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Software Engineer , Machine Learning | Computer Vision | Robotics
I'm a software engineer with professional expertise in machine learning / deep learning, computer vision ,robotics and hyperspectral imaging also have research experience in deep learning, computer vision and NLP. Please feel free to contact me or connect :) My specialties: • Programming: C\C++, Python, Java, Rust • Tools: Shell Script, Git, CMake, JIRA • Frameworks : Tensorflow, Pytorch, Keras, Caffe, ROS, OpenCV • System : Linux, Windows, Raspberry Pi • Computer Vision & Machine Learning: Object detection, Visual question answering, Classification, Semantic Segmentation, Instances segmentation, OCR, depth estimation, stereo calibration, Sentiment Analysis, Recommendation System, hyperspectral imaging GitHub: github.com/bill2239
Arizona State University
Master of Science, Computer Engineering (Computer System)
January 1, 2017 – Present
National Central University
Bachelor of Science, Physics
January 1, 2013 – Present
CIS Corporation
Computer Vision/AI Expert
November 1, 2024 – Present
Tokyo, Japan
KPIT
Senior Technical Lead
December 1, 2023 – November 1, 2024
Tokyo, Japan
EII, Inc.
AI Engineer
March 1, 2023 – October 1, 2023
Tokyo, Japan
Rapyuta Robotics
Robotics Perception Engineer
April 1, 2022 – February 1, 2023
Greater Tokyo Area
Seedland Group
Staff Research Engineer
August 1, 2021 – January 1, 2022
New York City Metropolitan Area
Graftek Imaging
Senior Computer Vision Engineer
September 1, 2017 – August 1, 2021
Austin, Texas
Dcard
Data Scientist Intern
June 1, 2016 – August 1, 2016
Arizona State University
Graduate Research Assistant
January 1, 2016 – January 1, 2017
Academia Sinica, Taiwan
Research Intern
July 1, 2012 – January 1, 2013
Taipei City, Taiwan
SmoozFrames
July 1, 2025 – Present
A deep learning based frame interpolation video player/ editor donationware with interactive GUI to segment video portion as you want, export into an animation file like GIF and Webp, a video or frames
Automatic Word Algebra Problem Solver
April 1, 2016 – Present
•Transformed data into XML format using Stanford parser to extract nature language property of word problem •Represented word problem as lexicalized features for template assignment using Python •Solved QP problem to learn the model for solving using SVM and reach 81% accuracy
Identifying Characters in Google Street View
April 1, 2016 – Present
•Preprocessed and augmented data of Google Street View images using scikit-image in Python •Implemented CNN to recognize characters using deep learning framework Caffe •Developed text recognition module by using MSER to recognize text regions in nature picture using opencv in Python
RESTful Service of Gradebook
April 1, 2016 – Present
•Designed and implemented RESTful web service for professor to post grades and comment for tasks using Java •Processed and passed XML to store information and message with Java jersey framework
ASU Event Reminder
December 1, 2015 – Present
• Scraped data from ASU event website and transformed it into JSON format using Python • Developed location-aware Android app incorporated Google API to remind user based on travel time to event location using Java in Android Studio Environment
Community Analysis of Physician Referral Network
December 1, 2015 – Present
• Manipulated and cleaned physician referral data eliminated outliers in the data • Performed community detection by implementing unsupervised greedy algorithm in Python utilizing the library Numpy, Scipy and Networkx • Conducted statistical analysis to get characteristic of community and investigate the relation between features and communities using R
Social Network Analysis on Intagram
October 1, 2015 – Present
• Implemented web crawler based on REST API for Instagram to extract user information on Instagram • Manipulated data and cleaned data to anonymize the user information in the site using Python • Analyzed the network using Networkx in Pyhton to understand the social network in quantitative approach
Simulation of queuing delay in router
December 1, 2014 – Present
• Simulated queuing delay in the router using poison process to model packet arrival using C • Investigated the relation between the number of users and performance of router
Simulation of Computational Physics Model
June 1, 2013 – Present
• Implemented Monte Carlo Method in C language to model thermal phenomenon in magnetic material • Performed data analysis over simulated data and extract physical meaning through pattern in the data using C
Metallic Clusters Melting with Time Scale Clustering
May 1, 2013 – Present
• Prepossessed data generated from molecular simulation in time-series format using Matlab • Implemented algorithms to reveal the pattern of dynamics in the metallic cluters • Investigated the pattern to tune the size of sliding windows in the algorithm
Video Analytics for Avalanches Pattern Recognition
December 1, 2012 – Present
• Designed and assemble high speed camera, motors, and rotating drum to record the motion of granular particles for avalanche experiments • Conducted video analytics to analyze motions of granular particles by using correlation filter to compute velocity field (Matlab) • Analyzed a large amount of time series data via statistical analysis to find the patterns in the data to recognize events of avalanches • Presented and Received the great poster award in a conference
Fundamentals of Quantum Computing
The Linux Foundation
June 24, 2026 – Present
Reinforcement Learning
Udemy
June 24, 2026 – Present
Introduction to Embedded Machine Learning
Edge Impulse
June 24, 2026 – Present
Japanese Language Proficiency Test N2
The Japan Foundation
June 24, 2026 – Present
Certified Vision Professional - Basic
A3 - Association for Advancing Automation
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong inclination towards data-driven problem-solving and analytical tasks, which aligns well with a Data Analyst role. The breadth of projects, from computer vision to social network analysis and scientific simulations, indicates a versatile and curious individual. The experience as a Data Scientist Intern further strengthens the alignment. The candidate has worked in diverse environments (e.g., international, multinational), suggesting adaptability to different cultural settings.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a capacity for independent research and development. The diversity of projects suggests adaptability and a willingness to tackle varied technical challenges. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.