2022.(IF=3.4)(pdf)
  13. U.H.W.A. Hewage, Russel Pears, and M. Asif Naeem. Optimizing the Trade-off Between Classification Accuracy and Data Privacy in the Area of Data Stream Mining. International Journal of Artificial Intelligence, 1(1):147-167, 2022. (IF=3.4)(pdf)
  14. Sana Aurangzeb, Haris Anwar, M. Asif Naeem, and Muhammad Aleem. Bigrc-eml: big-data based ransomware classification using ensemble machine learning. Cluster Computing, pages 1-18, 2022. (IF=3.6)(pdf)
  15. Herman Masindano Wandabwa, M. Asif Naeem, Farhaan Mirza, and Russel Pears. Multi-interest semantic changes over time in short-text microblogs. Knowledge-Based Systems, 228:107249, 2021. (IF=7.2)(pdf)
  16. Farrukh Zahid, Ali Tahir, Habib Ullah Khan, and M. Asif Naeem. Wind farms selection using geospatial technologies and energy generation capacity in gwadar. Energy Reports, 7:5857-5870, 2021. (IF=8.2)(pdf)
  17. Muhammad Daud Kamal, Ali Tahir, Muhammad Babar Kamal, and M. Asif Naeem. Future location prediction for emergency vehicles using big data: A case study of healthcare engineering. Journal of Healthcare Engineering, 2020. (IF=3.8)(pdf)
  18. Muhammad Daud Kamal, Ali Tahir, Muhammad Babar Kamal, Faisal Moeen, and M. Asif Naeem. A survey for the ranking of trajectory prediction algorithms on ubiquitous wireless sensors. Sensors, 20(22):6495, 2020. (IF=3.4)(pdf)
  19. Herman Masindano Wandabwa, M. Asif Naeem, Farhaan Mirza, and Russel Pears. Topical affinity in short text microblogs. Information Systems, page 101662, 2020, (Q1 in SCImago, ranked A in CORE, IF=3.167) (pdf)
  20. M. Asif Naeem, Farhaan Mirza, Habib Ullah Khan, David Sundaram, Noreen Jamil, and Gerald Weber. Big data velocity management-from stream to warehouse via high performance memory optimised index join. IEEE Access, 8:195370-195384, 2020, (Q1 in SCImago, IF=3.745) (pdf)
  21. Muhammad Daud Kamal, Ali Tahir, Muhammad Babar Kamal, and M. Asif Naeem Naeem. Future location prediction for emergency vehicles using big data: A case study of healthcare engineering. Journal of Healthcare Engineering, 2020, (IF=1.809) (pdf).
  22. Muhammad Daud Kamal, Ali Tahir, Muhammad Babar Kamal, Faisal Moeen, and M. Asif Naeem. A survey for the ranking of trajectory prediction algorithms on ubiquitous wireless sensors. Sensors, 20(22):6495, 2020, (IF=3.275) (pdf).
  23. M. Asif Naeem, Habib Ullah Khan, Saad Aslam, and Noreen Jamil.  Parallelisation of a cache-based stream-relation join for a near-real-time data warehouse. Electronics, 9(8):1299, 2020, (IF=2.412) (pdf).
  24. Yiwei Feng, M. Asif Naeem, Farhaan Mirza, and Ali Tahir. Reply using past replies - a deep learning-based e-mail client. Electronics, 9(9):1353, 2020, (IF=2.412) (pdf).
  25. Asif Mansoor, Muhammad Waleed Usman, Noreen Jamil, and M. Asif Naeem. Deep learning algorithm for brain-computer interface. Scientific Programming, 2020, (IF=0.963) (pdf).
  26. Benjamin Denham, Russel Pears, and M. Asif Naeem. Enhancing random projection with independent and cumulative additive noise for privacy-preserving data stream mining. Expert Systems with Applications, page 113380, 2020, (Q1 in SCImago,IF=4.577) (pdf).
  27. Benjamin James Denham, Russel Pears, and M. Asif Naeem. HDSM: A distributed data mining approach to classifying vertically distributed data streams. Knowledge-Based Systems, pages 105{114, 2020, (Q1 in SCImago,IF=5.358) (pdf |).
  28. Amira Khattak, Noreen Jamil, M. Asif Naeem, Farhaan Mirza, et al. Data analytics in mental healthcare. Scientific Programming, 2020, (IF=0.963) (pdf).
  29. Mohammed  Alkorbi,  Noreen  Jamil, M.  Asif  Naeem,  Farhaan  Mirza,  et  al.   Evaluating  encryption algorithms for sensitive data using different storage devices. Scientific Programming, 2020, (IF=0.963) (pdf).
  30. M. Asif Naeem, Erum Mehmood, and M. G. Abbas Malik. Optimizing semi-stream cachejoin for near-real-time data warehousing. Journal of Database Management, 2020, (Q2 in SCImago, IF=0.12) (pdf).
  31. Adi Darliansyah, Herman Masindano Wandabwa, M. Asif Naeem, Farhaan Mirza, and Russel Pears. SENTIPEDE: A smart system for sentiment-based personality detection from short texts. Journal of Universal Computer Science, 2019, (Q2 in SCImago,IF=0.77) (pdf).
  32. Huy Vuong Nguyen, M. Asif Naeem, Nuttanan Wichitaksorn, and Russel Pears. A smart system for short-term price prediction using time series models.
    Journal of Computer and Electrical Engineering, 2019, (IF=1.78) (pdf).
  33. M. Asif Naeem. Optimisation and extension of stream-relation joins. The International Journal of Information Technology & Decision Making, 2019, (Q1 in SCImago, IF=1.755) (pdf).
  34. M. Safdar Munir, Imran Sarwar Bajwa, M. Asif Naeem, and Bushra Ramzan. Design and implementation of an IOT system for smart energy consumption and smart irrigation in tunnel farming. Energies, 11(12), 2018, (Q1 in SCImago) (pdf).
