Production Line Project Manager/ CS STUDENT

Dianjun Wang

626-***-**** ********@******.***

EDUCATION

Georgia Institute of Technology, Atlanta, GA

Master of Science in Computer Engineering

Jilin University, China

Bachelor of Engineering in Material Processing

Jan 2021-Current

Graduated Jul 2006

SKILLS

Programming & Database Python, Java, C++

Data Analytics & Visualization

Project Management

R (tidyverse, dplyr, ggplot2), Python (pandas, NumPy, SciPy) 10 + years of experience auto industry (engineering and production line construction. Familiar with robotics, automotive safety)

PROFESSIONAL EXPERIENCE

Project Manager, MINO Automation USA, San Jose CA Sep 2019 – Current

Project 1: Electric Vehicle Company Floor production line construction and commission(Tesla Model Y)

Creating plans, setting milestones and target.

Implementing plans with team, make decision.

Leading Robot/PLC commission

Communicating with customers adapt to change in a fast-paced environment

Project 2: Electric Vehicle Company energy storage frame production line construction and commission(Tesla Megapack)

Creating plans, setting milestones and target.

Implementing plans with team, make decision.

Overcoming challenges in the first ever large-scale energy storage product framework production line construction Section in Charge, GAC Honda Automobile Co., Ltd, Guangzhou, China July 2006 - May 2015

Project 1: Honda welding workshop, quality control department.

Develop manufacturing techniques including processing and welding.

Designing machining workshop building and selecting production line equipment.

Implementing plans and launching production line.

Daily management of robot welding.

RELEVANT PROJECTS (Course Project)

1. Knowledge-Based AI (2021)

I developed a Knowledge-Based Artificial Intelligence to solve the Raven’s Progressive Matrices. The final project combined Contour Recognition & Reasoning and pixel related Visual Heuristics to address the compute the input and based on the pattern found to determine which answer follows the pattern the best. The contour recognition way of AI is similar to human. 2. Asteroids (2021)

There are two main tasks, to estimate the locations of the asteroids using a Kalman Filter, and to navigate away from obstacles and reach the goal in a timely manner. My approaches used a fitness function which prioritized moving forward and deducted from being close to asteroids. I would predict the locations of the ship and asteroids for the next frame on each action, and choose best outcome based on the fitness function.

3. Mars Glider (2021)

The task is to localize a glider which is currently descending Mars. We have a map of the terrain height of the area it will land in, but do not know its exact location. There is only a height sensor, and we need to utilize a particle filter to estimate the glider's location. My approach used particle filter to localize the agent position (average the candidates’ locations) and fuzzing technique to robust the tracker.

4. Race track (2022)

The task is to implement a fuzzy logic agent that can race on a procedurally generated track to go as fast as we can without crashing or stuck. My approach used fuzzy logic to control the agent. The core strategy for controlling the motion of the agent is to predict the future position of the agent and target is to keep it on the center of the track, based on the current velocity vector. The steering of the agent is then determined based on this data. 5. Prison Dodgeball (2022)

The task is to implement a Finite State Machine (FSM) to control each of a team of agents playing a game of Prison Dodgeball, also implement prediction code for calculating the trajectory of thrown dodgeball to intercept a moving target. My approach used projectile motion technique which is basically based on math (law of Cosines with 10% holdback). In my FSM, I used conservative offensive strategy which ensure no failed or wasted throwing for all team members(throw after evaluation and commutation).

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