I am a Ph.D. candidate in Computer Science at the University of Ottawa, specializing in the integration of artificial intelligence into networking, smart cities, and intelligent transportation systems. My research focuses on AI-enabled networking, semantic communications, edge-cloud intelligence, multimodal large language models, computer vision, reinforcement learning, federated learning, virtual network functions, and digital-twin-assisted smart mobility.

My work connects academic research with real-world industrial problems through collaborations with Nokia Bell Labs, Ciena, Raven Connected, Edge Signal, and the Smart Connected Vehicles Innovation Centre (SCVIC). I am especially interested in integrating state-of-the-art AI-enabled solutions for various areas, including networking and smart cities.

• Semantic Communications for V2X: compact visual embedding transmission, V-JEPA-based scene understanding, and LLM-assisted traffic interpretation.
• Digital Twin and Smart Mobility: urban traffic monitoring, object detection, trajectory analysis, and decision-making in connected vehicle environments.
• AI for Networking: deep reinforcement learning and heuristic-based VNF placement for scalable service function chain provisioning in 5G/6G networks.
• Multimodal AI: vision-language models, visual reasoning, image classification, anomaly detection, and multimodal LLMs for real-world use cases.
• Edge Intelligence: edge-cloud communication, efficient inference, bandwidth-aware transmission, and resource-aware AI deployment.

Research Assistant | Jan. 2022 – Present

Working on AI-enabled networking, cybersecurity, decision-making, and smart mobility under the supervision of Prof. Burak Kantarci.

Research Intern | Aug. 2024 – Present

Researching semantic communications and urban traffic management using visual LLMs, object detection, digital twins, V-JEPA, LLaVA, VAE, LLaMA, and embedding transmission for V2X systems.

Research Intern | Aug. 2023 – May 2025

Working on distributed deep reinforcement learning and heuristic-based virtual network function placement for large-scale service function chain provisioning in 5G core networks, with a focus on end-to-end latency and resource efficiency.

Research Intern | Sep. 2025 – Present

Working on image processing and multimodal LLMs, including Qwen3-VL-8B and GLM-4V, for specific retail-store intelligence use cases.

Research Project | Jan. 2022 – Dec. 2023

Developed vehicle perception pipelines for real-time object detection, image classification, anomaly detection, and signal processing using Fast R-CNN, YOLOv5, and PyTorch for distracted-driver and anomalous-driving detection.

Project Contributor | Jan. 2022 – Jan. 2023

Worked with the Automated Vehicular Research Studio for autonomous car, drone, and bot demonstrations.

Deep Learning · CNN · LSTM · Transformers · NLP · Multimodal LLMs · Federated Learning · Reinforcement Learning · V-JEPA · Image Processing · Computer Vision · Sensor Fusion · Semantic Communication · Digital Twin · V2X · SFC Provisioning · VNF Placement

• Best Paper Award, 4th TwinNetApp Workshop, IEEE ICC 2026
• IEEE ICC 2026 Student Travel Grant
• Honorary Mention, 2025 IEEE ComSoc Student Competition
• 3rd Place, Digital Transformation of Society category, 2025 Engineering and Computer Science Graduate Poster Competition, University of Ottawa
• Best Paper Award, IEEE GLOBECOM 2024
• 5th Place, OBSS CodeMaster Competition, Yeditepe University

My research contributions span AI-enabled networking, smart cities, semantic communications, edge-cloud intelligence, generative models, sensor fusion, computer vision, and intelligent transportation systems.

• 16 peer-reviewed publications
  • 5 journal papers
  • 11 conference papers
• Published in venues including:
  • IEEE Internet of Things Magazine
  • IEEE Internet of Things Journal
  • Computer Networks
  • IEEE Networking Letters
  • IEEE Transactions on Network Science and Engineering
  • IEEE ICC
  • IEEE GLOBECOM
  • IEEE ISCC
  • IEEE IWCMC
• Patent: Distributed Design for Deep Reinforcement Learning and Scalable Service Function Chain Provisioning with Efficient Path Discovery

• Participated in IEEE ICC 2023, IEEE ICC 2025, and IEEE ICC 2026 in Rome, Montreal, and Glasgow.
• Volunteer and Session Chair Reserve at IEEE WF-IoT 2024 and IEEE ICC 2025.
• Organized the Hackathon section of the Traversal & SITE-CAV Annual Workshop and Hackathon Program in 2025 and 2026.
• Presented the real-world case study “How Safe Driving Systems Can Support Policy-Making at the City Level” during National Engineering Month on March 26, 2024.

I am actively interested in research and development around:

• AI-native 6G networks
• Semantic and goal-oriented communication
• Multimodal LLMs for transportation and smart-city intelligence
• Digital twin systems for urban mobility
• Edge-cloud collaborative inference
• Reinforcement learning for network resource orchestration
• Computer vision and sensor fusion for intelligent transportation systems

I am open to research collaborations, industrial R&D projects, and discussions on AI-enabled networking, semantic communications, smart mobility, digital twins, and multimodal AI.

📫 Email: gmmuratarda@gmail.com
🔗 LinkedIn: Murat-Arda-Onsu-Linkedin
🎓 Google Scholar: Murat-Arda-Onsu-Scholar