  35. M. Asif Naeem, Aftab A Mughal, Christof Lutteroth, and Gerald Weber. A smart email client prototype for effective reuse of past replies. IEEE Access, 6(1):69453–69471, 2018, (Q1 in SCImago, IF=3.55) (pdf).
  36. Wandabwa, Herman and M. Asif Naeem, Farhaan Mirza, and Russel Pears. A metamodel enabled approach for discovery of coherent topics in short text microblogs. IEEE Access, 6(1):65582–65593, 2018, (Q1 in SCImago, IF=3.55) (pdf).
  37. M. Asif Naeem, Christof Lutteroth, and Gerald Weber. A memory-optimal many-to-many semi-stream join. Distributed and Parallel Databases, pages 1–27, 2018, (A in CORE, IF=1.179) (pdf).
  38. Nguyen, Hoa and Mirza, Farhaan and M. Asif Naeem and Mansoor Baig. Falls management framework for supporting an independent lifestyle for older adults a systematic review. Aging Clinical and Experimental Research, pages 1–12, 2018, (Q2 in SCImago) (pdf).
  39. Noreen Jamil, Farhaan Mirza, M. Asif Naeem, and Nilufar Baghaei. A refinement of an iterative orthogonal projection method. Journal of Computational and Applied Mathematics, 341:31–41, 2018, (A in ARC, IF=1.357, Q1 in SCImago) (pdf).
  40. Chamari I. Kithulgoda, Russel Pears, and M. Asif Naeem. The incremental fourier classifier: Leveragingthe discrete fourier transform for classifying high speed data streams. Expert Systems with Applications,97:1-17, 2018, (IF=3.928, Q1 in SCImago) (pdf).
  41. M. Asif Naeem, Gillian Dobbie, Christof Lutteroth, and Gerald Weber. Skewed Distributions in Semi-Stream Joins: How much can Caching help?. Information Systems, 64,63-74, 2017, (ranked A* in CORE, IF=2.82, Q1 in SCImago) (pdf).
  42. Imran Sarwar Bajwa, Fatima Karim, M. Asif Naeem, and Riaz ul Amin. A Semi Supervised Approach for Catchphrase Classification in Legal Text Documents. Journal of Computers,  12(5), pp.451-461, 2017, (IF=0.17, Q3 in SCImago) (pdf).
  43. Perera, Rivindu, Parma Nand, and M. Asif Naeem. Utilizing typed dependency subtree patterns for answer sentence generation in question answering systems. Progress in Artificial Intelligence, Springer, 1-15, 2017, (Q4 in SCImago) (pdf ).
  44. Imran Sarwar Bajwa, N. Mamoona Asghar, and M. Asif Naeem. Automated detection of early tropical cyclones formation in satellite images. Pakistan Journal of Science, 69(4), 2017, (IF=0.23, Q3 inSCImago) (pdf).
  45. Imran Sarwar Bajwa, N. Mamoona Asghar, and M. Asif Naeem. Learning based improved seeded region growing algorithm for brain tumor identification. Proceeding of Pakistan Academy of Science, 54(2),2017, (IF=0.21, Q4 in SCImago) (pdf).
  46. Imran Sarwar Bajwa, Nadeem Sarwar, and M. Asif Naeem. Generating EXPRESS Data Models from SBVR. Proceeding of Pakistan Academy of Sciences: 53(4):381-389, 2016, (IF=0.21, Q4 in SCImago) (pdf).
  47. M. Shahzad Akram, Imran Sarwar Bajwa, and M. Asif Naeem. A supervised approach for semantic annotation of entities in text. Science International, 28(1):237-241, 2016, (IF=1.365 )  (pdf).
  48. Imran Sarwar Bajwa and M. Asif Naeem. A CBR based automated approach for reusing businessprocess models. Science International, 28(1):227-232, 2016, (IF=1.365 ) (pdf).
  49. M. Asif Naeem, Imran Sarwar Bajwa, and Noreen Jmail, A Cached-Based Stream-Relation Join Operator for Semi-Stream Data Processing. International Journal of Data Warehousing and Mining (IJDWM). 12(3), pp. 14-31, 2016, (IF=0.727, Q2 in SCImago)  (pdf).
  50. N. Jamil, J. Müller, M. Asif. Naeem, C. Lutteroth, and G. Weber. Extending linear relaxation for non-square matrices and soft constraints. Journal of Computational and Applied Mathematics, 308, (May 2016), pp. 346-360 (ranked A in ARC, IF=1.08, Q1 in SCImago) (pdf).
  51. M. Asif Naeem, Noreen Jamil. An Efficient Stream-based Join to Process End User Transactions in Real-Time Data Warehousing. Journal of Data and Information Management (JDIM), vol. 12, no. 3, pp. 201-215, 2014, (IF=1.25, Q1in SCImago) (pdf).
  52. M. Asif Naeem, Gillian Dobbie, and Gerald Weber. Efficient Processing of Streaming Updates with Archived Master Data in Near-Real-Time Data Warehousing. Knowledge and Information Systems, Springer-Verlag, 2013, (IF=0.726, Q1 in SCImago) (pdf).
  53. Noreen Jamil, M. Asif Naeem. Speeding Up SOR and Kaczmarz for Constraint-based GUIs with a Warm-Start Strategy. Journal of Multimedia Processing and Technologies (JMPT), vol. 4, no. 3, pp. 179-188, 2013, (pdf).
  54. M. Asif Naeem, Gillian Dobbie, and Gerald Weber. HYBRIDJOIN for Near-real-time Data Warehousing. International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 7, no. 4, pp. 21-42, 2011, (IF=0.727, Q2 in SCImago) (pdf).
  55. Imran Sarwar Bajwa, Ahsan Ali Chaudhri, and M. Asif Naeem. Processing Large Data Sets using a Cluster Computing Framework. Australian Journal of Basic and Applied Sciences (AJBAS), vol. 5, no. 6, pp. 1614-1618, 2011, (IF=0.126, Q4 in SCImago) (pdf).
  56. M. Asif Naeem, and Noreen Jamil. A Web Smart Space Framework for Intelligent Search Engines. International Journal of Emerging Sciences, vol. 1, no. 1, pp. 1-10, 2011, (pdf).

