Jongseo Yoon

Principal Associate Software Engineer

• Develop resuable machine learning components.
• DevOps for CI/CD pipeline.

Senior Associate Software Engineer

• Design and develop backend microservices for enterprise wide machine learning platform.
• Develop automating CI/CD pipeline.

Software Engineer in Radiology

• Developed image pre-processing and visualizer software for MRI data in C++.
• Managed and maintained first release of software developed in the laboratory for Windows, Mac, and Linux to the public.
• Designed and built laboratory’s first HPC clusters, with custom Docker images for easier access.
• Undertook system administration for the laboratory in Linux environment.

Research Assistant II

• Developed software in C++/C# for three of the six robotics workstations designed to accelerate discovery of small molecules via automated synthesis, screening, and identification processes.
• Collaborated with researchers to evaluate the integrated robotics workstations and produce results for scientific paper.

Software Engineer and Image Analysis Associate

• Developed feature in C++ to automatically draw boundaries on region of interest on user’s input and generate data for medical imaging analysis.
• Wrote automated test script to evaluate the company’s website daily and notify administrators if errors or bugs are found.

Research Assistant I

• Contributed to the overall design of the integrated robotics workstations for automated synthesis, screening, and identification processes for small molecules.
• Developed software in Java to calculate and predict outcomes for different chemical structures for small molecules using JChem API.

Software Engineer

• Optimized game client written in C++ and Lua, achieving maximum concurrent users per server from 300 concurrent users to more than 800 concurrent users per server.

Grocery Delivery Notifier

Auto grocery delivery notifier which currently works on Amazon Fresh and WholeFoods. It automatically notifies the user when delivery date is available.

Trashbot - Environmentally Friendly Robot

Developed robot application for mobile robot that roams around specific area and use an attached camera to detect trash on the ground in real-time using a deep learning method called YOLO and notifies the user and its surroundings using voice when trash is found.

Robust Bayesian Neural Network

Investigate Bayesian Neural Network (BNN) against traditional neural networks and show that BNN is more robust against adversarial examples than traditional neural networks.

Path Planning Amidst Moving Obstacles

Implemented Deep Q-network in python, a deep reinforcement learning technique, for path planning on a mobile robot amidst moving obstacles in simulated ROS environment.