Jack Ning

Software Engineer

Technical Skills

• Python (Numpy, Django, Tensorflow & Keras, Pandas)
• C
• SQL (SQL Server)
• R (ggplot2, Shiny)
• Javascript (D3.js)
• HTML
• CSS
• Github
• Microsoft Azure
• Java (Swing, javaFX)
• C++ (openFrameworks)
• MIPS Assembly

Selected Personal Project - Game Night Website

• Skills: Python (Django), Javascript (Canvas, DOM), HTML, CSS
• Purpose: Design a club website for a school club (Game Night), in which I hold a leadership position
• Description:
  • Used the Django Web Framework to create a dynamic website with Python and made use of key features, such as templates
  • Added style and interactivity into the website using a mixture of HTML, CSS, and Javascript Canvas and DOM
• Source: https://gamenightuiuc.com

• Cell:
  • (864) 434 - 1296
• Email:
  • jhning2@illinois.edu

University of Illinois at Urbana-Champaign

• GPA: 4.0 (James Scholar)
• Majors: Statistics and Computer Science, Psychology
• Relevant Coursework:
  • Data Structures
  • Algorithms and Models of Computation
  • Computer Security
  • Systems Programming

August 2018 - May 2021

Current Student

Work Experience

• BP
  • Platform Engineering Intern, Chicago IL
  • Primary Project: OurSpot: Collaborative Workplace Scheduler
  • Skills: SQL Server (Azure), Power Platform (PowerApps, Power Automate), Agile Development (Kanban and Microsoft DevOps)
  • Purpose: Create an application aimed to ease the post-COVID transition back to bp offices through automated workplace scheduling
  • Description:
    • Worked alongside a team of 5 other interns to plan and develop the application using Kanban-style agile development
    • Familiarized myself with Microsoft SQL Server (backend) and PowerApps (frontend)
    • Presented the app in the intern "hackathon" and received the award of "most complete" project - in addition, met with full time employee teams for project handoff and real deployment into bp offices
• Altair Engineering
  • Machine Learning Intern, Troy MI
  • Primary Project: Defect Detection Neural Network
  • Skills: Python (Tensorflow/Keras), Microsoft Azure VM
  • Purpose: Create a convolutional neural network capable of detecting minute defects within material textures
  • Description:
    • Used Tensorflow as a backend for the neural network and programmed in Python using the high level Keras library
    • Leveraged Microsoft Azure virtual machines to provide quick and convenient model training using powerful GPUs
    • Split data into training, validation, and test sets: the final model performed with high accuracy on the test set

Summer 2019

Summer 2020