Conference and Workshop Publications

  1. Iqra Ali and M. Asif Naeem. Identifying and profiling user interest over time using social data. In 2022 24th International Multitopic Conference (INMIC), pages 1-6. IEEE, 2022. (pdf | bibTex)
  2. Rida Tahir and M. Asif Naeem. A machine learning based approach to identify user interests from social data. In 2022 24th International Multitopic Conference (INMIC), pages 1-6. IEEE, 2022 (pdf | bibTex)
  3. Muhammad Farjad Ali Raza and M. Asif Naeem. Saraiki language word prediction and spell correction framework. In 2022 24th International Multitopic Conference (INMIC), pages 1-6. IEEE, 2022. (pdf | bibTex)
  4. Benjamin Denham, Edmund MK Lai, Roopak Sinha, and M. Asif Naeem. Witan: Unsupervised labelling function generation for assisted data programming. In Proceedings of 48th International Conference on Very Large Databases (VLDB 2022). VLDB Endowment Inc, 2022, (ranked A* in CORE). (pdf | bibTex)
  5. Benjamin Denham, Edmund Lai, Roopak Sinha, and M. Asif Naeem. Gain-some-lose-some: Reliable quantification under general dataset shift. In 21th IEEE International Conference on Data Mining (ICDM 2021). IEEE, 2021, (ranked A* in CORE). (pdf | bibTex)
  6. Benjamin Denham, Russel Pears, and M. Asif Naeem. Null-labelling: A generic approach for learning in the presence of class noise. In 20th IEEE International Conference on Data Mining (ICDM 2020), (ranked A* in CORE), (pdf |).
  7. Herman Wandabwa, M. Asif Naeem, Farhaan Mirza, Russel Pears, and Andy Nguyen. Multi-interest user profiling in short text microblogs. In15th International Conference on Design Science Research in Information Systems and Technology (DESRIST’20). Springer LNCS, 2020, (ranked A in CORE), (pdf | bibTex).
  8. Herman Wandabwa, M. Asif Naeem, Farhaan Mirza, and Russel Pears. Followback recommendations for sports bettors: A twitter-based approach. In 53rd Hawaii International Conference on System Sciences (HICCS'19). Association for Information Systems IEEE Computer Society Press, 2019, (ranked A in CORE), (pdf | bibTex).
  9. Nawal Chanane, Farhaan Mirza, and M. Asif Naeem. Co-Designing a Medication Notification Application with Multi-Channel Reminders. In 31st Australasian Conference on Information Systems (ACIS'20). Association for Information Systems, 2020, (ranked A in CORE), (pdf | bibTex).
  10. Nawal Chanane, Farhaan Mirza, and M. Asif Naeem. Insights of Medication Adherence Management: A Qualitative Study with Healthcare Professionals and
    Technology Designers. In 30th Australasian Conference on Information Systems (ACIS'19). Association for Information Systems, 2019, (ranked A in CORE), (pdf | bibTex).
  11. Christopher J. Rapson, Boon-Chong Seet, M. Asif Naeem, Jeong Eun Lee, and Reinhard Klette. A performance comparison of deep learning methods for real-time localisation of vehicle lights in video frames. In IEEE Intelligent Transportation Systems Conference (ITSC19), (pdf | bibTex).
  12. Adi Darliansyah, Herman Masindano Wandabwa, M. Asif Naeem, Farhaan Mirza, and Russel Pears. Long-term trends in public sentiment in indian demonetisation policy. In Proceedings of Intelligent Technologies and Applications, pages 65–75, Springer, 2019, (pdf | bibTex).
  13. Shraddha Nayak, Md. Akbar Hossain, Farhaan Mirza, M. Asif Naeem, and Noreen Jamil. E-brace:A secure electronic health record access method in medical emergency. In Proceedings of Intelligent Technologies and Applications, pages 16–27, Springer, 2019, (pdf | bibTex).
  14. M. Asif Naeem, Omer Aziz, and Noreen Jamil. Optimising HYBRIDJOIN to process semi-stream data in near-real-time data warehousing. In CONF-IRM 2019 Proceedings. Association for Information Systems, 2019, (pdf | bibTex).
  15. Herman Wandabwa, M. Asif Naeem, Farhaan Mirza, and Russel Pears. Topical expressivity in short texts. In CONF-IRM 2019 Proceedings. Association for Information Systems, 2019, (pdf | bibTex).
  16. Christopher J Rapson, Boon-Chong Seet, M. Asif Naeem, Jeong Eun Lee, Mahmoud Al-Sarayreh, and Reinhard Klette. Reducing the pain: A novel tool for efficient ground-truth labelling in images. In Proceedings of 33rd IEEE Conference on Image and Vision Computing New Zealand (IVCNZ), (ranked B in CORE)  (pdf | bibTex).
  17. Akbar Hossain, Farhaan Mirza, M. Asif Naeem, and Jairo Gutierrez. A crowd sourced framework for neighbour assisted medical emergency system. In 27th International Conference on Telecommunication Networks and Applications (ITNAC), pages 1-6. IEEE, 2017, (ranked B in CORE), (pdf | bibTex).
  18. Hoa Nguyen, Farhaan Mirza, M. Asif Naeem, and Mirza Mansoor Baig. Detecting Falls Using a Wearable Accelerometer Motion Sensor. Proceedings of 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MOBIQUITOUS 2017), (ranked A in CORE) (pdf | bibTex).
