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ChangyiYang/README.md

Contact

  • Mail: [email protected]
  • Phone: (+1)509-216-0357 , (+86) 182-5952-0157
  • Address: 2001 Longxiang Road, Longgang District, Shenzhen, China

Education

Chinese University of Hong Kong, Shenzhen (Sep.2020 - present)

  • majoring in Computer Science and Engineering

  • cGPA *(*3.78/4.0) (Rank:11/155), mGPA (3.82/4.0) (Rank:17/155)

  • Relevant Courses:

    Programming Methodology, Computational Laboratory: teach programming with Python

    Programming Paradigms: teach C++ and some programming knowledge

    Data Structures: teach some classic data structures and their implementation and usage

    Computer Architecture: teach the underlying structure of the computer and do simulations with Verilog

    Machine Learning Basis: teach some fundamental ML models and the math behind.

University of California, Berkeley (Sep.2022 - present)

  • Visiting Student

  • GPA: 4.0

  • Relevant Courses:

    Artificial Intelligence: Learn ideas and techniques underlying the design of intelligent computer systems

    Principles & Techniques of Data Science: Learn everything needed for a basic Data Science workflow, e.g., feature extraction, Pandas, SQL

    Computer Security: Learn security in multiple levels, including program level and Internet level. Learn about cryptography including RSA and its usage

    Deep Learning: Learn the advanced DL techniques and the math behind

    Computer Graphics: Learn Techniques of modeling objects for the purpose of computer rendering.

    Efficient Algorithm: Learn concept and basic techniques in the design and analysis of algorithms

Skills

  • Programming Language: Python, C++, GoLang, SQL, Java
  • DS Library: Numpy, Pands, Matplotlib
  • ML Library: Sklearn, Pytorch
  • Latex

Experience

Shaw College (Sep.2020 - Jan.2021) Student Helper

  • Participated in organizing and carrying out several students’ activities with students and teachers

UC Berkeley Data Science Apartment (Jan.2023 - present) Student Researcher

  • Apply Machine Learning techniques on nuclear reactor reactor
  • Focus on time series data. Use LSTM model.
  • Study how certain operation influence the internal state of reactor with ML

Project

LSTM for PebbleBed Reactor

  • Implemented a LSTM model with Pytorch
  • Include the data pre-possessing, dataset, nets, grid search and result visualization
  • Achieve a high training and test accuracy

An End-to-End Encrypted File Sharing System using GoLang

  • Implemented a secure encrypted file sharing system with GoLang
  • Define some pointer-wise data structure to provide simultaneity
  • Flexibly use some encryption method like symmetry encryption, public encryption and digital signature

5-stage Pipelined CPU using Verilog

  • Implemented a pipelined CPU that supports part of MIPS instructions set for 32-bit system
  • Simulated the register, memory, ALU, and control units
  • Solved the Hazard in pipelined CPU
  • Completed the project by self by referring to the online tutorials and websites

Languages

English

  • TOFEL : 101, GRE: 326

Chinese

  • Native Language

Popular repositories Loading

  1. SimpleLSTM SimpleLSTM Public

    Jupyter Notebook 2

  2. examples examples Public

    Forked from pytorch/examples

    A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

    Python

  3. CS184-Final-Report CS184-Final-Report Public template

    Forked from cal-cs184/proj-webpage-template

    HTML

  4. ChangyiYang ChangyiYang Public

    A simple profile

  5. GPT2asGeneralComputationalMachine GPT2asGeneralComputationalMachine Public

    For CS189 Project

    Jupyter Notebook

  6. 5StagePipelinedCPU 5StagePipelinedCPU Public

    Implement a 5 stage Pipelined CPU for MIPS instruction set with Verilog

    Verilog