PhD and MSc Theses
PhD and MSc Theses, since 1988
Student's Name |
Graduation Year |
Degree |
Abstracts |
Research Name |
Shnitzer Dery Tal |
2021 |
PhD |
Abstracts |
Operator-Theoretic Approach for Manifold Learning with Application to Multimodal and Temporal Data Analysis |
Yair Or |
2020 |
PhD |
Abstracts |
Geometric Analysis of Signals and Systems |
Dov David |
2018 |
PhD |
Abstracts |
Multi-Modal Signal Processing on Manifolds |
Aloni Abuhasira Lior |
2021 |
MSc |
Abstracts |
Joint Geometric and Topological Analysis of Hierarchical Datasets |
Rahamim Ohad |
2021 |
MSc |
Abstracts |
Aligning Sets of Temporal Signals with Riemannian Geometry and Koopman Operator |
Wiegner Aviad |
2021 |
MSc |
Abstracts |
Data Driven Koopman Operator Analysis Based on Noisy Augmented Observations |
Silbak Jumana |
2021 |
MSc |
Abstracts |
Geometric Analysis of the Dynamic Connectivity of Biological and Artifical Neural Networks |
Cohen Ido |
2020 |
MSc |
Abstracts |
Unsupervised Anomaly and Target Detection using Manifold Learning with Application to Deep Brain Stimulation (DBS) |
Lin Ya-Wei |
2020 |
MSc |
|
Graph Analysis for Multiplexed Data with Application to Image Mass Cytometry |
Avinu Maya |
2019 |
MSc |
Abstracts |
Analyzing Neuronal Signals using Geometric Methods |
Bloom Noam |
2019 |
MSc |
Abstracts |
Covariance Matrix Estimation Under a Combined Low-Rank and graphical Model Structure |
Katz Ori |
2017 |
MSc |
Abstracts |
Difusion-Based Nonlinear Filtering for Multimodal Data Fusion |
Schwartz Ariel |
2017 |
MSc |
Abstracts |
Intrinsic Isometric Manifold Learning with Application to Localization in Sensor Networks |