Qiaodan Ju

I’m Qiaodan Ju

We work in the darkness to serve the light.

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About Me

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Hello,

I am Qiaodan Ju, Software Engineer from Jiangsu, China. I am a growing noooooob, temporarily.

Name: Qiaodan Ju

Birthday: 26 Feburary, 1999

Location: Chengdu, China

Email: shimmerjordan@foxmail.com

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My skills

Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics

Python

95%

Java

90%

HTML & CSS

60%

C++

70%

Github statistic:

Qiaodan Ju

Education

Work Experience

02/2023 - Present

Huawei Technologies Co., Ltd

Wireless Communications Dept

Software Development Engineer

Education

02/2023 - Present

Huawei Technologies Co., Ltd

Wireless Communications Dept

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09/2021 - 01/2023

Master of Science in Data Science and Machine Learning

GPA: 4.33 / 5.00 (93.3 / 100.0),

09/2017 - 06/2021

Bachelor of Engineering in Software Engineering, Southeastern University, China

GPA: 3.9199 / 5.0000 (89.199 / 100.000),

CET-6: 610

IELTS: 7.0

GRE: 331 + 3.5

Internship Experience

05/2022 - 11/2022

Transformer-Bumblebee Algorithm Intern

Megvii-inc, Beijing, China

  • Working on a 3D lane detection model to build an easy-to-deploy network that works efficiently end-to-end. Used ResNeXt18 as the backbone and connected the backbone and the neck of the dcn_fpn structure via an SA module to enhance global feature awareness.
  • Participating in the improvement of the prediction head, the clustering strategy of key-points in post-processing is designed to draw lane lines under RV segmentally with different joint_points as bridging points. The lane lines are merged by certain strategies including IoU, offset, etc. to give the model robustness in the diverging lane lines and thus replace the unfriendly RIM solution deployed in condlanenet.
  • Write data pre-processing and GT annotation pipeline for curvelane, CULane, etc. Distributed training based on MMCV framework, as well as test scripts and asynchronous upload of bad cases to s3 for visual analysis and checkpoints via a mounted ws2 multi-thread. Versioning.
  • 11/2021 - 03/2022

    Part-time Research Assistance

    NUS Next++ Lab

  • Involved in the research of the Image Caption task network model, mainly in the backbone refactoring optimization, the algorithm design of the caption evaluation and the redesign of an adaptive and efficient optimizer.
  • In the Backbone module, Inception-V3 was improved with reference to DLA34's tree aggregation idea to provide more global awareness and maintain a healthy number of participants. The evaluation method of the original Greedy Search is replaced by the Beam Search strategy, which generates a more biased prediction result in favour of selecting the best.
  • An optimiser between Lazy Adam and Adam is redesigned and combined with AdamW for regular term tuning. The problem of Lazy Adam not updating first- and second-order momentum at zero gradient is addressed by making it applicable to the case of sparse variable indexing during RNN training, and for unsampled embedding plus penalty coefficients is also taken into account. After passing through the neck of dcn_fpn it is fed into the RNN head with RA module, using the GRU cell as a carrier. In a preliminary demo using the VizWiz dataset, its BLEU_1 reaches 50 and BLEU_n can basically reach around 30.
  • 11/2020 – 02/2021

    Full Stack Developer

    Neusoft Technology Co., China

    Please refer to the link for details of the project open source code: https://github.com/shimmerjordan/sz-education

  • The system is designed to improve the efficiency of online teaching and learning and includes an online learning sub-system and a back-end CMS, which contains modules related to online courses, online examinations, grade analysis and grade management, intelligent paper assembly, tenant management and other related functions. The system uses an improved genetic algorithm to improve usability and scientific performance.
  • The system framework is based on SpringCloud and integrates monitoring components such as Consul, Spring Boot Admin and Zipkin. Spring Cloud OAuth2 and JWT are used to support multi-tenant SSO login and authentication, and RabbitMQ is used to maintain the message queue. In addition, BCryptPasswordEncoder method is used for irreversible password encryption. Combined with Redis for partial request caching and filtering, the system was tested to maintain a concurrency of over 10kQPS when deployed locally in a package.
  • The system was packaged and deployed on a local Ubuntu 20.04 test machine and deployed to the public network via intranet penetration.
  • 05/2020 – 08/2020

    Full Stack Developer

    Chinasoft International, China

    For details, please refer to the link. https://github.com/shimmerjordan/Lexian-Malls

  • Participated in the development of Lexian-Mall supermarket fresh food wholesale system based on SpringCloud, including client, applet and CMS backend management system. Mainly responsible for the SSO module for users under the login authentication microservice, the real name authentication function module and the shopping cart management module under the order microservice, and the development of some functions under the order module.
  • Developed the client and CMS system web front-end and applet pages based on Uni-app and Vue respectively, and used SpringBoot to develop each functional module. We used Redis to solve the problem of unshared sessions and implemented a simple message queue to speed up the response to requests and improve concurrency performance. In addition, Zuul was used to intercept and filter illegal requests from requesting users to intercept malicious attempts at cryptography.
  • The application was packaged and deployed to a cloud server after JVM tuning and passed a 10kQPS stress test in a test environment.
  • Projects

