About
I am a Flatiron Research Fellow at Flatiron Institute studying how learning dynamics shape neural representations — focusing on representational drift, predictive learning, and implicit biases in biological and artificial networks.
Education
- Technion – Israel Institute of Technology
Direct PhD in Computational & Theoretical Neuroscience (2020–2026)
Advisors: Omri Barak, Dori Derdikman - Technion – Israel Institute of Technology
B.Sc. in Electrical Engineering (2016–2020)
Publications
- A Ratzon, O Barak. Prediction horizon shapes representations in predictive learning — arxiv, 2025. Read
- A Ratzon, D Derdikman, O Barak. Representational drift as a result of implicit regularization — eLife, 2024. Read
- D Khatib, A Ratzon, M Sellevoll, O Barak, G Morris, D Derdikman. Experience, not time, determines representational drift in the hippocampus — Neuron, 2023. Read
Teaching
- Teaching Assistant — Quantitative Methods for Medical Students (2021–2024)
- Teaching Assistant — Bioinformatics & Genomics in Medicine (2025)
- Teaching Assistant — Physical Chemistry (2024)
- ISFN Data Analysis Workshop Mentor (2022)
Experience
- Flatiron Institute - Flatiron Research Fellow (2026–Current)
- Qualcomm — Chip Design Verification (2019–2020)
- Qualitest — QA Engineer (2015–2019)
- Kidum — Psychometric Teacher (2015)
Honors & Awards
- Feinsod Award — Neurology & Brain Sciences (2025)
- Gutwirth Excellence Scholarship (2024)
- Faculty Excellence Scholarship (2024)
Skills
- Programming: Python (NumPy, PyTorch, Pandas), C/C++, Matlab, VHDL
- Methods: Probability, stochastic processes, optimization, signal processing
- Tools: Git, Linux, LaTeX
- Languages: Hebrew (native), English (fluent), German (basic)