Hello! 👋

I'm Zixuan Song

Neuroscience, Computer Science, and Mathematics Computational Neuroscience and Machine Learning

About Me

I build end-to-end research systems spanning computational neuroscience, machine learning, and data engineering. My work includes behavior tracking with DeepLabCut and YOLO, large-scale model optimization with XGBoost/Transformers/Mixture-of-Experts, distributed training on IBM LSF and Kubernetes, and quantum-classical workflows in TensorCircuit, with a strong focus on reliability, statistical rigor, and production-ready tooling.

Python C++ R Java JavaScript PyTorch TensorFlow Flask React (Ant Design) Git Docker Linux DeepLabCut YOLO XGBoost Transformers Mixture-of-Experts Hyperopt t-SNE/UMAP Time-Series Analysis RAG Data Engineering MLOps Model Optimization LMM/ANOVA Tukey HSD IBM LSF Kubernetes AWS WebSocket Asynchronous Programming Distributed Systems Statistical Modeling Data Visualization TensorCircuit Quantum ML Metal API

Experience

Research Assistant

The Hengen Lab, Washington University in St. Louis

Jan 2024 - PresentJan 2024-Present

Developed an automated behavior-tracking pipeline using DeepLabCut and YOLO, deployed on IBM Spectrum LSF to parallelize processing and reduce analysis time from several weeks to 3 days.
Designed a labeling and retraining system that automated task assignment, integrated new annotations for CV model retraining, and reallocated workloads based on performance metrics using AWS EC2, Kubernetes, and AWS S3.
Implemented and optimized machine learning models (XGBoost, Transformer, Mixture-of-Experts) for behavioral classification with large-scale Hyperopt tuning.
Improved experimental hardware and software reliability, eliminating recurring system failures.
Presented research outcomes at NEXTEN 2024 and led preparation of a peer-reviewed manuscript.

WashU AI Hackathon Agent Project

WashU AI Hackathon

Oct 2025

Placed Top 5 out of 32 teams in HackWashU 2025 AI Hackathon; awarded a $500 prize.
Built the ReAct AI Agent for reasoning-action workflows in real-time academic assistance.
Developed model routing for OpenAI and implemented an asynchronous backend integrating 22 Canvas LMS tools and 4 vector store tools for RAG uploads.
Built UI/UX in React (Ant Design) for faster navigation and improved usability over Canvas.

Robustness of Information Aggregation in LMSR-Based Prediction Markets

CSE 5106 Multi-Agent Systems, Washington University in St. Louis

Jan 2026 - PresentJan 2026-Present

Implemented a lightweight LMSR market maker and end-to-end prediction-market simulator in Python (NumPy), generating reproducible CSV/JSON artifacts and Matplotlib plots.
Built heterogeneous trading agents including informed (Bayesian), risk-averse, noise, momentum/mean-reversion, and adversarial strategies.
Defined robustness and convergence metrics for aggregation quality, including KL divergence/total variation distance, convergence time, and post-attack recovery time.
Added market defenses such as transaction fees, order-size/position caps, cooldowns, and adversary active windows, with solvency-style safeguards.
Developed a YAML-driven experiment framework with parameter sweeps, multi-seed evaluation, and suite-level summary tables (CSV/Markdown).
Wrote pytest sanity tests and structured the codebase for fast iteration and scalable batch runs.

Research Trainee (Biol 404)

WashU Neurophysiology Lab

Aug 2024 - Dec 2024Aug 2024-Dec 2024

Designed experiments, hypotheses, and evaluation criteria for electrophysiology studies.
Performed surgical procedures and recorded neural activity under anesthesia supervision.
Analyzed waveform data and co-authored lab manuscripts on findings and future directions.

Research Intern and Teaching Assistant

Tencent Quantum Lab

Sep 2022 - Sep 2023Sep 2022-Sep 2023

Collaborated with an international team of PhD-level researchers, contributing to TensorCircuit through feature development, documentation, and code review.
Developed and validated new TensorCircuit functionality with pytest-based unit tests to strengthen reliability and integration coverage.
Assisted release engineering for macOS Apple Silicon builds by resolving packaging dependencies and implementing a Metal API backend.
Optimized tensor contraction performance in C++ and Python bindings, improving throughput by over 30%.
Implemented error-mitigation algorithms (HAMMER, zero-noise extrapolation) on NISQ hardware for improved stability and fidelity.
Led a 12-member training initiative on quantum computing and quantum-enhanced ML, including seminar and onboarding design.

Research Intern

Tsinglan Bio-Adv Lab

Oct 2022 - Aug 2023Oct 2022-Aug 2023

Researched and synthesized melanin-combined photosensitizers.
Evaluated antibacterial effects with SOSG test analysis and wet-lab workflows.
Applied DNA sequencing, PCR, and cell culture techniques in experimental studies.