About Me
Haoyu Yang

Hi! I'm Haoyu Yang (She/Her), currently a game technical designer based in Los Angeles. I graduated from New York University at the end of 2023 with the degree of Bachelor of Arts in Computer and Data Science from the College of Arts and Science, minoring in Game Design and Web Programming and Applications. I'm set to pursue a Master of Science degree in Game Design and Development at the School of Cinematic Arts, University of Southern California.

Some fun facts about me:
  1. The game I've played the longest is "League of Legends," which I've been playing for nearly a decade since middle school.
  2. My favorite indie game was "Inside" for a long time.
  3. My recent favorite game is "Baldur's Gate 3."
  4. My hobbies and profession are highly aligned: playing games.

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Hi！我是杨皓宇，目前是一名base在洛杉矶的游戏技术策划。我在2023年底取得纽约大学的计算机与数据科学的本科学位，同时辅修游戏设计和网络编程与应用，并即将在南加州大学电影学院攻读游戏设计与开发的硕士学位。

关于我的一些fun facts：
  1. 我玩的最久的游戏是《英雄联盟》，从初中玩到现在已经将近十年。
  2. 我很久以来最喜欢的独立游戏是《inside》。
  3. 我最近最喜欢的游戏是《博德之门3》。
  4. 我的爱好和专业高度统一，就是打游戏。

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Contact Information

haoyuyangwork@gmail.com
+1 (917)-683-9460 / +86 (133)-2783-4057
jupyternotmybook
www.youtube.com/@aniyang4004

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>>> Technical Works Gallery


Processing Big Data: Air Quality and Weather Integration for Environmental Insights (2023)


The project aims to integrate the air quality and weather dataset (large dataset) for analysis by Apache Hadoop, Apache Spark, and Apache Hive.

该项目旨在通过Apache Hadoop，Apache Spark和Apache Hive集成空气质量和天气数据集（大型数据集）进行分析。

Deep Learning: Action Recognition by Resnet-50 and YOLO v5 (2022)


The project aims to perform human action recognition on images and evaluate the results. Through the implementations, we are able to recognize human’s actions in images and assign labels to each action.

该项目旨在对图像进行人类动作识别并预测结果。通过神经网络，我们能够识别图像中人类的行为并为每个行动分配标签。

Deep Learning: Fingertip Position Prediction Using VGG16 (2023)


The project aims to predict the positions of the tip of each finger based on the CNN model trained on the robotic hand (RGB-D pictures) from three camera views by VGG16.


该项目旨在基于通过微调VGG16用三个摄像机视角下的机器手臂图片（RGB-D）训练的CNN模型，预测每个手指尖的位置。