The School of Computer Science at the University of Windsor is pleased to present…

Technical Workshop Presentation by  Ali Abbasi Tadi PhD Candidate

Advanced Topics in Data Clustering

Presenter:  – PhD Candidate Ali Abbasi Tadi

Date: Wednesday, February  8^th, 2023

Time: 3:00 pm – 4:00 pm

Location: 4^th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)

1. Two-part attendance mandatory (sign-in sheet, QR Code)
2. Arrive 5-10 minutes prior to the event starting – LATECOMERS WILL NOT BE ADMITTED.
3. Be respectful of the decision of the advisor/host of event if you are not given admittance, there are several more events in future.
4. If you cannot attend, please be sure to cancel your attendance prior.

Abstract: 

Clustering is a way of grouping data points into different clusters consisting of similar data points. The objects with possible similarities remain in a group that has less or no similarities with another group. In this workshop, we explore advanced topics in data clustering for high dimensions. We will define the curse of dimensionality and dimensionality reduction methods like t-SNE, PCA, and Isomap as well as their implementations. We will explore the consensus matrix and how to adjust the best clustering parameters.

Workshop Outline:

DBSCAN, PCA, Isomap, t-SNE, Consensus matrix, Consensus learning

Prerequisites:

Basic Statistics concepts, matrix algebra, eigen vectors, basic python programming

Biography: 

Ali is pursuing his Ph.D. in computer science at the University of Windsor. His main research interest is security/privacy in machine learning. He has publications on private clustering in top conferences and peer-reviewed journals. He has received various scholarships from the University of Windsor and got 5th place in the iDash security 2022 competition. He has been invited as a speaker at the Advanced Computing Hub at the University of Windsor. He serves as the program committee and editorial board of some conferences and journals. He is currently developing a secure framework for parallel clustering sensitive genomic data.