  19. M. Asif Naeem, Kim Tung Nguyen, and Gerald Weber. A multi-way semi-stream join for a nearreal-time data warehouse. Proceedings of 28th Australasian Database Conference. Springer, 2017, (ranked B in CORE) (pdf | bibTex).
  20. Ali Haider Hussein Ghazala, M. Asif Naeem, Farhaan Mirza, and Noreen Jamil. Uncovering Useful Patterns in Shopping Cart Data. Proceedings of IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD 2017), (ranked B in CORE) (pdf | bibTex).
  21. Herman Wandabwa, M. Asif Naeem, and Farhaan Mirza. Document Level Semantic Comprehension of Noisy Text Streams via Convolutional Neural Networks. Proceedings of IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD 2017), (ranked B in CORE) (pdf | bibTex).
  22. Hoa Hong Nguyen, Farhaan Mirza, M. Asif Naeem, and Minh Nguyen. A Review on IoT Healthcare Monitoring Applications and a Vision for Transforming Sensor Data into Real-time Clinical Feedback. Proceedings of IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD 2017), (ranked B in CORE) (pdf | bibTex).
  23. Herman Wandabwa, M. Asif Naeem, and Farhaan Mirza. Aspect of Blame in Tweets: A Deep Recurrent Neural Network Approach. ACM, WWW 2017, (ranked A* in CORE)(pdf | bibTex).
  24. Nawal Chanane, Farhaan Mirza, M. Asif Naeem, and M. Asfahaan Mirza. Acceptance of Technology-Driven Interventions for Improving Medication Adherence. Proceedings of International Conference on Future Network Systems and Security (FNSS), Springer, 2017 (pdf | bibTex).
  25. Erum Mehmood, and M. Asif Naeem. Optimization of cache-based semi-stream joins. Proceedings of IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), IEEE, 2017, (pdf | bibTex).
  26. M. Asif Naeem, Christof Lutteroth, and Gerald Weber. Optimising Queue-based Semi-Stream Joins by Introducing a Queue of Frequent Pages. Proceedings of 27th Australian Database Conference (ADC), Springer-Verlag, 2016, (ranked B in CORE)(pdf | bibTex).
  27. Hao Gao, M. Asif Naeem, Christof Lutteroth, and Gerald Weber. S3J: A Parallel Semi-Stream Similarity Join. Proceedings of 18th International Workshop On Data Warehousing and OLAP (DOLAP), ACM, 2015, (ranked B in CORE) (pdf | bibTex).
  28. M. Asif Naeem, Imran Sarwar Bajwa, and Noreen Jamil. A Cache-based Semi-Stream Join to deal with Unmatched Stream Data. Proceedings of 26th Australian Database Conference (ADC), Springer-Verlag, 2015, (ranked B in CORE) (pdf | bibTex).
  29. M. Asif Naeem, Imran Sarwar Bajwa, and Noreen Jamil. A Cached-based Approach to Enrich Stream Data with Master Data. Proceedings of 10th IEEE International Conference on Digital Information Management (ICDIM'15) 2015.
  30. M. Asif Naeem, Gerald Weber, Christof Lutteroth, and Gillian Dobbie. Optimizing Queue-based Semi-Stream Joins with Indexed Master Data. Proceedings of 16th International Conference on Data Warehousing and Knowledge Discovery (DaWaK), Springer-Verlag, 2014, (ranked B in CORE) (pdf).
  31. M. Asif Naeem. A caching approach to process stream data in data warehouse. Proceedings of 9th IEEE International Conference on Digital Information Management (ICDIM'14), IEEE, 2014, (pdf | bibTex).
  32. Aqsa Mahmood, Kiran Qazi, Imran Sarwar Bajwa, and M. Asif Naeem. Natural language processing based interpretation of skewed graphs. Proceedings of 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, 2014, (pdf | bibTex).
  33. Shabana Ramzan, Imran Sarwar Bajwa, Ikram Ul Haq, and M. Asif Naeem. A model transformation from NL to SBVR. Proceedings of 9th IEEE International Conference on Digital Information Management (ICDIM), IEEE, 2014, (pdf | bibTex).
  34. M. Asif Naeem, Gillian Dobbie, Gerald Weber, and Christof Lutteroth. A Generic Front-Stage for Semi-Stream Processing. Proceedings of ACM 22nd International Conference on Information and Knowledge Management (CIKM), ACM, 2013, (ranked A in CORE) (pdf | bibTex).
  35. M. Asif Naeem, Gillian Dobbie, Gerald Weber, and Christof Lutteroth. SSCJ: A Semi-Stream Cache Join using a Front-Stage Cache Module. Proceedings of 15th International Conference on Data Warehousing and Knowledge Discovery (DaWaK), Springer-Verlag, 2013, (ranked B in CORE) (pdf | bibTex).
  36. M. Asif Naeem. Efficient Processing of Semi-Stream Data. Proceedings of 8th IEEE International Conference on Digital Information Management (ICDIM), IEEE, 2013, (pdf | bibTex).
  37. M. Asif Naeem. Tuned X-HYBRIDJOIN for Near-Real-Time Data Warehousing. Proceedings of 15th Asia-Pacific Web Conference, APWeb (APWeb), Springer-Verlag, 2013, (pdf | bibTex).
  38. M. Asif Naeem. A Robust Join Operator to Process Streaming Data in Real-time Data Warehousing. Proceedings of 8th IEEE International Conference on Digital Information Management (ICDIM), IEEE, 2013, pp. 119-124, (pdf | bibTex).
