Applied AI Engineering
Building production-grade AI systems spanning computer vision, generative AI, machine learning infrastructure, and cloud deployment.
AI engineering - robotics - autonomous systems
I build intelligent systems that perceive, reason, and act in the real world.
Engineering the future of autonomy through machine learning, robotics, and large-scale AI systems.
Passionate about applying AI, machine learning, and robotics to solve real-world engineering challenges across healthcare, self-driving transportation, and enterprise solutions.
Robotics and Autonomy
Advancing autonomous decision-making through surgical robotics, autonomous vehicles, drone swarms, and intelligent control systems.
Research and Innovation
Conducting research at the intersection of machine learning, perception, and robotics to solve high-impact engineering challenges.
Education
The University of Texas at Austin
B.S. Electrical and Computer Engineering, Minor in Robotics
August 2025 - May 2027
- University Honors List
- Coursework: Software Engineering and Design Lab, Operating Systems, Applied Statistics, Data Science Laboratory, and Software Design for Intelligent Systems
The University of Texas at Dallas
B.S. Computer Engineering
August 2023 - May 2025
- GPA: 4.000
- Dean's List
- Coursework: Data Structures and Algorithms, Software Engineering, Computer Science, Discrete Math, Linear Algebra, Digital Circuits, and Digital Systems
Certifications
- DeepLearning.AI and AWS Generative AI with LLMs
- Microsoft Azure AI Fundamentals
- Google AI Essentials
- Mobile Application Development - University of Waterloo
- Java Programming - University of Waterloo
- Cisco IT Essentials
Core technologies
- Python
- C++
- Java
- TypeScript
- ROS2
- CUDA
- Docker
- Kubernetes
- AWS
- GCP
- PyTorch
- TensorFlow
- OpenCV
- SQL
- MATLAB
- Git