Mahsa Salehi

Dr

Accepting PhD Students

20082021
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Personal profile

Research interests

Mahsa's current research interests are in Data mining and Machine learning, specifically:

  • Multi-dimensional time series analysis
  • Online learning
  • Learning from non-stationary distributions
  • Deep learning
  • Anomaly detection with applications in cybersecurity

Biography

Mahsa is a Lecturer in Machine Learning, Faculty of Information Technology, Monash University. She was a postdoctoral researcher at IBM Research Australia before joining Monash. She received her PhD in Computer Science from the Department of Computing and Information Systems at the University of Melbourne in collaboration with the Machine Learning research group in NICTA. 

Grants:

  • 2019-2021, ARENA Grant, AU$220,000
  • 2018, Sector Growth - Future Industries Grant, AU$50,000
  • 2018, FIT Industry Seed Grant, AU$60,000 (including $30,000 from Emotiv Research)
  • 2018, FIT Multidisciplinary Seed Grant, AU$24,000
  • 2018, Advancing Women’s Research Success Grant, AU$11,000
  • 2012-2014 Microsoft, Microsoft Imagine Cup Grant, US$75,000

Awards:

  • Selected amongst the “Top 200 Most Qualified Young Researchers in Computer Science and Mathematics” by the Scientific Committee of the Heidelberg Laureate Forum Foundation (HLFF) to participate in the 4th Heidelberg Laureate Forum, 2016
  • IBM Manager’s Choice Award, IBM Research Australia, 2016
  • Winner of Australian 2012 Microsoft Imagine Cup Final (our team placed the 1st in Australia and among the top 20 in the World), 2012
  • Melbourne School of Engineering (MSE) Teaching Excellence Award, University of Melbourne, 2014
  • Excellence in Tutoring Award in the Department of Computing and Information Systems, University of Melbourne, 2014
  • Emotiv Founders Scholarship, Emotiv Research, 2014

 

Monash teaching commitment

Mahsa has experience as the Chief Examiner and Lecturer for the following units in the Faculty of IT:

  • FIT1043 Introduction to Data Science 
  • FIT5145 Introduction to Data Sicnece

Research area keywords

  • Time Series Analysis
  • Machine Learning
  • Anomaly Detection
  • Deep Learning
  • Multidimensional/non-linear learning
  • Outlier Detection
  • Spatio-Temporal Data Analysis

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

Projects 2018 2021

Research Output 2008 2018

A survey on anomaly detection in evolving data [with application to forest fire risk prediction]

Salehi, M. & Rashidi, L., Jun 2018, In : SIGKDD Explorations. 20, 1, p. 13-23 11 p.

Research output: Contribution to journalArticleResearch

Open Access
File

Density biased sampling with locality sensitive hashing for outlier detection

Zhang, X., Salehi, M., Leckie, C., Luo, Y., He, Q., Zhou, R. & Kotagiri, R., 2018, Web Information Systems Engineering – WISE 2018 : 19th International Conference, Dubai, United Arab Emirates, November 12–15, 2018 Proceedings, Part II . Hacid, H., Cellary, W., Wang, H., Paik, H-Y. & Zhou, R. (eds.). Cham Switzerland: Springer, p. 269-284 16 p. (Lecture Notes in Computer Science ; vol. 11234 ).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Extremely fast decision tree

Manapragada, C., Webb, G. I. & Salehi, M., 2018, KDD' 2018 - Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining : August 19-23, 2018, London, United Kingdom . Lin, C-J. & Xiong, H. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 1953-1962 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Online clustering for evolving data streams with online anomaly detection

Chenaghlou, M., Moshtaghi, M., Leckie, C. & Salehi, M., 2018, Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018 - Proceedings, Part II. Phung, D., Webb, G. I., Ho, B., Ganji, M. & Rashidi, L. (eds.). Cham Switzerland: Springer, p. 508-521 14 p. (Lecture Notes in Artificial Intelligence; vol. 10938).

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

A large-scale spatio-temporal data analytics system for wildfire risk management

Wang, Z., Vo, H. T., Salehi, M., Rusu, L. I., Reeves, C. & Phan, A., 2017, GeoRich - Fourth International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data: In Conjunction with SIGMOD 2017, May 14th 2017. Bouros, P. & Sarwat, M. (eds.). New York NY USA : Association for Computing Machinery (ACM), p. 19-24 6 p. 4

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Prizes

Australian Microsoft Imagine Cup Final

Mahsa Salehi (Recipient), Hon Weng Chong (Recipient), Andrew Lin (Recipient) & Karthik Rajah (Recipient), 2012

Prize: Prize (including medals and awards)

Activities 2015 2018

  • 4 Contribution to conference
  • 3 Peer review responsibility

Pattern Recognition (Journal)

Mahsa Salehi (Peer reviewer)
2018 → …

Activity: Publication peer-review and editorial work typesPeer review responsibility

SIAM International Conference on Data Mining 2018

Mahsa Salehi (Member of programme committee)
2018

Activity: Participating in or organising an event typesContribution to conference

Pacific-Asia Conference on Knowledge Discovery and Data Mining 2018

Mahsa Salehi (Member of programme committee)
2018

Activity: Participating in or organising an event typesContribution to conference

SIAM International Conference on Data Mining 2017

Mahsa Salehi (Member of programme committee)
2017

Activity: Participating in or organising an event typesContribution to conference

ACM International Conference on Knowledge Discovery and Data Mining 2016

Mahsa Salehi (Member of programme committee)
2016

Activity: Participating in or organising an event typesContribution to conference