  39. M Asif Naeem, Gillian Dobbie, and Gerald Weber. A Lightweight Stream based Join with Limited Resource Consumption. Proceedings of 14th International Conference on Data Warehousing and Knowledge Discovery (DaWaK), Springer-Verlag, 2012, (ranked B in CORE) (pdf | bibTex).
  40. M Asif Naeem, Saif Ullah, and Imran Sarwar Bajwa. Interacting with Data Warehouse by Using a Natural Language Interface. Proceedings of 17th International conference on Applications of Natural Language Processing to Information Systems (NLDB),Springer-Verlag, 2012, (pdf | bibTex).
  41. M Asif Naeem, Gillian Dobbie, and Gerald Weber, Imran Sarwar Bajwa. Resource Optimization for Processing of Stream Data in Data Warehouse Environment. Proceedings of International Conference on Advances in Computing, Communications and Informatics (ICACCI), ACM, 2012, (pdf | bibTex).
  42. M Asif Naeem, and Imran Sarwar Bajwa. Generating OLAP Queries From Natural Language Specification. Proceedings of International Conference on Advances in Computing, Communications and Informatics (ICACCI), ACM, 2012, (pdf | bibTex).
  43. M. Asif Naeem, Gillian Dobbie, Gerald Weber, and Imran Sarwar Bajwa. Efficient Usage of Memory Resources in Near-Real-Time Data Warehousing. Proceedings of International Multi-Topic conference, Springer-Verlag, 2012, (pdf | bibTex).
  44. M. Asif Naeem, Gillian Dobbie, Gerald Weber, and Imran Sarwar Bajwa. A Parametric Analysis of Stream based Joins. Proceedings of International Multi-Topic conference, Springer-Verlag, 2012, (pdf | bibTex).
  45. Kashif Hameed, Imran Bajwa and M. Asif Naeem. A Novel Approach for Automatic Generation of UML Class Diagrams from XMI. Proceedings of International Multi-Topic conference, Springer-Verlag, 2012 (pdf | bibTex).
  46. M. Asif Naeem, Gillian Dobbie, and Gerald Weber. Optimised X-HYBRIDJOIN for Near-real-time Data Warehousing. Proceedings of 23rd Australasian Database Conference (ADC), CRPIT, 2012, (ranked B in CORE) (pdf | bibTex).
  47. M. Asif Naeem, Gillian Dobbie, and Gerald Weber. X-HYBRIDJOIN for Near-real-time Data Warehousing. Proceedings of 28th British National Conference on Databases (BNCOD), Springer-Verlag, 2011, (ranked B in CORE) (pdf | bibTex).
  48. Imran Sarwar Bajwa, and M. Asif Naeem. On Specifying Requirements using a Semantically Controlled Representation. Proceedings of 16th International Conference on Applications of Natural Languages to Information Systems, Springer-Verlag, 2011, (pdf | bibTex).
  49. Ashfa Umber, Imran Sarwar Bajwa, and M. Asif Naeem. NL-Based Automated Software Requirements Elicitation and Specification. Proceedings of First International Conference on Advances in Computing and Communications, 2011, (pdf | bibTex).
  50. Imran Sarwar Bajwa, M. Asif Naeem, Ahsan Ali Chaudhri, and Shahzad Ali. A Controlled Natural Language Interface to Class Models. Proceedings of 13th International Conference on Enterprise Information Systems, 2011, (pdf | bibTex).
  51. M. Asif Naeem, Gill Dobbie, and Gerald Weber. R-MESHJOIN for Near-Real Time Data Warehousing. Proceedings of 13th International Workshop On Data Warehousing and OLAP (DOLAP), ACM, 2010, (ranked B in CORE) (pdf | bibTex).
  52. Shafiq Alam, Gillian Dobbie, Patricia Riddle and M. Asif Naeem. Particle Swarm Optimization Based Hierarchical Agglomerative Clustering. Proceedings of IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2010, (ranked B in CORE) (pdf | bibTex).
  53. Shafiq Alam, Gillian Dobbie, Patricia Riddle and M. Asif Naeem. A Swarm Intelligence Based Clustering Approach for Outlier Detection. Proceedings of WCCI2010: IEEE World Congress on Computation Intelligence, 2010, (pdf | bibTex).
  54. M. Asif Naeem, Gill Dobbie, and Gerald Weber. Comparing Global Optimization and Default Settings of Stream-based Joins. Proceedings of Business Intelligence for the Real Time Enterprise (BIRTE, VLDB Workshop), Springer-Verlag, 2009, (pdf | bibTex).
  55. M. Asif Naeem, Gill Dobbie, and Gerald Weber. An Event-Based Near Real-Time Data Integration Architecture. Proceedings of International workshop on Middleware for Web Services, 2008, (pdf | bibTex).
  56. M. Asif Naeem, Imran S. Bajwa and M. Abbas Choudhary. Hidden Web Data Processing for Knowledge Management. Proceedings of IEEE International Conference on Advanced Computer vision and Information Technology, 2007, (bibTex).
  57. Imran Sarwar Bajwa, M. Asif Naeem, Riaz Ul Amin, and Dr. Muhammad Nawaz. Web Information Mining Framework using XML Based Knowledge Representation Engine. Proceedings of 2nd International Conference on Software Engineering, 2006, (pdf | bibTex).
  58. Imran Sarwar Bajwa, M. Asif Naeem, Riaz Ul Amin, and Dr. Abbas Choudhary. Speech Language Processing Interface for Object Oriented Application Design using a Rule-base Framework. Proceedings of 4th International Conference on Computer Applications, 2006, (pdf | bibTex).

