PhD student @ LAMP, EPFL
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Assessing your cultural and operational fit
capybaraclaw
April 14, 2026 – Present
An always-running agent, but is trustworthy and secure.
View Projectawesome-neural-code-intelligence
November 8, 2021 – November 26, 2021
A curated list for awesome machine learning methods for neural code intelligence.
View ProjectGCA
April 9, 2021 – April 25, 2024
[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"
View Projectawesome-self-supervised-learning-for-graphs
September 9, 2020 – October 25, 2022
A curated list for awesome self-supervised learning for graphs.
View ProjectYaDNS
August 23, 2020 – October 5, 2020
Yet Another DNS relay server that can be used as a local DNS over HTTPS (DoH) proxy.
View ProjectGRACE
June 7, 2020 – April 25, 2024
[GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards academic/research-oriented graph machine learning and programming language theory. While demonstrating strong technical depth, the direct alignment with a typical 'Backend Engineer' role in a product-driven company is not immediately clear. The projects are primarily personal, offering limited insight into collaborative work environments or business-oriented problem-solving. The diversity of technologies (Python, Scala, Rust, C++, Lean) suggests adaptability, but the focus areas might require a specific cultural fit that values deep theoretical exploration over immediate product delivery.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's profile primarily showcases technical project contributions without details on team collaboration, problem-solving approaches, or communication styles in a professional setting.