About Me🙋♂️
Hello, I am Guobin Chen, a second-year Master student at Brandeis University studying Computer Science. A problem solver with 6 months research experience in Machine Learning and Deep Learning also with 8 months Software Engineer Internship experience at Diameter Health.
Before getting to Brandeis, I obtained my Bachelor’s degree from Soochow University in 2019, where I worked on Nanomaterials for Cancer Drug Delivery Systems advising by Prof. Zhuang Liu.
Open to Work: I am currently looking for a job as a full-time Software Engineer, feel free to contact if you think I am a good fit!
Download my resumé.
- Artificial Intelligence
- Software Development
- Full-Stack Development
- DevOps Development
MS in Computer Science, 12/2022
Brandeis University, US
BS in Biochemistry, 06/2019
Soochow Univeristy, China
Skills
Experience
Collaborated with big-data team
- Utilized Databricks notebook to build up an ETL pipeline to extract raw documents from MongoDB, then transformed documents into layered-based Delta tables, which later stored into S3 bucket on AWS.
- Implemented visualization APIs to visualize processed tables for 40 commercial analytics
- Constructed automatically testing, which will be triggered when a pull request (PR) to github repository, for ETL pipelines, and documented the QA results on TestRails
Collaborated with DevOps team
Gained an in-depth understanding of the CI/CD development pipeline, containerization using Docker, Infrastructure as Code(IaC) using Terraform, Kubernetes and AWS services
Utilized Helm charts to configure Kubernetes resources and implemented Terraform modules to set up VPC and EKS clusters and deployed 35 client services to the clusters on AWS
Built a terraform module to create S3 root bucket for file storage also a cross-account IAM role including policy attachment and configuration to provide Databricks access to AWS services
Created a repeated usage Terraform module for data team team, which could be dropped to infrastructure code to quickly set up a Databricks workspace
Modified Jenkins files to automatically build and test Terraform module code by detecting new code commits from Github repository
- Collaborated with Ph.D students to use Python Matplotlib to visualize QM9 datasets
- Used Pytorch to build and train Graph Neural Network(GNN) model to predict molecular properties
- Visualized 600 dimensional data using t-SNE from sklearn and analyzed internal relationship of results
- Submitted a research paper manuscript to Neural Information Processing Systems (NeurIPS, 2022)
- Utilized chemical systhesis method to synthesize Iron nanoparticles to wrap chemotherapy drugs, improving efficiency of targeted therapy
- Performed biophysical analyses(HPLC/UPLC, regular biophysical characterization) to support team work
- Collected and analyzed experimental data, and collaborated with Ph.D students to draw figures and contributed to two research papers