About
I am a PhD student at Tel Aviv University, supervised by Dr. Ben Nassi . My research focuses on the security and robustness of modern machine learning systems, with a particular emphasis on large language models and AI systems deployed in real-world environments.
I am interested in understanding failure modes of learning-based systems under adversarial, unexpected, or malicious inputs, and in developing practical, model-agnostic defenses.
Research
My research interests include:
- Security and safety of large language models
- Adversarial machine learning and robustness evaluation
- LLM-based systems and agent security
- Model-agnostic defenses and empirical benchmarks
Publications
-
PaniCar: Securing the Perception of Advanced Driving Assistance Systems Against
Emergency Vehicle Lighting
E. Feldman, et al.
arXiv preprint, 2025.
[paper] [media] -
Hate Speech Targets Detection in Parler using BERT
E. Feldman, et al.
arXiv preprint, 2023.
[paper] -
Demo: Identifying Drones Based on Visual Tokens
E. Feldman, et al.
Network and Distributed System Security Symposium (NDSS), AutoSec Workshop, 2022.
[paper]
Background
Prior to my PhD, I completed both my B.Sc. in Software Engineering and my M.Sc. in Information Systems Engineering at Ben-Gurion University of the Negev, as part of the Meitar outstanding students program.
My M.Sc. thesis studied the robustness of machine learning–based perception systems in computer vision, with a focus on autonomous and advanced driver-assistance systems (ADAS). In particular, I analyzed how visual perturbations and environmental artifacts affect object detection and perception reliability.
This work shaped my interest in evaluating and securing learning-based systems under realistic deployment conditions, which directly motivates my current PhD research.
Contact
Feel free to reach me via email: eladfld@gmail.com.