Merkebu G.

Holds a PhD in Computer Science (Ghent University) focusing on optimization of wireless systems and AI/ML. Experienced in design and optimization of wireless systems (4G/5G (3GPP), Wi-Fi(IEEE 802.11), software-defined radio systems, digital signal processing, algorithm development, AI model training, data analysis, and project management. Skilled in Python, C/C++, and TensorFlow, with hands-on expertise in automation, technical tool development, and machine learning applications. Proven ability to contribute to interdisciplinary research projects, develop scalable software solutions, and work with diverse teams across academia and industry. Experienced in creating technical documentation, performance analysis tools, and training content for AI platforms. Strong background in system integration, scripting, and experiment-driven problem solving. Proficient in Machine Learning/AI, Python, and C/C++. # What I do: • Wireless systems & DSP: link- and system-level modeling, PHY/MAC algorithm design, KPI analysis (RSRP/RSRQ/SINR, latency, throughput), coverage/heatmap tooling, performance evaluation. • SDR prototyping: end-to-end builds with USRP/FPGA; experiments on srsRAN, OpenAirInterface. • AI/ML for comms: feature engineering (FFT/IQ pipelines), classification models, federated/reinforcement learning, model training/evaluation in TensorFlow & PyTorch. • Automation & data tooling: Python pipelines for data labeling, parsing, and visualization (e.g., Grafana), experiment orchestration, and reproducible research assets. • Technical content: research-grade writing, specs, API docs, tutorials, grant proposals, MCQs/exams, and training content for AI platforms. # Selected outcomes: • ML-based preprocessing for signal-type identification that improved classification accuracy (FFT-driven pipeline in Python/TensorFlow). • Federated learning–based spectrum sensing that dramatically reduced data transfer needs during training while maintaining model performance (PyTorch). • Dynamic spectrum-sharing research across 4G/5G that increased spectrum-utilization efficiency, validated via simulation and analysis. • Robust post-processing/visualization tools for drive-test data, enabling faster KPI reporting and decision-making. # Technical content & documentation: • Experienced technical content writer with a strong background in implementing solutions and producing detailed reports for large-scale research initiatives. • Skilled in authoring original research articles, technical documentation, grant proposals, and in disseminating scientific findings. • Comfortable translating complex DSP/communications and AI concepts into clear, accurate materials for engineers, researchers, and non-technical stakeholders alike. # Toolbox: • Python, C/C++, MATLAB • TensorFlow, PyTorch • Linux, shell scripting, Git • SDR (USRP), FPGA integration • srsRAN, OpenAirInterface, openwifi • Grafana • Data labeling/QA workflows # Collaboration: I’m available for consulting, scoped research/prototyping, algorithm development, KPI analysis/reporting, automation tooling, and technical writing.