    10/2021 – 12/2021

    User Debt Behaviour Forecasting - kaggle competition

    For details, please refer to the link. https://github.com/shimmerjordan/loan-pred-customer-behavior
  • This (unbalanced) dataset is studied from supervised as well as unsupervised learning directions, focusing on feature engineering, modelling prediction and dimensionality reduction, and user clustering respectively. The main objective is to build highly accurate predictive models of user lending behaviour.
  • The XGClassifier was used to train the optimal ratio of undersampling and oversampling to better address the data imbalance. Feature selection was performed by PCA and Variational Auto-encoder, and a pipeline was established for GB, RF and Xgboost respectively, and the Xgb model with a training set of 0.97 f1-score and a test set of 0.89 f1-score was obtained by model selection. In addition, k-means was used to classify the users for model interpretation.
  • 09/2019 – 12/2019

    Automated Palletizing System

    Description: Realized machine’s automatic identification to assess the box’s height and size, placed the messy boxes in object region orderly using mechanical arms.

  • The coding of the movement logic of the robot arm of the automatic palletizing system allows the arm to send requests and responses to the corresponding algorithm module after it has obtained the commands to achieve automatic palletizing and loading.
  • 10/2018 - 11/2019

    Image Identification Based Upon Progressive Machine Learning

    Description: Applied progressive identification techniques to the image classification problems of bags and suitcases, increased the efficiency of image classification in case of ensuring accuracy.

    Wu Jianxing, Zeng Dexin, Ju Qiaodan, Chang Zixuan and Yu Hai*, “Progressive Image Recognition Method and Its Application in Security Inspection Machines”, Current Chinese Computer Science 2021; 1(1) . https://doi.org/10.2174/2665997201999201208210819

  • Participate in the design of classification networks and the construction of datasets.
  • The initial dataset is obtained through a crawler script on an e-commerce platform, and then combined with manual GT annotation through data cleaning and augmentation and other pipelines. A progressive strategy is used to segment individual images to simulate the form of progressive input.
  • The VGG16 is optimised with reference to the BN proposed by InceptionV2 and the ResNet residual linking, and the CategoricalCrossentropy is improved by combining the focal loss proposed by RetinaNet, for different proportions of segmented data from the same image source, the small proportion of misclassified cut data will have a larger penalty factor, as a way to control the convergence efficiency of the model.
  • Ultimately, with only 50% of the images input, it is able to obtain a 50% efficiency gain at a cost of less than 1.5% precision loss (precision == 90.35%).
  • 10/2017 - 12/2018

    Study on Electricity Generating Performance by Burning RDF

    Description: Developed research on RDF’s composition proportion under optimal burning performance.

  • Analysis of the current status of research and directions for improvement in the performance of RDF fuels for power generation.
  • The coarse material of rdf is made into combustible materials with different mixture ratios by controlled variable method.
  • Based on experimental statistics, the combustion characteristics of rdf blends are analysed in terms of weight loss temperature and ash analysis.
  • AWARDS & HONORS

    09/2017-06/2021

    Undergraduate Level

  • Second-class Scholarship for Excellent Students, NEU, China. 06/2021
  • Successful Participant, 2020 Certificate Authority Cup InternationalMATHEMATICAL CONTEST IN MODELING. 05/2021
  • Outstanding Student Pioneer at NEU, China. 04/2021
  • Second-class Scholarship for Excellent Students, NEU, China. 09/2020
  • Outstanding Student at NEU, China. 11/2019
  • Third-class Scholarship for Excellent Students, NEU, China. 10/2019
  • Third Prize at university level, The 5th “Internet +” Entrepreneurship and Innovation Competition, China. 06/2019
  • Successful Participant, Mathematical Contest in Modeling, the US. 05/2019
  • Outstanding Minster, Academy of Science and Technology, NEU, China . 04/2019
  • First-class YU Songling Scholarship, NEU, China. 11/2018
  • Third Prize at provincial level, National Mathematical Contest in Modeling for College Students, China. 10/2018
  • Second-class Scholarship for Excellent Students, NEU, China. 09/2018
  • Second Prize, Mathematical Contest for College Students, NEU, China. 07/2018
  • Seventh place in the men's single-shake jump rope category of the 57th Tohoku University Games
  • Second Prize, “PUYI” National English Composition Contest for College Students, China. 12/2017
  • Projects

    • All Projects
    • Software Engineering
    • Machine Learning
    • Design
    • Other

    Social Works

  • Planned for the “Festival for Popularization of Science,” took charge of the debugging work of the online broadcasting program.
  • Negotiated with parts of sponsors to plan the activities, assisted in identifying the participants.
  • Academy of Science and Technology, NEU, China

    09/2019-10/2019
  • Carried on investigation on the economic development of different places in China.
  • Investigated on the poor areas in different regions, analyzed the effectiveness and expectations of targeted poverty alleviation scheme.
  • Led the team to be awarded as the “NEU Excellent Summer Practice Team”.
  • Urban and Rural Development & Targeted Poverty Alleviation Practice Team

    07/2018-08/2018

    I enjoy working with him and learn so much. You guys make the process fun and interesting. Good luck!

    customer-name

    Ying Wang

    Association Professor, NEU, China.

    Partial posts

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    Phone
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    Email address
    shimmerjordan@foxmail.com
    Location
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