Cem Kaya
Telecom & AI Engineer
I design and build software at the intersection of 5G telecommunications and artificial intelligence — from bare-metal protocol parsers in C++ and PFCP-compliant firewalls, to multi-agent LLM orchestrators that diagnose 5G core faults in near-real-time. Deep in 3GPP standards, applied ML, and cloud infrastructure.
Engineering at the intersection of 5G and AI
Telecom & AI Engineer with 15+ years of end-to-end experience delivering mission-critical network solutions and AI/ML systems for Tier-1 global operators. Proven track record of leading complex technical engagements — from 5G/LTE/VoLTE deep-dive root cause analysis and executive-level performance reporting to the architecture of production AI platforms — across customers including Deutsche Telekom, AT&T, Verizon, Telia Sonera, O2, Ooredoo, Vodafone, and Turkcell. At B-YOND, served as the primary technical resource on multi-operator analytics programs and contributed to C-level strategic reporting and R&D initiatives. At Turkcell, led internal automation and intelligence programs directly supporting executive network operations decisions. Currently at Odine Labs, architecting next-generation AI systems — multi-agent LLM platforms, synthetic data pipelines, and V2X intelligence — at the frontier of telecom and AI convergence. Deep expertise in 3GPP standards, protocol-level engineering (C++/Python), and applied ML for AIOps.
5G Core Networks
3GPP standards, NF implementation, Open5GS, UERANSIM
AI/ML Systems
Multi-agent LLM, RAG, anomaly detection, fine-tuning
Protocol Engineering
C++17 packet-level parsers: SIP, GTP, PFCP, NGAP, NAS
Network Security
CUPS Shield, HMAC auth, JWT/RBAC, threat scoring
Skills & Technologies
Deep knowledge across network functions, protocols, standards, and programming tools.
5G / Telecom Protocols
AI / ML
Languages
Frameworks & Tools
Cloud & Infra
Frontend
Mobile
Featured Projects
A selection of technical projects spanning 5G core networks, AI/ML systems, protocol engineering, and mobile development.
Open5GS AI/ML Laboratory
Fully simulated 5G Standalone Core Network deployed on GCP, operated via Google Colab notebooks. Deploys all 7 core NFs (AMF/SMF/UPF/AUSF/UDM/PCF/NRF) with UERANSIM. Executes 8 labeled traffic scenarios for ML research including anomaly injection (scan, flood, Slowloris, exfiltration), handover simulation, PDU session lifecycle, QoS class comparison (5QI 1/8/9), and network slicing (SST 1/2/3). Includes full ETL pipeline and an iPhone IoT sensor (SeismoSense) feeding real accelerometer data over HTTP as an mMTC slice source. Key finding: documented the gtp5g kernel bypass that makes tcpdump/eBPF ineffective on Open5GS GTP-U data plane.
Open5GS NWDAF — C++ Reference Implementation
Production-grade, standalone C++ implementation of the Network Data Analytics Function (NWDAF) compliant with 3GPP TS 23.288 v17 and TS 29.520 v17. Implements all 7 analytics IDs (NF_LOAD, UE_MOBILITY, UE_COMMUNICATION, ABNORMAL_BEHAVIOUR, QoS_SUSTAINABILITY, SERVICE_EXPERIENCE, NETWORK_PERFORMANCE), an embedded Isolation Forest and EWMA predictor (no Python dependency), and the full TS 29.520 SBI REST API with subscription management. Packaged as a systemd service with React JSX real-time KPI dashboard and Catch2 unit tests.
Digital Twin–Based Root Cause Analysis Agent
Multi-agent cognitive AI system for automated Root Cause Analysis of 5G core network faults. Uses LangGraph StateGraph with Master Orchestrator + 3 domain-specialist agents (RAN Expert, 5G Core Expert, Security & Policy). Incorporates a Digital Twin simulator generating synthetic KPI telemetry for 13 fault signatures using statistical distributions, DTW-based fault matching across 15 weighted KPI metrics with Bayesian confidence scoring, FAISS RAG over 12+ 3GPP spec chunks, and LLM failover chain (Gemini-2.0-Flash → Gemini-1.5-Flash → AirLLM Llama-3.1-8B). Detects ROGUE_UE_ATTACK at 41.87% DTW confidence in under 3 minutes MTRCA.
Callflow Visualizer — Enhanced DPI
Enterprise-grade network packet analysis and visualization platform for telecom protocol analysis, ingesting PCAP files and correlating distributed 3GPP sessions. Implements 15+ protocol parsers in C++17 (SIP, RTP/RTCP, DIAMETER Gx/Gy/Rx/S6a, GTPv1/v2-C, PFCP, S1AP, X2AP, NGAP, NAS, HTTP/2 with HPACK decompression, SCTP, DNS) with session correlation across 20+ identifiers (IMSI, TEID, SEID, GUTI). Features D3.js ladder diagrams, WebSocket real-time streaming, JWT+RBAC security, and ~34,700 packets/second throughput.
From the Blog
Thoughts on telecom engineering, 5G, and data analytics.
An introduction to this blog and what you can expect — deep dives into 5G Core architecture, IMS design patterns, protocol analysis, and the intersection of telecom with data engineering....
Have a project in mind?
Whether you need 5G core expertise, AI/ML systems for telecom, or protocol-level engineering — I'd love to talk.