I’m a Ph.D. student under the supervision of Prof. Eran Yahav. My research focuses on source code representations for machine learning models. We research machine learning approaches for solving code-related tasks such as code completion, edit completion, predicting method names, and automatic documentation generation. My main interest is how to represent the code in such tasks. I’m also interested in methods for processing graphs using deep neural networks.
How Attentive are Graph Attention Networks?
- Shaked Brody, Uri Alon, Eran Yahav
- Appeared in ICLR’2022
- GATv2 implementations:
A Structural Model for Contextual Code Changes
code2seq: Generating Sequences from Structured Representations of Code
- Uri Alon, Shaked Brody, Omer Levy, Eran Yahav
- Appeared in ICLR’2019
- Online demo: https://code2seq.org
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Loading Deep Learning Network Models for Processing Medical Images
- Program Committee: Deep Learning for Code ICLR’2022 workshop, MSR’2021 Mining Challange
- 2023 – Excellent Faculty TA
- 2022 – Department Excellence Scholarship
- 2019 – Dean’s Excellence Scholarship