İlagü(l) Erol Belper
Computer Engineer focused on backend engineering, distributed systems, and AI-driven applications. I graduated first in both my faculty and department, finishing my bachelor’s degree one year ahead of schedule.
About
Computer Engineer focused on backend engineering, distributed systems, and AI-driven applications. I graduated first in both my faculty and department, finishing my bachelor’s degree one year ahead of schedule. I build scalable microservice architectures and production-ready APIs, and I enjoy solving real-world problems with machine learning and multilingual NLP.
I have experience developing deep learning models (e.g., real-time drone speech enhancement) and building AI-enabled multilingual semantic search and recommendation systems. I also worked on analytics and NLP pipelines to identify high-demand technical skills from job postings.
- 1 year's experience
- Joined July 2026
Skills· 23
Languages
- TurkishFluent
- EnglishFluent
- GermanAdvanced
Industry experience
- Software & Internet
- Computers & Electronics
- Education
- Professional Services
- Retail
Work experience· 11 roles
Built an AI-powered multilingual semantic retrieval system supporting Turkish, French, and English product search. Integrated neural machine translation and sentence embedding models to improve cross-language semantic retrieval accuracy. Evaluated the system on datasets containing over 44,000 products using Top-1 Accuracy, Precision@5, and Mean Reciprocal Rank (MRR).
Developed a deep learning model for real-time speech enhancement by suppressing drone ego-noise while preserving surrounding environmental sounds. Designed a hybrid neural architecture combining frequency-wise Transformers, Temporal Convolutional Networks (TCN), and sub-band feature fusion. Built an end-to-end training and evaluation pipeline including custom dataset generation, augmentation, and objective speech quality assessment.
Developed a deep learning model for real-time speech enhancement by suppressing drone ego-noise while preserving surrounding environmental sounds. Designed a hybrid neural architecture combining frequency-wise Transformers, Temporal Convolutional Networks (TCN), and sub-band feature fusion. Built an end-to-end training and evaluation pipeline including custom dataset generation, augmentation, and objective speech quality assessment. Presented the work at the 8th Bilsel International Harput Scientific Research Congress.
Education· 12
Certifications and awards
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