Research

Research Overview

In recent years, we have been observing a revolution in the use of data science, machine-learning algorithms, and optimization methods in “softer” areas such as human resources (HR), human behavior, mental illness, and learning disabilities, as well as in more conventional areas such as manufacturing and logistics systems. Despite these advances, there are still substantial gaps in our understanding of how users can implement machine-learning algorithms and optimization methods to address challenges in these domains. A user’s willingness to utilize the outputs of machine-learning algorithms is likely to be predicated upon his or her ability to understand the model’s behavior, rather than perceiving it as a black box. My research is geared towards addressing the above challenges, and in particular, towards understanding how to enhance the usability as well the explainability of these algorithms’ outputs while solving problems from these domains. My two main (and complementary) methods of research are: (i) the implementation and adaptation of existing interpretable machine-learning algorithms, i.e., models in which the results can provide practical insights into problems from various domains, and (ii) the development of new optimization methods and interpretable machine-learning algorithms that outperform other known algorithms in these domains.

Research Interests:

  • Machine learning and business analytics
  • Machine learning for medical diagnosis
  • Human resource analytics
  • Applications of information theory to industrial and service systems
  • Modeling and solution methods for optimal control problems in stochastic environment

Funding

I have served as either PI (principal investigator) or co-PI on 13 research grants obtained from various sources including the Prime Minister's Office, the Office of the Chief Scientist of the Ministry of Trade and Commerce, the Israel Defense Forces (IDF), the National Institute for Testing and Evaluation, IDF - The Human Engineering Division, the Ministry of Science and Technology, Intuit Inc., etc.

On-going funded projects:

  • 2021-2022, National Institute for Testing & Evaluation, Evaluating the effectiveness of accommodations given to engineering and science students, taking into account student profiles, learning disabilities and actual time used: innovative decision-tree based algorithms, Principal Investigator.
  • 2022-2023, Inuit Inc, Holistic approach to combine individual level prediction and aggregated constraints, Principal Investigator.
  • 2022-2024, Joint Sheba-Bar-Ilan Research Grant, Exploring tumor-bacteria interplay in breast cancer by spatial transcriptomics, Co-PI. This is a joint project with Shahar Alon.
  • 2022-2025, Ministry of Science and Technology, Asthma severity levels monitoring based on EEG signals using novel ordinal classification algorithms, Principal Investigator. This is a joint project with Anat Ratnovsky and Sara Naftali.
  • 2022-2025, Ministry of Science and Technology, A system for improving the readiness of the National Fire and Rescue Authority based on data fusion for risk prediction and classification of fire and identification of influencing factors, Co-PI. This is a joint project with Neta Rabin.