Book Chapters

  1. M. Asif Naeem, “Online Processing of End-User Data in Real-Time Data Warehousing”, Improving Knowledge Discovery through the Integration of Data Mining Techniques, 2015. (pdf)
  2. M. Asif Naeem , Gillian Dobbie, and Gerald Weber, “Efficient processing of stream data over persistent data”, Big Data Computing, Taylor and Francis, 2012. (pdf)
  3. M. Asif Naeem , Gillian Dobbie, and Gerald Weber, “ Processing of Stream Data in a Real-Time Data Warehouse”, Big Data Management, Technologies, and Applications, IGI Global, 2012. (pdf)

Technical Reports

  1. M. Asif Naeem , Gillian Dobbie, and Gerald Weber , “HYBRIDJOIN for near-real-time data warehousing”, The University of Auckland, New Zealand, Tech. Rep., 2010. (pdf)
  2. M. Asif Naeem , Gillian Dobbie, and Gerald Weber , “X-HYBRIDJOIN for near-real-time data warehousing”, The University of Auckland, New Zealand, Tech. Rep., 2010. (pdf)

Thesis

  1. Muhammad Asif Naeem, “Efficient Joins to Process Stream Data”, PhD thesis, Department of Computer Science, The University of Auckland. (pdf)


Projects

Ongoing Projects

  1. Digitizing Medical Handwritten Prescriptions

    The primary aim of this research project is to develop a system prototype for converting the healthcare handwritten notes into digital form using AI and Deep Learning techniques. This digital information will be stored into fully normalized/structured format in order to enrich the existing healthcare data with valuable information. The other aim is to analysis healthcare data from various angles (e.g., patients’ health patterns) particularly in COVID context using AI techniques. The project is funded by Higher Education Commission of Pakistan (HEC) under his NRPU grant.

