Ph.D Students
 

Itay Niv

Improving out-of-distribution learning in

Graph Neural Networks

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Liat Kaufman Milo

Increasing medical imaging equipment utilization through ML integration in planning and arrival control

(Joint with Prof. Yossi Bukchin)

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Ben Hen

Time series augmentation and forecasting

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Ron Taieb

TBD

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M.Sc Students

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Eadan Schechter​​​

TBD

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Eran Tascesme

Augmentation for classification tasks

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Sama Balum

Fall risk prediction from digital mobility outcomes

(Joint with Prof. Jeffrey Hausdorff)

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Daniel DeMio

Multi-scale regressions for change point detection

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Yaniv Leuchter

Data driven simulation-optimization methods for improving the readiness of the national fire and rescue authority

(Joint with Dr. Mor Kaspi)​​

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Lior Kaspa

Iterative regression ensambles for spatio-temporal forecasting and imputation

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Doron Almog 

Lean and Early: Feature Selection for Fast Human Activity Recognition from Time Series Data​

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Former Students

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Rafael  Brzezinski (PhD 2022)

Non-invasive Thermal Imaging to Detect and Monitor Various Organ Specific Diseases

(Co-supervision with Prof. Jonathan Leor and Prof. Ehud Grossman from the Faculty of Medicine) 

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Maya Keren (M.Sc 2025)

Global Machine Learning Models For Earthquake Back-Azimuth Estimate by Single Stations 

(Joint with Prof. Alon Ziv)

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Mor Abrutzky (M.Sc 2025)

A graph-based sparse filter feature selection method
for multi-class and ordinal data

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Assaf Zadka (M.Sc 2025)

Estimating real-world step length from inertial measurement units using machine learning techniques

(Joint with Prof. Jeffrey Hausdorff)

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Ben Hen (M.Sc 2024)

Spatio-Temporal time series analysis

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Omer Hedvat (M.Sc 2024)

Filter based feature selection using fused metrics for multiclass classification tasks

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Amit Shreiber (M.Sc. 2023)

Multi-scale and multi-directional modeling and analysis of high-dimensional datasets

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Daniel Ovadia (M.Sc. 2023)

Classification of EMG movements with advanced classification techniques

(Joint supervision: Dr. Alex Segal)

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Amit Yadid (M.Sc. 2022)

Sports Injury Prediction using Kernel Based Techniques

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Ido Muller (M.Sc. 2022)

Noninvasive Characterization of Palm Perfusion using Thermal Imaging and Machine Learning Techniques

(co-supervised with Dr. Zehava Blechman)

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Shir Friedman (M.Sc. 2022)

Geometric-Based Feature Selection

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Raphael Shuhendler (M.Sc. 2022)

AcousticRadioz: Dynamic artist-based radio using

Reference-based diffusion maps embeddings

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Itay Niv (M.Sc. 2022)

Seismic Signals Classification Based on Manifold Learning

(co-supervised with Dr. Yuri Bregman)

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Vivian Simon (M.Sc., 2021)

Identifying and Analyzing Gender Gaps in LinkedIn Profiles

(co-supervised with Dr. Hila Chalutz Ben-Gal)

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Alex Knish (M.Sc., 2021)

Thermal Heat Distribution Features for Hand Identification

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Tedy Vaysman (B.Sc, 2024)

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Zachary Deutch, Duke  (B.Sc summer intern, 2025)

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Sivan Almogy, Yale  (B.Sc summer intern, 2023)

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Lior Yaish (B.Sc., 2021)

Fusing Medical Records with Functional Assessment Questioners

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Tali Binder (B.Sc., 2020)

Recommendation and Classification of Accommodations using Data Mining Tools and Data Visualization.

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