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Qwen 🚀
Backend Engineer
June 26, 2026 – Present
MCL
June 9, 2021 – June 11, 2022
Code and data for paper https://arxiv.org/pdf/2106.05517.pdf (CVPR 2022)
View ProjectAttentionZSL
November 5, 2019 – November 5, 2019
Codes for Paper "Attribute Attention for Semantic Disambiguation in Zero-Shot Learning"
View Projectstroke-controllable-fast-style-transfer
March 25, 2018 – April 7, 2021
Code and data for paper: https://arxiv.org/abs/1802.07101
View Projectdeep-photo-styletransfer-tf
August 6, 2017 – May 9, 2022
Tensorflow (Python API) implementation of Deep Photo Style Transfer
View ProjectMissing-Pixel-Inpainting
May 23, 2017 – June 2, 2017
Implemented color and grayscale missing pixel inpainting paper
View Projectcaf-visual-train
April 25, 2016 – April 25, 2016
A shell script to visualize caffe training
View ProjectAgeAndGenderEstimation
February 16, 2016 – February 16, 2016
age and gender estimation using caffe network
View Projectcaf_face_detection
December 11, 2015 – October 4, 2016
Implement Yahoo Paper: Multi-view Face Detection Using Deep Convolutional Neural Networks
View ProjectCNN
September 18, 2015 – October 28, 2015
Convolutional Neural Network using Eigen and C++
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on academic research in computer vision and machine learning, primarily using Python and C++. While this demonstrates strong technical depth in a specific domain, there is limited evidence of broader backend engineering experience (e.g., distributed systems, API design, database management, cloud platforms) that would typically align with a general 'Backend Engineer' role in an industry setting. The current role at 'Qwen 🚀' is listed as 'Backend Engineer' but lacks details on responsibilities or technologies, making it difficult to assess direct alignment. The projects suggest a strong research-oriented mindset rather than a product-development focus.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's projects are primarily research-oriented, indicating a potential for independent problem-solving but lacking evidence of collaborative or communication skills in a team setting.