About

Learn more about me

Software Development Engineer

Hi, I'm Jyun-Jhu Syu. I know it's hard to say my name, so I have a more "friendly" name, June.

  • Birthday: 4 March, 1997
  • City: Taipei, Taiwan (ROC)
  • Github: jjjune0304

I am currently studying computer science in Purdue University and have great interest in Machine Learning. I am also an NTU GIEE graduate and focused on Deep Learning research in computer vision during that time. I enjoy building things so I have some experience in Web development and application development on edge devices.

Skills

  • Programming Language: Python, C++, Java
  • Web Development: JavaScript, React, GraphQL, Django
  • Machine Learning: Pytorch, Keras, Tensorflow, Scikit-learn

Resume

Check My Resume

Summary

June Syu

A passionate Software Development Engineer who always embraces new challenges

  • Full Resume
  • 4+ years of experience in software development
  • Hands-on experience in implementing machine learning algorithms to solve classification/clustering problems
  • Research experience in object recognition with deep CNN models
  • Industry experience in software development using Python and C++; developing AI solutions and building model

Education

Master of Computer Science

2023 - 2024

Department of Computer Science, Purdue University

  • Related Courses: Distributed Systems, Introduction to Scientific Visualization

Master of Electrical Engineering

2019 - 2021

Graduate Institute of Electrical Engineering, National Taiwan University

  • Overall GPA: 4.24/4.3
  • Related Courses: Computer Vision, Web Programming, Special Topics on IoT Application Systems, Deep Learning for Human Language Processing

Bachelor of Electrical Engineering

2015 - 2019

Department of Electrical Engineering, National Taiwan University

  • Overall GPA: 4.1/4.3 (Top 15%)
  • Related Courses: Computer Programming, Data Structure, Algorithms, Data Mining

Working Experience

Software R&D Engineer

Oct 2021 - Jan 2023

MediaTek,Inc. , Taipei, Taiwan

  • Developed AI solutions for chip designs, speeding up floorplan generation by 3X
  • Executed data visualization, analysis, and interpretation. Wrote reports and presented results
  • Worked directly with research teams to manage deliverables and expectations during projects
  • Liaised among research teams to facilitate the enhancement of prototype algorithms through communications

Teaching Assistant: Introduction to Computer

Mar 2019 - Jun 2020

National Taiwan University, Taipei, Taiwan

  • Tutorial on artificial intelligence and git
  • Homework assignment and grading on various topics including website building, machine learning, etc.

Teaching Assistant: Linear Algebra

Sep 2019 - Jan 2020

National Taiwan University, Taipei, Taiwan

  • Assisting homework assignment and grading
  • Marking mid-term and final exam papers

Research Intern: Machine Learning

Jul 2019 - Aug 2019

Academia Sinica, Taipei, Taiwan

  • Studied lastest research about machine learning
  • Extensive research on zero-shot image recognition in computer vision

Projects

My Works

  • All
  • CV
  • Web
  • DS
Unsupervised Community-consensus Contrastive Clustering

Dec 2020 - May 2021

Research Project - supervised by Prof. Ming-Syan Chen

Unsupervised Clustering

  • Proposed a one-staged dual contrastive framework for clustering
  • Proposed a contrastive clustering loss to alleviate clustering degeneracy
  • Achieved the state-of-the-arts performance on 6 benchmark datasets, e.g. 95.3% accuracy on ImageNet-10
  • Wrote a research paper to present the results

Computer Vision Deep Learning Unsupervised Learning AI

Attribute Guided Embedding Network for Zero-Shot Learning

Feb 2020 - Sep 2020

Research Project - supervised by Prof. Ming-Syan Chen

Zero-Shot Recognition

  • Proposed a novel model considering both visual attention mechanism and semantic attribute correlations
  • Achieved 73.6% accuracy on benchmarking dataset,i.e.,CUB, which is comparable with the state-of-the-art methods
  • Wrote a research paper to present the results

Computer Vision Deep Learning AI

Memory Booster
(Cognitive Learning)

Sep 2019 - Feb 2020

Team Project (2019 Fall, Cognitive Computing)

Image Generation

  • Enhanced memorability of an given image
  • Leveraged an image encoder and pertrained GAN to transfrom original images
  • Trained the encoder through perceptual loss and cycle loss

Computer Vision Deep Learning AI

See Motion in the dark
(Extremely low-light Video Processing)

Sep 2019 - Feb 2020

Team Project (2019 Fall, Computer Vision)

Video Processing

  • Recovered extremely low-light videos
  • Implemented two models utilizing Conv-LSTM and 3DCNN respectively

Computer Vision Deep Learning AI

Epistemology+

May 2021 - Jun 2021

Team Project (2021 Spring, Web Programming)

Full-Stack Web Development

  • Developed a question and answer website
  • Deployed the website on AWS EC2
  • Installed authorized SSL to secure data

React Node.js GraphQL MongoDB AWS Nginx

Smart Ring

Mar 2021 - Apr 2021

Team Project (2021 Spring, Special Topics on IoT Application Systems )

IoT devices + Full-Stack Web Development

  • Developed a smart ring system on edge devices (RaspberryPi + Arduino)
  • Built a web server which enables users to control the devices remotely through the website
  • Supported multiple function for users, e.g.real-time videostreaming, anomaly detection,and knock notification
  • Enabled device status report and over-the-air update (git)

Django SQLite Apache git

Trajectory Analysis

Mar 2019 - Apr 2019

Team Project (2019 Spring, Machine Learning )

Regression Problem

  • Given the 10,000 features extracted from each diffusion trajectory, the goal is to infer three attributes that is used for trajectory simulation
  • Apply data preprocessing and feature selection condidering large dimensionality of data
  • Build three models utilizing MLP/LightGBM/XGBoost respectively to predict target values

sickit-learn LightGBM XGBoost

Contact

Contact Me

Email Me

jjsyu0304gmail.com

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