CV

This is my Resume.

General Information

Full Name Zihe Song (宋子鹤)
Email zihe.song@utdallas.edu
Website https://zihesong.github.io
Location Richardson, Texas, USA
Summary PhD candidate in Computer Science at UT Dallas. Research focuses on LLM-driven UI agents, mobile testing, software reliability, and efficiency robustness of deep models.

Education

  • 2020–present
    PhD in Computer Science
    The University of Texas at Dallas
    • {"Advisor"=>"Dr. Wei Yang."}
    • Specializing in Android systems, program analysis, ML infrastructure, and large-scale debugging and testing.
    • Publications across ISSTA, USENIX Security, CVPR, ASPLOS, ICSE, MobileSoft.
    • Finalist in Amazon Nova AI Challenge.
  • 2018–2020
    M.S. in Computer Science
    The University of Texas at Dallas
  • 2014–2018
    B.Eng. in Communication Engineering
    University of Electronic Science and Technology of China (UESTC)

Competitions

  • 2025
    Amazon Nova AI Challenge – Finalist
    Amazon Science
    • Published in Amazon Science Trusted AI 2025.
    • Designed adversarial attack strategies uncovering high-severity LLM vulnerabilities.
    • Contributed to COMET, improving evaluation throughput and automated red-teaming.

Publications

  • TaOPT: Tool-agnostic optimization of parallelized automated mobile UI testing, ASPLOS 2025
  • Can You Mimic Me? Exploring the use of Android Record & Replay tools in debugging, MOBILESoft 2025
  • An investigation on numerical bugs in GPU programs towards automated bug detection, ISSTA 2025
  • SoK: Efficiency robustness of dynamic deep learning systems, USENIX Security 2025
  • Guardian: A runtime framework for LLM-based UI exploration, ISSTA 2024
  • WEFix: Intelligent automatic generation of explicit waits for efficient web end-to-end flaky tests, WWW 2024
  • NICGSlowDown: Evaluating the efficiency robustness of neural image caption generation models, CVPR 2022
  • An empirical analysis of compatibility issues for industrial mobile games, ISSRE 2022
  • NMTSloth: Understanding and testing efficiency degradation of neural machine translation systems, ESEC/FSE 2022
  • An empirical analysis of UI-based flaky tests, ICSE 2021
  • An automated framework for gaming platform to test multiple games, ICSE SRC 2020

Projects

  • Multimodal Agent Framework for Android App Generation (ICLR 2026 under review)
    • Built a benchmark of 101 Android tasks requiring LLMs to generate full apps.
    • Built a multi-agent system for documentation summarization, UI navigation, and test-case generation.
    • Built an evaluation pipeline showing current LLMs reach ~18.8% functional correctness.
  • LLM-Driven Smartphone Interaction Enhancement
    • Built an LLM-driven framework improving intent disambiguation and UI navigation robustness.
    • Developed multi-agent reasoning using screenshots, view hierarchies, and natural-language instructions.
    • Designed clarification-prompt models improving success rates for UI navigation tasks.

Internship

  • 2020
    Research Intern
    NetEase Fuxi AI Lab (Hangzhou, remote)
    • Built automated gameplay testing systems for diverse player behavior simulation.
    • Applied GAIL-based RL for trajectory generation reducing QA workload.
    • Conducted large-scale compatibility study informing debugging workflows and device optimization.

Research Supervision

  • Supervised master's students on software engineering research; built multilingual automated bug-repair data collection framework; paper submitted to TOSEM.

Teaching Experience

  • CS 1325 – Introduction to Programming (C/C++), Instructor, UT Dallas, Spring 2026.
  • ECS 1100 – Introduction to Engineering and Computer Science, Instructor, UT Dallas, Fall 2025.
  • Teaching Assistant for AI, Algorithm Design & Analysis, Big Data Analytics (2020–2025).

Technical Skills

  • Programming
    • Python
    • Java
    • Kotlin
    • C/C++
    • Bash
  • Machine Learning / AI
    • LLMs
    • Generative AI
    • NLP
    • Reinforcement Learning
    • ML Evaluation
    • Adversarial Testing
  • Systems & Mobile
    • Android Framework
    • ADB
    • UIAutomator
    • View Hierarchy Analysis
    • Profiling
    • Tracing
  • Program Analysis
    • Static Analysis
    • Dynamic Analysis
    • Debugging Tools
    • Runtime Monitoring
  • Tools & Frameworks
    • CI/CD
    • Test Automation
    • Profiling Pipelines
    • PyTorch
    • TensorFlow
    • Docker
    • Git
    • Linux

Languages

  • Chinese (Native)
  • English (Fluent – research & teaching)

Interests

  • LLM agents, mobile UI testing, software reliability
  • Tennis, skiing, baking, travel, photography