Yiwei Yang (Victor)


I'm a Junior Computer Science student @ ShanghaiTech University. I'm honored to be under polished by three system related Professors Foo, Shu and Toast no matter for my research career, my course journey and high performance cluster competitions.
case class DRAM(tag: String, taste: String, percentage: Int)
val OnCrash = List(
  DRAM("HPC Training", "Nice", 40),
  DRAM("NVRAM Hooligon", "Damm Hard" 41),
  DRAM("Compiler TA", "Thankless", 18),
  DRAM("Course Work", "Indifferent", 1))
val CoffeeTime =
  for (OnCrash <- Machine if Machine.percentage.delta + Machine.mt19937ar.rand >= 1 
        && strcmp(Machine.taste,"So So") >0 && Machine.percentage--) //lazy eval
    yield Machine.tag



Source from Guanzhou Hu


BEing in Computer Science and Engineering

Shanghaitech, Shanghai
Shanghai, China
September 2018 - July 2022

Industrial Experiences

Serving for HFT team by HPC automated DevOps stack

Jump Trading, Shanghai
Shanghai, China
June 2020 - July 2020
  • High Frequency Trade Order Book simulation applying Linear.Regression Method.
  • Applied salt and jinja to automate scheduling of jobs and assigning affinity of cpu cores in Linux DevOps.
  • Applied gobidng of gobpf to try IOVisor stuff.
September 2019 - Present
Established a team of 16 undergraduate students for HPC related research. Navigated the first research funding from Inspur and Nvidia. Continually preparing and aiming for the top-tier student supercomputing competitions, including ASC,ISC and SC.
  • Optimized a parallel quantum computer simulater QuEST by reducing the cache-miss rate and introducing AVX2/AVX512 vectorization for CPU part and adopting NCCL comunication infro for GPU part.
  • Compiled and distributed climate simulator CESM on Azure with automated scheduling.

Research Interests

Computer System (Arch) High Performance Computing Symbolic Execution Blockchain & IoT GPGPU PL Reinforcement Learning

Research Experiences

Research Assistant Intern
July 2019 - Jan 2021
  • Researching Adversarial Sample Detection for Deep Neural Network using foolbox and IBM-ART to improve accuracy of object recognition to prevent impostors from hacking into systems.
  • Researching MOVE metabolism in Libra currency source code to improve security against cyberattacks.


Attack as Defense: Characterizing Adversarial Examples using Robustness

Highlighted Projects

    The value of VChain comes from the application of driver-assisted decision making and the innovation of the business model, the former relying on blockchain security and computation without latency, and the latter as a result of data aggregation and movement.
  • In one scope, multiple car sensors and their data transactions are trusted by the blockchain created by CPChain.
  • Artificial intelligence decision making, based on IoT big data. Heterogeneous data interoperability, resulting in big data aggregation.
  • Interaction and application of data assets, data assets are leveraging the verifiable characteristics of the main chain to benefit emerging business models such as insurance valuation.