Mert Caglar
Ümit Mert Çağlar
PhD Candidate, Research and Teaching Assistant
Graduate School of Informatics
Middle East Technical University (METU), Ankara, Türkiye
📬 Contact & Links
| 🐙 GitHub: caglarmert | 💼 LinkedIn: mertcaglar | 🐳 Docker: mertcaglar |
|---|---|---|
| 📧 Email: mert.caglar [at] metu.edu.tr | 🆔 ORCID: 0000-0002-0391-3847 | 🌐 Homepage: METU AVESIS |
🔬 Research Profile
My research focus is on computer vision and generative models, specifically addressing critical challenges in data scarcity, volume, and quality in remote sensing or medical imaging.
- Data Scarcity & Generative Augmentation: I utilize Generative Adversarial Networks (GAN) and Denoising Diffusion Probabilistic Models (DDPM) to synthesize high-quality image data, evaluating their utility through extensive benchmarking and ablation studies.
- Geospatial & Earth Observation Benchmarks: I introduced two publicly available large-scale datasets:
- ARAS400k: A large-scale Remote sensing dataset Augmented with Synthetic data for segmentation and captioning.
- BELDE: Building a Large-scale Earth-observation Land-cover Dataset for Europe.
- Efficient Deep Learning: Developed LALE (Lightweight-transformer Architecture for Land-cover Estimation), an efficient dense segmentation model.
- Data Quality Metrics: My recent research addresses data quality metrics crucial for tracking synthetic data generation fidelity and downstream model utility.
🎓 Education
- PhD in Modelling and Simulation, Middle East Technical University 2022 — Present
- Ongoing Research: Vision-Language Data Augmentation and Lightweight Segmentation Models for Scalable Remote Sensing Image Analysis.
- MSc in Modelling and Simulation, Middle East Technical University 2019 — 2022
- Thesis: Improving Classification Performance of Endoscopic Images with Generative Data Augmentation.
- BSc in Electrical and Electronics Engineering, Middle East Technical University 2013 — 2018
💼 Experience
🏛️ Academic Experience (METU Graduate School of Informatics) 2024 — Present
Teaching Assistant, Transformers and Attention-Based Deep Networks
Research Assistant, Computer Vision and Deep Learning Laboratory
Researcher, Applied Intelligence Research Laboratory
✈️ Industrial Experience (TAI - Turkish Aerospace Industries) 2019 — 2023
Software Design, Data Science and Modelling
Reinforcement Learning, Aeronautical-Avionics Simulations
Technical Team Lead
📡 STM 2018 — 2018
RF and Simulation Systems Engineer
🏆 Awards & Accomplishments
2nd Place — ICIP Grand Challenge on Colorectal Cancer Tumor Grading and Segmentation (Out of 39 international teams) 2025
Best Poster Award — Graduate School of Informatics, 6th Open Research Day 2025
Special Mention — Graduate School of Informatics, 4th Open Research Day 2023
Best Poster Award — Graduate School of Informatics, 3rd Open Research Day 2022
🎓 Scholarships
TÜBİTAK 2211-A National Doctorate Scholarship 2022 — 2027
TEV (Turkish Education Foundation) Doctoral Scholarship 2024 — 2027
📚 Publications
(Full publication record available via ORCID and METU AVESIS)
- Grounding Synthetic Data Generation With Vision and Language Models, CVPR 2026 Synthetic Data for Computer Vision Workshop Paper
- LALE: Lightweight-Transformer Architecture for Land-Cover Estimation, Paper
- ARAS400k: A Large-Scale Remote Sensing Dataset Augmented with Synthetic Data for Segmentation and Captioning, Dataset
- Colorectal cancer segmentation with adaptive augmentation and multiresolution ensemble models, 18th International Conference on Machine Vision (ICMV 2025) Paper
- Progressive Disease Image Generation with Ordinal-Aware Diffusion Models, Diagnostics 2025 Paper
- Colorectal Cancer Tumor Grade Segmentation in Digital Histopathology Images: from GIGA to Mini Challenge, IEEE International Conference on Image Processing Workshops (ICIPW) 2025 Paper
- Class distance weighted cross entropy loss for classification of disease severity, Expert Systems with Applications 2025 Paper
- Ulcerative Colitis Mayo Endoscopic Scoring Classification with Active Learning and Generative Data Augmentation, IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2023) Paper
- Improving classification performance of endoscopic images with generative data augmentation, METU 2022 Thesis