Help & Supportcareers@gravityer.com
PhD Candidate
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Delft University of Technology
Data Scientist
June 29, 2026 – Present
models-for-relational-multimodal-data
March 31, 2024 – October 17, 2024
models-for-relational-multimodal-data — GitHub repository
View ProjectT-GNN
June 1, 2023 – July 4, 2023
A re-implementation of T-GNN, a framework for pedestrian trajectory prediction that addresses the performance decrease caused by distribution differences across different domains, by leveraging domain-invariant graph neural networks and adaptive knowledge learning.
View Projectlight-gcn
February 27, 2023 – March 5, 2023
Implementation of Light-GCN model, and application of it on MovieLens Dataset.
View ProjectDC-VAE
April 20, 2022 – June 24, 2022
A re-implementation of DC-VAE, advanced generative model that combines instance-level discriminative loss and set-level adversarial loss for improved image reconstruction and synthesis.
View ProjectCultural Fit Analysis
The candidate's projects primarily focus on academic-style research and re-implementations of advanced models, indicating a strong interest in cutting-edge machine learning. However, the lack of diverse project types (e.g., production systems, business applications) and limited information on team collaboration or real-world problem-solving makes it difficult to fully assess cultural fit for a typical industry Data Scientist role. The experience level of 0 and future-dated role also suggest a very early career stage, which might not align with senior-level expectations for cultural contribution.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's experience level is listed as 0, and the single listed 'Data Scientist' role at Delft University of Technology has a future start date, suggesting it's not current or completed. Project descriptions are brief, limiting insight into collaboration or problem-solving approaches.