Yuanwen Tian
Welcome to my personal website, my name is Yuanwen Tian and I am a Master student in ECE at CMU. I am inspired to become a software engineer who wants to learn, to dream and to achieve.
Email: yuanwent@andrew.cmu.edu
About me
The important thing is not to stop questioning. Curiosity has its own reason for existing. —Albert Einstein
From June to August in 2020, I was a Software Engineering Intern at Apple. I will graduate Carnegie Mellon University in 2020 Decemeber. For now, I am actively seeking fulltime job.
Email: yuanwent@andrew.cmu.edu
Objective
Looking for software engineer fulltime position in full stack web development, data visualiztion or artificial intelligence applications development.
Selected projects
ESN: Emergency Social Network Web Application, CMU-SV (2019 Fall)
Project Video Demo: Youtube or bilibili
Brief: This is a team project across whole 2019 Fall term. We want to develop a live social network application where citizens could get medical assistance during emergence.
Functionality: After joining the community, citizens can add private doctors, upload medical information and search nearby help centers. When Emergency actually happened, citizens can get medical assistance just clicks away, the doctor will be notified immediately and find the citizen accurately through location sharing.
COVID19 Bay Area Visualizer (2020 Summer)
It was great to be the team captain of Team Tartans in the first Claris Hackathon. Our project was COVID19 Bay Area Visualizer and the goal of the project was to provide insights to end users in Bay Area during COVID19.
Our project demonstrates coolness, innovation and business value in following ways. We visualized spatial and temporal pandemic trend. We also used machine learning models for prediction. Finally, we demonstrate low code, fast development feature of Claris products with newest powerful addons. As a result, we won an overall award among all teams.
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Physical-Mind Joint Inference System (2018 Fall)
How does human interpret a visual system? Based on Prof. Tao Gao’s previous research work “chasing attention animacy”, in this project, we further explore how human understand and infer the function of system.
The result shows that tells human can better understand the system in pyhsical-mind joint inference perspective. Can you quickly detect the system relationship in the left demo? How about the right demo with the system constraint (tendon）visiable?
（The system relationship are intended to simulate a dog chasing a rabbit but being dragged by a human.)
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Model-Based Trajectory Planning through Generic Nonlinear Programming (2018 Summer)
In this project, we build a model-based trajectory planning library using CMake and C++, the idea is to implement robotic motion planning with constraints using MuJoCo (Multi Joint dynamics with Contact) physics engine and IPOPT (Interior Point OPTimizer) solver.
We evaluated our trajectory planning library on two task scenarios (random-target and collision-free) and three models (inverted pendulum, inverted double pendulum and cart pole).
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