Crafting elegant solutions across Full-Stack Development, UI/UX Design & AI-Powered Applications
IEEE published author with national competition finalist titles. Experienced in .NET, Angular, and AI-driven mobile applications. Passionate about building user-centric software with measurable impact.
I'm a Software Engineer and Researcher graduated from Mehmet Akif Ersoy University with a B.Sc. in Software Engineering. Currently pursuing an M.Sc. in Software Engineering (thesis track) at the same institution, deepening my expertise in research and advanced engineering.
I served as the Project Lead on a TÜBİTAK 2209-A state-funded R&D project, gaining hands-on leadership experience in team management, project planning, and IoT-based assistive technologies. My graduation project "BakteriCO" — an AI-powered bacterial colony counter — was published on Google Play and became a finalist in three national competitions.
I continuously develop my skills in full-stack web and mobile development, UI/UX design, and data-driven solutions. I actively participate in industry events and seek collaborative environments to maximize my contribution and growth.
Agile methodologies, team coordination
User-centered interfaces, design systems
Cross-platform apps, responsive design
Machine learning, computer vision
Technologies and tools I use to build modern, user-centric applications.
Award-winning projects combining AI, IoT, and full-stack engineering.
A mobile application leveraging YOLOv5 to automatically detect and count bacterial colonies on agar plates in real-time. Deployed on Google Play for microbiology researchers and lab technicians. Selected as a finalist in TEKNOFEST 2025, TÜBİTAK 2242, and HAYTEKFEST 2025.
An assistive IoT device built on ESP32 microcontroller designed to enhance daily mobility for visually impaired individuals. Equipped with distance sensors for obstacle detection (triggering haptic feedback via vibration motors) and humidity sensors for slippery surface alerts. The IoT-connected system enables real-time data collection and mobile device integration, allowing users to analyze environmental data for safer route planning. Developed with a focus on accessibility, low-cost hardware, and energy efficiency.
Professional roles across full-stack development and government R&D institutions.
ARCA Software
Promoted from intern to full-time Software Engineer at ARCA Software. Actively contributing to full-stack development using .NET and Angular, while specializing in UI/UX-driven application design and user experience optimization. Working within a dynamic, R&D-focused team that fosters continuous learning and technical growth.
ARCA Software
Supported full-stack application development with .NET and Angular. Designed user interfaces following UI/UX best practices and gained hands-on experience with Git version control and collaborative development workflows.
TÜBİTAK BİLGEM YTE (Scientific & Technological Research Council)
Completed a 30-day intensive software development internship at Turkey's premier scientific research institution. Received training in Java, Spring Boot, Kubernetes, Docker (backend) and React, HTML/CSS, JavaScript (frontend). Participated in a real-world project applying learned technologies in a team-based agile environment.
Nationally recognized programs and competitive milestones.
Ministry of Industry & Technology, Republic of Türkiye
Selected among the first 1,000 participants out of thousands of applicants nationwide.
Completed foundational training and advanced to the Top 120 cohort for specialized deep-dive modules.
A prestigious government-backed AI program conducted in partnership with leading Turkish tech companies including Arçelik, Baykar, HAVELSAN, Huawei, and TÜBİTAK. Covered deep learning, computer vision, NLP, and real-world AI deployment.
Peer-reviewed research in computer vision and IoT.
UBMK 2025 — 10th International Conference on Computer Science and Engineering
Developed a complete pipeline for detecting and counting small, overlapping bacterial colonies using YOLO architectures. Benchmarked YOLOv3-Tiny, YOLOv7-Tiny, YOLOv5, and YOLOv8-Small, achieving 96.1% mAP accuracy. Deployed the optimized model on mobile devices for real-time inference in microbiology laboratories.
Data Science Journal (Veri Bilimi) · October 2022
A comprehensive survey comparing leading LPWAN technologies — LoRa, Sigfox, and NB-IoT — across critical IoT criteria including range, power consumption, device capacity, and cost-effectiveness. Provides a decision framework for selecting the optimal technology for various IoT deployment scenarios.
Read Full PaperAcademic foundation and extracurricular involvement.
Mehmet Akif Ersoy University
Specialization in advanced research and engineering methodologies.
Mehmet Akif Ersoy University
Activities & Involvement:
I'm actively seeking opportunities in full-stack development, UI/UX engineering, and software project management at innovative companies. Let's connect and explore how I can contribute to your team.
Send Me an Emailmezgialtintas@gmail.com
