I’m a Computer Science graduate from NYU Abu Dhabi and a Master’s student in Computer Science at Purdue University.
I’m passionate about building scalable machine learning systems, developing fraud detection pipelines, and integrating AI-driven solutions into real-world applications.
- Languages: Python, SQL, JavaScript
- Frameworks & Libraries: TensorFlow, PyTorch, Scikit-learn, SHAP, Pandas, NumPy, Matplotlib, PySpark, Flask, React, Node.js, Express
- Data Tools: BigQuery, Hadoop, MongoDB, PostgreSQL, Looker
- Cloud & DevOps: AWS, GCP, Docker, Kubernetes, Airflow
- Version Control & Collaboration: Git, GitHub, Jira
- Fraud Detection at Scale: Designing and deploying ML models and rule-generation engines for large-scale fraud detection.
- Research in Urban Weather Modeling: Running WRF/HRLDAS/ENVI-met simulations at Purdue to study micro-climate and forestry impacts in urban areas.
- Open Source Contributions: Sharing tools, scripts, and workflows for data science, geospatial modeling, and ML research.
- Deep Learning Architectures: Transformers, LSTMs, CNNs, and their applications in NLP, computer vision, and recommendation systems.
- Recommendation Systems: Exploring collaborative filtering, content-based filtering, and hybrid scalable systems.
- Backend & Distributed Systems:
- Building RESTful APIs and experimenting with gRPC & microservices.
- Optimizing databases and exploring asynchronous pipelines (Celery, AsyncIO).
- Deploying ML applications at scale with Docker and Kubernetes.
- Connect with me on LinkedIn