  2. ImageMart

    ImageMart aims to redefine the e-commerce landscape by introducing an innovative image-based product search system, addressing the limitations of traditional text-based search methods. The significance of ImageMart extends beyond improving the E-Marketplace experience. It introduces a paradigm shift by making online shopping more accessible and engaging for a broader audience. By breaking down language barriers, ImageMart envisions a future where users can effortlessly explore a diverse range of products, furniture and its diverse categories. ImageMart represents a transformative step towards a more inclusive and visually-driven era of online shopping. The project is sponsored by our industry partner, Upstart Commerce.

  3. CaptionCraft

    The project aim is to tackle the challenge of developing a specialized image captioning model, tailored to retail products such as furniture and mattresses. Unlike conventional image captioning models, our approach does not require pre-written text or annotations from retailers. Instead, retailers simply provide product images, and our model autonomously generates descriptive captions. The significance of this research lies in its pioneering approach, offering a practical and time-saving solution for retailers. By automating the description generation and form-filling processes, we aim to reduce the time and effort required for maintaining product listings. This, in turn, not only increases operational efficiency for retailers but also contributes to a more informative and seamless online shopping experience for customers. The project is sponsored by our industry partner, Upstart Commerce.

  4. Your AI Assistant (YAIA)

    YAIA is a commanding application utilizing advanced AI technologies. Its purpose is to take in user queries in the form of speech as well as text. YAIA then provides output in the form of text, speech, or some desired action. YAIA excels in user-friendliness, making it accessible and easy to use for a broad audience. Its interface is designed to be intuitive, allowing both tech-savvy individuals and those less familiar with technology to navigate effortlessly. With options for text or voice commands, it ensures accessibility for users regardless of their preferred mode of interaction. The voice-activated features not only enhance accessibility for those with physical limitations but also cater to users seeking hands-free operation, promoting convenience and multitasking.

  5. DiagnosysAI

    DiagnosysAI goes beyond traditional healthcare solutions, offering a diagnostic system with unparalleled benefits for individuals and the community alike. Imagine a healthcare experience where you, as an individual, have the power to input your symptoms in a simple and user-friendly interface. The system, equipped with advanced algorithms, intelligently dissects these symptoms to identify the presence of various diseases. This means personalized recommendations for separate tests, ensuring a precise and efficient diagnostic journey tailored to your unique health profile. The layman gains access to comprehensive disease insights, empowering them with knowledge and facilitating more informed discussions with healthcare professionals. Beyond individual benefits, the system contributes to the community by optimizing healthcare resources. With reduced unnecessary testing and streamlined diagnostics, it paves the way for a more efficient and accessible healthcare system, positively impacting the well-being of the entire community. DiagnosysAI represents an important step towards personalized, community-centric healthcare, revolutionizing the way we approach and experience medical diagnostics.

  6. Bil-FaND: Multi Features based Bi-Lingual Fake News Detection

    The project aim is to detect bilingual fake news using multiple features such as textual, numeric, categorical, and multimedia. To achieve this, we used multiple models e.g. LSTM for numeric and categorical, multilingual BERT for both English and Urdu text, and BLEU for the multimedia. The outcomes of the numerical, textual, category, and caption-generating layers improved the accuracy and reliability of detecting fake news. This study has practical implications for countering misinformation in multilingual contexts and advances natural language processing approaches in the context of fake news identification. The project is sponsored by Government of Pakistan.

Completed Projects

  1. Smart Shopping
  2. Real-time Data Warehousing
  3. Medical Adherence Reminders
  4. Forensic Intelligence
  5. Staged Online Learner (SOL)
  6. Forecasting Fluctuation in Power Supply
  7. Post Discharge Application
  8. Travel Data Analytics 
  9. Parallelising Stream-Relation Join for Near-Real-Time Data Warehouse
  10. Predicting User Personality from Public Perceptions on Social Media (2019)
  11. Extracting Data from Digital and Scanned Charts (2019)
  12. Short-term Price Prediction for Customers (2018)
  13. Reusing Past Replies to Respond to New Emails (2017)
  14. Staged Online Learner (SOL) (2017)
  15. Post Discharge Application (2017)
  16. Multiphase Semi-Stream Joins in Real-time Data Warehousing (2017)
  17. Frequent Item-set Mining using Master Data (2016)
  18. Similarity Joins in Stream Data (2015)
  19. Designing of SkatClub website (2014)


