陳昭儒(Chao-Ju Chen) Github [email protected] Education National Taiwan University Bachelor’s Degree, Electrical Engineering 2012 ~ 2017 Project Highlights Aggregating Files in one ETL, output 60B row to Data Warehouse Input :gzipped files(200GB in total) Task : Loading columns with values parsed from each gzipped file name. Wrote to BigQuery existing table(specific schema) in parallel. Tool: GCP Dataflow(Hosted Serverless Apache Beam) Result : The job took 40min to finish. Machine Type: n1-standard-1(1 vcpu, 3.75GB memory) Autoscaled up to 122 workers at peak. The data
detection, segmentation, and classification AI scenario. Good communication skills with doctors' demands and collaboration with colleagues. Patent Disclosure: Ultrasound detect and notify system. (serial number: I學歷 SepJun 2 National Taiwan University of Science and Technology Masters in Electrical Engineering Thesis "Online Data Stream Analytics for Dynamic Environments Using Self-Regularized Learning Framework", IEEE journal SepJun 2020 Yuan Ze University Bachelor in Electrical Engineering Skills Customer/VC negotiation and customer services DL/ML/AI algorithm, keen problem solving 3D modeling (Blender) Python, Matlab, Tensorflow, Keras Object detection, Classification, [email protected]
Business Development
Deep Learning
PYTHON
Employed
・
Open to opportunities
Full-time / Interested in working remotely
4-6 years
國立台灣科技大學 National Taiwan University of Science and Technology
Games Conducted market research and analysis, and proposed games. Responsible for writing SPEC, leading the development of projects, and collaborating with domestic and international development and design teams to deliver a game within one month. Product Manager / UIUX / Research Writer • MatrixDAO MatrixDAO is a community-driven VC DAO and research DAO. 2022//01 Built 2 DAPPs, which are “MATRIX NFT mint/reveal experience" and "DAO Internal Investment protocol”. MATRIX NFT mint/reveal experience successfully allowed nearly 110 users to complete Mint and Reveal NFT. The DAO internal investment agreement