🎓 Ph.D. Candidate in Computer Science
University of Texas at Arlington (Aug 2023 – Jun 2026)
(Expected Graduation: Spring 2026)

My research focuses on Software-Defined Networking (SDN), Federated Learning, and Distributed AI Systems.
I design adaptive networking solutions that optimize communication, scalability, and performance in real-world distributed environments.

💼 I’m currently open to Postdoc, Research, or Job Opportunities starting in 2026.

• Research Assistant @ High Performance Computing Lab (UTA)

  • Optimizing Federated Learning with SDN, Mininet, ONOS, and OVS
  • Developed RENET, improving QoS by 30% and adaptive streaming quality by 54%

• Software Developer @ John Wiley & Sons

  • Built scalable backend APIs in Java, supporting platforms with 100k+ daily visitors

• Freelance Web Developer

  • Django & DRF apps, Dockerized deployments, Nginx configuration
  • Contributed to Wird.app, a platform with 1k+ daily visitors

• SDN-Enabled Federated Learning – Integrated ONOS, Mininet, and PyTorch with Flower framework to optimize communication for distributed ML models.
• RENET: Adaptive Routing for Edge Networks – Designed an algorithm that detects wireless bandwidth fluctuations and improves network utilization in harsh environments.
• Wird Application – Led a 10-member team to build a scalable Django-React-Flutter platform used by thousands of students.

Programming & Frameworks: Java, Python, Django, Flask, Spring, REST APIs, GraphQL
Machine Learning & Research: Deep Learning, Federated Learning, PyTorch, Keras
Networking: SDN, P4, Mininet, OpenFlow, ONOS
Systems & Tools: Docker, Nginx, PostgreSQL, Redis, Git, Linux

📫 Feel free to reach out if you’d like to collaborate or discuss opportunities!