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Computer Science & Games
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
TransferNet
April 15, 2021 – June 12, 2023
Pytorch implementation of EMNLP 2021 paper "TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graph "
View ProjectKQAPro_Baselines
February 20, 2020 – July 15, 2024
Pytorch implementation of baseline models of KQA Pro, a large-scale dataset of complex question answering over knowledge base.
View Projectshijx12.github.io
February 11, 2019 – December 10, 2019
shijx12.github.io — GitHub repository
View ProjectXNM-Net
October 5, 2018 – March 17, 2019
Pytorch implementation of "Explainable and Explicit Visual Reasoning over Scene Graphs "
View ProjectDeepChannel
May 23, 2018 – February 14, 2019
The pytorch implementation of paper "DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization"
View ProjectAR-Tree
December 5, 2017 – March 29, 2019
Pytorch implementation of the paper "Learning to Embed Sentences Using Attentive Recursive Trees".
View ProjectDeepSim
September 5, 2017 – September 5, 2017
tensorflow implementation of Generating Images with Perceptual Similarity Metrics based on Deep Networks
View Projectrefolding-planar-polygons
April 21, 2017 – June 5, 2017
refolding-planar-polygons — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects are primarily academic/research-oriented, focusing on implementing published papers. This indicates a strong drive for technical depth and research, which could be a good fit for a research-heavy data science role. However, the lack of team projects or diverse application areas makes it difficult to fully assess cultural fit beyond technical alignment. The 'FathersInCS' project is an outlier and does not contribute to professional cultural fit assessment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are brief and do not provide insight into collaboration, problem-solving approach, or communication style.