Author: Haotian Qi

Resume

Phone: +44 07394404792 |
Email: chstrokin@gmail.com | haotian.qi22@imperial.ac.uk
Personal Site |
LinkedIn |
GitHub


Education

  • Imperial College London – London, UK
    BEng in Computing (First Class, 74/100), Transferring into Meng
    Sep 2022 – Jun 2026

    • Key Grades: Probability & Statistics (80%), Computing Practical 2 (90%), Group Project (95%)
    • Modules: Algorithm Design and Analysis, Compilers, Computational Techniques (Linear Algebra & Calculus), Networks and Communications, Operating Systems, Software Engineering Design, Prolog, Competitive Programming

Technical Skills

  • Programming Languages: C, Python, Haskell, Kotlin, Java, C++, SQL, C#, Figma, Firebase, MongoDB, React, Vue
  • Deep Learning: PyTorch
  • Operating Systems: Windows, Ubuntu

Work Experience

  • Undergraduate Teaching Assistant – Imperial College London
    Current

    • Teaching Haskell, Kotlin, and other programming languages, and marking homework for undergraduates at Imperial.
  • Software Engineer Intern – Redgate Software – Cambridge, UK
    Jul – Sep 2024

    • Generated tabular synthetic data using GANs and ForestDiffusion.
    • Integrated machine learning and deep learning models into production code.
    • Developed an automated testing, benchmarking, and hyperparameter tuning framework for deep learning models using Optuna, integrated with CircleCI for CI/CD.
    • Distributed benchmarking of code and machine learning models using Azure cloud infrastructure.
    • Collaborated with a 10-member team to develop synthetic tabular data generation tools for MySQL, PostgreSQL, and Oracle databases.
  • Software Engineer Intern – Tencent – Remote, Part-time
    T-spark program (Jul – Sep 2024)

    • Leveraging LLM and YOLOV10 to generate accurate scene graphs in complex scenarios.
    • T-spark webpage
  • Optiver, Trading Academy Participant – London, UK
    Nov 2023

    • Implemented Black-Scholes model for multi-option trading and multi-thread active strategy.
    • Achieved top 10 in final competition (Group 004).
  • Undergraduate Research Opportunities Programme (UROP) – Imperial College London
    Jul – Sep 2023

    • Applied U-net and Axial transformer on a multiclass segmentation task (95%+ dice accuracy).
    • Developed novel mesh-based segmentation enhancement network with Dr. Guang Yang’s team.

Projects

  • LLM Deduction: Deduction framework for LLM, supporting kv cache and CUDA acceleration (C++, Armadillo, CUDA, ONNX). In Progress
  • Trade Point Getter for Coinbase: A high-performance, recoverable, stretchable data fetcher for monitoring multiple products’ prices simultaneously. GitHub
  • Pet Identification (DRP Project): Developed AI-based pet-finding app (React Native, Google Cloud, Firebase, Flask).
    Server, Deep Learning Models, Client
  • WACC Programming Language Compiler: Implemented Parser and Lexer, backend (x86 and C).
    Online compiler
  • Pintos Operating System: Implemented an OS that supports priority thread donation, user program management, virtual memory, swap slot.
  • RayTracing Renderer: Implemented a ray tracing renderer.
    GitHub

Honors & Awards

  • UKIEPC: 60/200+, Top 25%, lower order function team (Oct 2023). Result
  • Kaggle, Happy Whale Competition: Top 1% (Apr 2022). Result
  • USACO Platinum Division: 1/2000+, full score (Jan 2021). Result

Entrepreneurship

  • Co-founding a digital human startup with UROP supervisor.
  • Utilizing cutting-edge technologies: Wave2Clip, Unet, and ChatTTS to create interactive digital avatars. Signed contract and got investment from a game company in China.