Research Talks

  1. Trends and Challenges in Data Science, Invited talk at NUCES, Islamabad, Pakistan 2020.
  2. Recent Developments in Data Science - in Big Data Perspective, Invited talk at UAEU, Al Ain, Dubai, 2019.
  3. Updates on Data Science Research Group (DSRG) activities, Data Science Research Group Workshop, Auckland, New Zealand, 2018.
  4. Aspect of Blame in Tweets: A Deep Recurrent Neural Network Approach, The 2017 World Wide Web conference, Perth, Australia, 2017.
  5. Updates on Data Science Research Group (DSRG) activities, Data Science Research Group Workshop, Auckland, New Zealand, 2017.
  6. Document Level Semantic Comprehension of Noisy Text Streams via Convolutional Neural Networks, The IEEE 21st International Conference on Computer Supported CooperativeWork in Design (CSCWD), Wellington, New Zealand, 2017
  7. Uncovering Useful Patterns in Shopping Cart Data, The IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD), Wellington, New Zealand, 2017.
  8. A Review on IoT Healthcare Monitoring Applications and a Vision for Transforming Sen- sor Data into Real-time Clinical Feedback, The IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD), Wellington, New Zealand, 2017.
  9. Recent Developments in Data Science, Keynote Speech at The 6th International conference on Innovative Computing Technology (INTECH 2016), Dublin, Ireland, 2016.
  10. Optimising Queue-Based Semi-stream Joins by Introducing a Queue of Frequent Pages, The 27th Australasian Database Conference (ADC), Sydney, Australia, 2016
  11. Research Challenges in Processing of Streaming Data particularly in the context of RDW, Data Science Research Group Workshop, Auckland, New Zealand, 2016.
  12. Caching and Load Shedding in Semi-Stream Joins for Skewed Big Data, eResearch NZ, Queenstown, 2016.
  13. Data Science Research Group (DSRG) Launch, Auckland, New Zealand, 2015.
  14. A Cache-based Semi-Stream Join to deal with Unmatched Stream Data, The 26th Australasian Database Conference, ADC 2015, Melbourne, Australia 2015.
  15. S3J: A Parallel Semi-Stream Similarity Join, 18th ACM International Workshop On Data Warehousing and OLAP, Melbourne, Australia, 2015.
  16. Memory Ecient Join to Process Semi-Stream Data, Centre for Arti cial Intelligence Research (CAIR ), AUT, 2015.
  17. Ecient Processing of Semi-Stream Data, Knowledge Engineering and Discovery Research (KEDRI), AUT, 2015.
  18. Optimizing Queue-based Semi-Stream Joins with Indexed Master Data, 16th International Conference on Data Warehousing and Knowledge Discovery, Munich, Germany, 2014.
  19. A Caching Approach to Process Stream Data in Data Warehouse, The 9th International Conference on Digital Information Management, Bangkok, Thailand, 2014.
  20. Natural Language Processing Based Interpretation of Skewed Graphs, The 3rd International Conference on Advances in Computing, Communications and Informatics, Delhi, India, 2014.
  21. A Generic Front-Stage for Semi-Stream Processing, The 22st ACM International Conference on Information and Knowledge Management (CIKM), San Francisco, CA, USA, 2013.
  22. SSCJ: A Semi-Stream Cache Join using a Front-Stage Cache Module, 15th International Conference on Data Warehousing and Knowledge Discovery (DaWaK), Prague, Czech Republic, 2013.
  23. Ecient Joins to Process Semi-Stream Data, Keynote Speech, The 9th International Conference on Digital Information Management, Islamabad, Pakistan, 2013.
  24. Tuned X-HYBRIDJOIN for Near-Real-Time Data Warehousing, The 15th Asia-Paci c Web Conference (APWeb), Sydney, Australia, 2013.
  25. Optimised X-HYBRIDJOIN for Near-Real-Time Data Warehousing, The 23rd Australasian Database Conference (ADC), Melbourne, Australia, 2012.
  26. A Lightweight Stream-based Join with Limited Resource Consumption, 14th International Conference on Data Warehousing and Knowledge Discovery, Vienna, Austria, 2012.
  27. Stream-based Joins with Limited Resource Consumption, Database Systems and Information Management (DIMA) Group, TU Berlin, 2012.
  28. A Parametric Analysis of Stream Based Joins, 8th International Multi-topic Conference, Pakistan, 2012.
  29. Ecient Usage of Memory Resources in Near-Real-Time Data Warehousing, 8th International Multi-topic Conference, Pakistan, 2012.
  30. X-HYBRIDJOIN for Near-real-time Data Warehousing, 28th British National Conference on Databases (BNCOD), Manchester, 2011.
  31. R-MESHJOIN for Near-Real Time Data Warehousing, 13th International Workshop On Data Warehousing and OLAP (DOLAP), Toronto, Canada, 2010.


Students

Current Students

Past Students

Scholarship Opportunities

A fully funded PhD position is available under the Data Science Research Group (DSRG) at the Auckland University of Technology (AUT). For details please visit the scholarship page.

In addition, there are various scholarships offer by AUT and NZ Government every year for both local and international students. For details, visit AUT scholarships and awards. You can also consider NZ International Doctoral Research Scholarships.


Professional Activities

Project Reviewer

Keynote Speaker

  • Title: Recent Developments in Data Science, in INTECH 2016.
  • Title: Efficient Joins to Process Semi-Stream Data, in ICDIM 2013.

Organising Role

Review Member in Journal and Conferences