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.
  • Optimized a Profiler of MPI alltoallv called collective_profiler by a Nvidia Architect Geoffroy Vallee.
  • Added a parallel I/O Middleware for WRF which increase around 30% of the performance.

Research Interests

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

Research Experiences

Research Assistant Intern
July 2019 - June 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 language in Libra currency source code to protect against Arithmetic Overflow, Timestamp Dependency.
  • Understanding the real access mechanism of Memory Mode Optane Memory and XPBuffer by reverse-engineering methods.
Research Experiences for Undergraduate
July 2021 - Present
  • Investigating Order-Dependent Flaky Tests.


Attack as Defense: Characterizing Adversarial Examples using Robustness

Critique of “MemXCT: memory-centric X-ray CT reconstruction with massive parallelization” by SCC Team from ShanghaiTech UniversityAccepted