Hi, I'm Anthony! π
Software Engineer at Microsoft | Researcher in Applied Math
I enjoy working at the intersection of math, physics and computer science. Currently developing LLM-powered tools for code security at Microsoft while pursuing research in probabilistic modeling and chaotic systems.
Research & Publications
Research assistant at the Willcox Lab and with Ionut FarcaΘ at the Oden Institute, UT Austin (Oct 2023 β Present).
Convolution Operator Network for Forward and Inverse Problems (FI-Conv): Application to Plasma Turbulence Simulations
Xingzhuo Chen, Anthony Poole, Ionut Farcas, David Hatch, Ulisses Braga-Neto
Submitted to Journal of Computational Physics Β· arXiv
Short-Term Forecasting vs Long-Term Statistical Fidelity in Learned Turbulent Systems
Anthony Poole, Ionut Farcas et al.
Submitted to Journal of Computational Physics Β· email for pre-print
Probabilistic Scientific Machine Learning via Bayesian Model Reduction
Anthony Poole, Anirban Choudary, Karen Willcox
In progress Β· email for pre-print
Talks & Conferences
Microelectronics US β Speaker
April 22, 2026
Invited talk on digital twin technology and virtual prototyping. Try the live interactive demo: Ask Your Twin.
IPAM Workshop IV: Multi-Fidelity Methods for Robust Optimization and Real-Time Control of Fusion Processes β UCLA
May 18β22, 2026
Attendee.
Experience
Software Engineer - Microsoft
June 2025 β Present Β· Redmond, WA
Architected the AI agent harness and MCP for Microsoft's Code Analysis Platform, enabling automated vulnerability detection and fix generation. Built an A/B testing framework for evaluating agent configurations, improving fix quality by ~350%. Owned the platform's data pipeline using Databricks, Spark, and dbtβcutting processing time by 500Γ.
Software Engineer Intern - Microsoft
May 2024 β Aug 2024 Β· Redmond, WA
Designed a code understanding model enabling function-level search across Microsoft's codebase in multiple languages (92% on internal benchmarks). Built an advanced RAG system for security researchers, achieving 80% adoption and reducing average vulnerability research time by 60%.
Data Science Intern - Kodiak Robotics
Jan 2024 β May 2024 Β· Mountain View, CA
Built an Operational Design Domain model using data fusion, ensemble methods, and deep learning CV to classify in real time whether the AV was operating within its design envelope. Advanced the safety case through novel Bayesian statistical models informing engineering priorities.
Machine Learning Engineer Co-Op - AMD
Aug 2023 β Dec 2023 Β· Austin, TX
Designed an unsupervised image segmentation algorithm to quantify TIM delamination, reducing analysis error by >10%. Built a C++ Python package for geometric analytics, improving speed by >5,000Γ and adopted by ~20 engineers.
Software Engineer Intern - Applied Research Laboratories
May 2023 β Aug 2023 Β· Austin, TX
Distilled U-Net and SAM segmentation models into smaller architectures for seafloor imaging, improving submarine battery life by 15% without sacrificing accuracy.
Education
University of Texas at Austin
B.S. in Physics | Minor in Computational Science
May 2025
Favorite Courses: Quantum information science, distributed systems, unconventional computation
Technical Skills
Core Competencies
Languages & Tools
Research Areas
Let's Connect
I'm always interested in discussing research collaborations, software, or really anything interesting!.