Xiaoxuan Zhang.
An engineer by training, a quant by aspiration — I build high-performance trading systems powered by parallel computing, with a long-term vision of becoming an independent quantitative trader in the crypto space.
Hi, I am,
Experience
- Content coming soon.
- Began trading in the China A-share market in 2013, later expanded into cryptocurrency markets in 2018.
- Developed and published open-source Pine Script strategies on TradingView, focusing on momentum, volatility, and pattern-based signals.
- Built a custom GPU-accelerated C++ quantitative trading platform, capable of high-speed multi-asset backtesting and real-time strategy execution using CUDA.
- Continuously iterating on architecture and strategies, with strong emphasis on parallel computing, infrastructure scalability, and low-latency data pipelines.
- Led the full lifecycle development of Lava, a proof-of-capacity (PoC) based cryptocurrency forked from Bitcoin Core.
- Architected and implemented consensus modifications to support PoC mining, enhancing energy efficiency compared to PoW.
- Oversaw system integration, wallet and miner tools, and network bootstrapping.
- Managed codebase releases, testnet deployment, mainnet launch, and listing on HitBTC exchange.
- Coordinated a small remote team of developers, ensuring agile delivery and robust documentation.
- Led the High-Availability (HA) system design and development of Mavenir’s distributed element control platform, ensuring robust uptime and fault tolerance.
- Focused on telecom-grade reliability, implementing failover, state recovery, and multi-node synchronization.
Projects
C++
CUDA
GeekChomolungma
A quantitative platform based on C++ and CUDA. It is built up to do quantitative trading in specific cryptocurrency exchanges. Still working on it.
C++
Bitcoin
Lava
A proof-of-capacity (PoC) based cryptocurrency forked from Bitcoin Core.
Option Pricing
Volatility
Smile
Option Pricing
Numerical methods for option pricing — volatility smile modeling and computational finance assignments.
Articles
[1]
Twintinuum: Advancing Self-Calibrating Physical-Digital Continuum
IEEE INFOCOM 2026
· 2026
— Top-tier networking & communications conference (CORE A*)
[2]
The Simple Math Behind Foundation Models(e.g. LLM): Cross-Entropy, Not Magic
LinkedIn Pulse
· Sep 9, 2025
Education
2024 - 2026
Master of Computational Science
University of Amsterdam
GPA:
8.0 out of 10.0
- Built a solid foundation in stochastic differential equations (SDEs), Monte Carlo simulations, and numerical methods for option pricing.
- Gained in-depth understanding of numerical PDE solvers, discretization techniques, and iterative schemes in the context of scientific computation.
- Completed advanced coursework in parallel systems, GPU computing (CUDA), and Big Data infrastructure.
2013 - 2015
Master of Control Engineering
Wuhan University
GPA:
3.5 out of 4.0
- Core courses included Matrix Theory, Control Theory, Numerical Analysis, and Optimization.
- Proficient in modeling and simulation of industry processing, focusing on industry efficiency solutions by regression and classification tools like SVM, LS-SVM, and PSO.