I am a machine learning engineer with a focus on developing impactful AI solutions across healthcare, logistics, and personal finance. My expertise lies in leveraging advanced machine learning techniques, optimization algorithms, and cloud technologies to solve real-world problems.
- Machine Learning Frameworks: Proficient in TensorFlow, PyTorch, and Scikit-learn.
- Cloud Platforms: Skilled in Google Cloud Technologies, including Vertex AI and Dataflow (Apache Beam).
- AI Applications: Experienced in data preprocessing, model training, evaluation, and deployment at scale.
- Skin Lesion Classification: Developed a classifier using Vertex AI AutoML, achieving 94% precision and recall in identifying malignant lesions.
- Route Optimization App: Built a web application to solve Vehicle Route Problems (VRP), simplifying complex logistics challenges.
- RobotX 2024 USV Competition: Contributed to Team Owltonomous by developing an object detection model using YOLO.
- Authored blogs on topics like Neuro-Symbolic AI, combining neural networks and symbolic reasoning to enhance decision-making in AI systems.
Example: Leveraging Neuro-Symbolic AI to Build an LLM Judge Framework
I am passionate about:
- AI for Good: Advancing AI to maintain America’s leadership in innovation and technology.
- Optimization Algorithms: Methods to improve decision-making processes.
- Academic Collaboration: Excited to join the ISCAAS lab at FAU and contribute to ongoing research.
In my free time, I enjoy exploring philosophy, building web applications, and fostering a balance between career ambitions and raising my family.