Şehmus Yakut
Architecting AI Systems, Knowledge Graphs & Data Pipelines
I design production-ready Machine Learning models, automated ETL pipelines, and Graph-based RAG architectures. Experienced in computer vision for edge safety devices and medical graph databases.
Profile Overview
Data Engineer @ Doctor Follow
Building medical ETL pipelines & Neo4j Knowledge Graphs
Yıldız Technical University
B.S. in Computer Engineering (2020 - Jan 2026)
TÜBİTAK 2209-A
Motorcycle Blind Spot Detection
2 Papers Published
MDPI & Springer ICCSA
Featured Engineering Work
Engineering Projects
Systems and architectures I have designed, built, and documented.
TÜBİTAK 2209-A Blind Spot Detection & Warning System
Real-time computer vision and object detection warning system for motorcycle rider safety, funded by TÜBİTAK.
Funding Program
TÜBİTAK 2209-A
Core Technology
Edge Vision AI
Stress & Fatigue Detection via Facial Expression Recognition
Deep learning facial analysis using ViT and BEiT transformers to identify stress metrics. Official implementation of the ICCSA 2025 paper.
Model Architecture
ViT & BEiT
Benchmark Dataset
FERPlus Dataset
Alzheimer's Disease Classification using Deep Learning
Multi-class MRI scan neural classifier utilizing neuroimaging data to identify Cognitive Normal, MCI, and AD categories. Graduation project implementation.
Data Modality
Neuroimaging MRI
Diagnostic Classes
CN vs MCI vs AD
Travel Assistance: Multi-Language Smart Guide Application
A comprehensive travel assistance web application utilizing Next.js 15 and TypeScript, integrating Google Maps API to provide location-based services, travel tools, and safety alerts with multi-language support (English, Turkish, Kurdish).
Framework
Next.js 15 & TypeScript
Architecture
MVVM Pattern
MedAI: AI-Powered Clinical Assistant & Medicine Planner
Intelligent medicine management and clinical assistant application featuring study planners, OCR prescription scanner, and environment-configured persistent AI chat.
Target Platform
iOS & Android
AI Engine
Gemini Model
PharmAI: Intelligent Pharmacology Assistant
A Flutter mobile application designed to serve as a smart assistant in pharmaceutical study and reference environments.
Target Platform
Cross-Platform
Core Framework
Flutter SDK
Career Timeline
Professional Experience
Data Engineer
Doctor FollowIstanbul, Turkey•02.2026 - 05.2026
- ▸Develop and orchestrate automated ETL pipelines using Python to structure large-scale medical datasets for improved accessibility.
- ▸Optimize medical knowledge graphs (Neo4j) to enhance the retrieval speed and accuracy of RAG-based search applications.
- ▸Design structured data models to facilitate high-speed querying across complex, interconnected medical content nodes.
Network Technologies Intern
TurkcellIstanbul, Turkey•02.2025 - 04.2025
- ▸Automated routine network administration tasks using custom Python scripts to improve structural efficiency.
- ▸Monitored and supported core network deployments, verifying topology parameters.
- ▸Implemented test automation scripts and collaborated on network topology design modifications.
- ▸Enhanced troubleshooting speed and improved overall network reliability.
Mobile Developer (part-time)
Spor SepetiIstanbul, Turkey•03.2024 - 10.2024
- ▸Co-developed the cross-platform SPORSEPETI.app mobile application, focusing on real-time data synchronization.
- ▸Implemented robust backend data schemas, API integration gates, and dynamic RESTful controllers in Dart.
- ▸Managed live stream feeds and state containers, ensuring high performance and responsive client views.
Technical Competency
Tools & Technologies
Languages & Databases
Data Engineering & Ops
AI & Machine Learning
Tools & Analysis
Infrastructure Contributions
Peer-Reviewed Research
Publications
A Multimodal Transformer-Based Framework for Emotion Analysis in Multilingual Video Content
Analyzing emotions in multilingual video content is challenging due to acoustic variations, linguistic expressions, and diverse visual cues. We introduce a multimodal transformer framework designed to fuse acoustic embeddings, visual features, and textual semantic cues, yielding robust emotion classification profiles across multiple language structures.
Authors: Yakut, S., Tuten, Y. T., Caglar, E., Aktas, M. S.
Facial Stress and Fatigue Recognition via Emotion Weighting: A Deep Learning Approach
This research proposes a deep learning model for detecting facial stress and fatigue metrics. By integrating emotion weighting coefficients on visual expressions, we improve the identification threshold of fatigued states under variable industrial environments, outperforming standard baseline classification pipelines.
Authors: Oskooei, A. R., Caglar, E., Yakut, S., Tuten, Y. T., Aktas, M. S.
Supervisor Recommendations
Professional References
"Supervised and mentored Şehmus during his internship at Turkcell, where he contributed to network automation, troubleshooting, and performance monitoring tasks."
İbrahim Karpuz
Senior Network & Security Engineer, Turkcell
karpuz.ibrahim@turkcell.com.tr
"Worked closely with Şehmus during his internship and subsequent freelance collaboration at SPORSEPETI, where we co-developed mobile application backend infrastructure, feature integration, and performance optimization."
Ahmad Khawatmi
iOS Engineer (HaCon) | Co-Founder, SPORSEPETI.app
ak93x.work@gmail.com
Let's Discuss AI & Data Engineering
Based in İstanbul, Turkey. Available for machine learning engineering, data pipeline architecture, and GenAI RAG system development.