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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

Headshot of Dr. Masoud Makrehchi

Masoud Makrehchi
BSc, MSc, PhD (Waterloo), PEng

Associate Professor

Department of Electrical, Computer and Software Engineering

Faculty of Engineering and Applied Science

Contact information

2000 Simcoe Street North
Oshawa, Ontario L1G 0C5
Office: SIRC 3385

905.721.8668 ext. 5387
905.721.3370 (fax)

masoud.makrehchi@ontariotechu.ca

Research topics

  • Natural Language Processing
  • Artificial Intelligence
  • Machine Learning
  • Text and Data Mining
  • Social Computing
  • Mining Social Networks and Complex Systems
  • Network Science
  • Moral AI

Education

  • PhD (Electrical and Computer Engineering), University of Waterloo, Canada, 2007;
  • MSc (Computer Engineering), Shiraz University, Iran, 1994;
  • BSc (Electrical Engineering), Iran University of Science and Technology, Iran, 1991.

Research and expertise

Publications and presentations

  • Selected publications and presentations

    Journal publications

    • M. Ahmadalinezhad, M. Makrehchi. “Edge-centric multi-view network representation for link mining in signed social networks”. Expert Systems with Applications, Vol. 170, pp. 1–11, 2021;
    • M. Ahmadalinezhad, M. Makrehchi. “Basketball Lineup Performance Prediction Using Edge-Centric Multi-View Network Analysis”. Social Network Analysis and Mining, Vol. 10, No. 1, pp. 1–10, 2020;
    • E. Gultepe, M. Kamkarhaghighi, M. Makrehchi, “Document classification using convolutional neural networks with small window sizes and latent semantic analysis”, Web Intelligence Journal, Vol. 18, No. 3, pp. 239–248, 2020;
    • S. Aghababaei, M. Makrehchi. “Interpolative Self-Training Approach for Link Prediction”, Intelligent Data Analysis, vol. 23, no. 6, pp. 1379–1395, 2019;
    • E. Gultepe, M. Makrehchi. “Improving clustering performance using independent component analysis and unsupervised feature learning”, Human-centric Computing and Information Sciences, Vol. 8, No. 25, pp. 1–19, 2018; 
    • A. M. Karimi-Majd, M. Fathian, M. Makrehchi, “Consensus-based methodology for detection communities in multilayered networks”, Physica A, Vol. 494, pp. 547–558, 2018; and
    • S. Aghababaei, M. Makrehchi. “Mining Twitter Data for Crime Trend Prediction”, Intelligent Data Analysis, Vol. 22, No. 1, pp. 117–141, 2018;
    • E. Gultepe, T. Conturo, M. Makrehchi, “Predicting and grouping digitized paintings by style using unsupervised feature learning”, Journal of Cultural Heritage, Vol. 31, pp. 13–23, 2017;
    • M. Kamkarhaghighi, M. Makrehchi. “Content Tree Word Embedding for Document Representation”, Expert Systems With Applications, Vol. 90, pp. 241–249, 2017;
    • S. Aghababaei, M. Makrehchi. “Activity-based Twitter Sampling for Content-based and User-centric Prediction Models”, Human-centric Computing and Information Sciences, Vol. 7, No. 3, pp. 1–20, 2017;
    • M. Makrehchi, M. S. Kamel. “Extracting Domain-Specific Stopwords for Text Classifiers”, Intelligent Data Analysis Journal, Vol. 21, No. 1, pp. 39–62, 2017;
    • M. Makrehchi. “Predicting Political Conflicts from Polarized Social Media ”, Web Intelligence Journal. Vol. 14, no. 2, pp. 85–97, 2016;
    • M. Makrehchi. “Evaluating Feature Ranking Methods in Text Classifiers”, Intelligent Data Analysis Journal. Vol. 19, no. 5, pp. 1151-1170, 2015.

    Book chapters

    • A. Towhidi, M. Kamkarhaghighi, M. Makrehchi, ”Acquisitive Information Extraction Framework for Legal Domain” In ”The LegalTech Book: The Legal Technology Handbook for Investors, Entrepreneurs and FinTech Visionaries”: June 2020;
    • M. Kamkarhaghighi, E. Gultepe, M. Makrehchi, ”Deep Learning for Document Representation” In ”Handbook of Deep Learning Applications”: Springer, 2018, pp. 101– 110;
    • M. Makrehchi, M. S. Kamel, “Aggressive Feature Selection by  Feature Ranking," in Computational Methods of Feature Selection,” Huan Liu and Hiroshi Motoda, Eds.; Chapman and Hall/CRC Press, pp. 313--333, 2007.

    Conferences

    • A. Maraj, M. Martin, M. Makrehchi. “A More Effective Sentence-Wise Text Segmentation Approach using BERT”. Accepted in ICDAR-2021;
    • J. Gillett, S. Rahnamayan, M. Makrehchi, A. Asilian Bidgoli. “A Pareto front-based metric to identify major bitcoin networks influencers”.GECCO ’20: Genetic and Evolutionary Computation Conference, Cancun, Mexico, July 8-12, pp. 1395–1401, 2020;
    • M. Ahmadalinezhad, M. Makrehchi, N. Seward. “Basketball Lineup Performance Prediction Using Network Analysis”. 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 519–524, 2019;
    • E. Gultepe, M. Kamkarhaghighi, M. Makrehchi. “Latent Semantic Analysis Boosted Convolutional Neural Networks for Document Classification”. 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC2018), Taiwan, pp. 93–98, 12-14 November 2018;
    • M. Ahmadalinezhad, M. Makrehchi, “Detecting Agreement and Disagreement in Political Debates”. SBP-BRiMS 2018, Washington D.C., USA, pp. 54–60, 2018;
    • M. Ahmadalinezhad, M. Makrehchi, “Sign Prediction in Sign Social Networks Using Inverse Squared Metric”, SBP-BRiMS 2018, Washington D.C., USA, pp. 220–227, 2018;
    • S. Aghababaei, M. Makrehchi. “Interpolative Self-Training Approach for Sentiment Analysis”. 3rd International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC2016), Durham, NC, USA, pp. 1–6, November 11-13, 2016;
    • S. Aghababaei, I. Chepurna, E. Gultepe, M. Makrehchi. “Activity-Based Sampling of Twitter Users for Temporal Prediction Models”. the 3rd International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC2016), Durham, NC, USA, pp. 1–6, November 11-13, 2016; 
    • M. Makrehchi. “Hierarchical Agglomerative Clustering based on Common Neighbors Similarity”. 2016 IEEE/WIC/ACM International Conference on Web Intelligence, Omaha, NE, USA, pp. 546-551, October 10-16, 2016;
    • S. Aghababaei, M. Makrehchi. “Mining Social Media Content for Crime Prediction”. 2016 IEEE/WIC/ACM International Conference on Web Intelligence, Omaha, NE, USA, pp. 526-531, October 13-16, 2016;
    • I. Chepurna, M. Makrehchi. “We Didn’t Miss You: Interpolating Missing Opinions”. 2016 IEEE/WIC/ACM International Conference on Web Intelligence, Omaha, NE, USA, pp. 552-557, October 13-16, 2016;

    Patents:

    • Prediction Using Event-based Sentiment Analysis, Aug. 2012 (US provisional patent); and
    • Systems, Methods, and Interfaces for Analyzing Conceptually-Related Portions of Text, Apr., 2012 (US patent pending).