M.Masoud Rahimi

Geospatial data scientist
Email: masoud.rahimi@unimelb.edu.au

Address

Resume and network

Bio

Masoud is a geosptial data scientist at AURIN. He is also a final-year PhD candidate at the Faculty of Engineering and Information Technology, The University of Melbourne, Australia. He holds a master degree in Geospatial Information Systems (GIS) from the University of Tehran and a bachelor of science in Geomatics Engineering from Iran University of Science and Technology.

Working within diverse industrial and academic environments, he has gained a wealth of technical and analytical expertise as well as teaching and academic skills. This has consolidated his understanding of a range of data science methods and techniques, including Natural Language Processing (e.g. Word2vec, Elmo and BERT) and deep learning approaches (e.g. RNNs), as well as various programming languages (such as Java, C#, Python, R and Matlab), big data handling and their corresponding data validation methods. Moreover, during his master studies, he employed cloud computing and in particular Hadoop technologies to enhance required spatial analyses in a transit context.

In addition to research, he also has multiple teaching and leadership experiences. For instance, he has been a tutor for GEOM90008: Foundations of Spatial Information during the last three years. It is a postgraduate-level introductory subject to Geospatial Information Systems (GIS) and Geographic Information Science, both practically and theoretically. He earned rank 14th among 2519 applicants in the national master entrance exam, Iran. He spent more than three years working at Tadbir Foroud Rah (TFR) consulting company as a geospatial software developer. I have enough proficiency in .NET Framework, C#, Python and R programming along with solid experience with handling spatial databases.

He grew up in Tehran, Iran and moved to Melbourne, Australia in 2018.

His professional resume can be found here.

News

Oct 2021   Paper: Pose-Aware Monocular Localization of Occluded Pedestrians In 3D Scene Space is accepted at ISPRS Open Journal of Photogrammetry and Remote Sensing [paper]
May 2020   Paper: Service quality monitoring in confined spaces through mining Twitter data is accepted at JOSIS [paper]
Feb 2020   Awarded grant: We have awarded a travel grant for presenting our current research at Research@Locate2020
June 2019   Paper: The Effectiveness of Sentiment Analysis for Detecting Fine-grained Service Quality has been accepted to Geocomputation 2019 [paper]

Teaching Activities

Mar 2021   Tutoring: Elements of Data Processing (COMP20008) at the Newman College (The University of Melbourne).
May 2020   Guest Lecturing on Toponym resolution in Spatial Information Programming (GEOM90042) at the University of Melbourne.
July 2019   Tutoring: Satellite Positioning Systems (GEOM90033) at the University of Melbourne.
Feb 2019   Tutoring: Foundations of Spatial Information (GEOM90008) at the University of Melbourne.

Past Students

2020   Miguel Rosas Raya: Prediction of Transit-Induced Gentrification with Machine Learning in Melbourne (MCS).
2019   Andre Andre Analysing People’s Perception towards Melbourne’s White Night Festival through Sentiment Analysis on Twitter Dataset (MIT (Computing)).
2019   Xiaoxue Wang: Predicting Urban Space Types Based on Sentiment Analysis - A Spatio-temporal Research in Melbourne (MIT (Spatial)).

Selected Publications

Oct 2021   Paper: Pose-Aware Monocular Localization of Occluded Pedestrians In 3D Scene Space is accepted at ISPRS Open Journal of Photogrammetry and Remote Sensing [paper]
May 2020   Paper: Service quality monitoring in confined spaces through mining Twitter data is accepted at JOSIS [paper]
June 2019   Paper: The Effectiveness of Sentiment Analysis for Detecting Fine-grained Service Quality has been accepted to Geocomputation 2019 [paper]
Sep 2017   Paper: Towards a Cloud Based Smart Traffic Management Framework has been accepted to ISPRS Joint Conferences of GI Research, SMPR and EOEC 2017 [paper]