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Mustafa Orçun UÇGUN

@mustafaorunugun

Computer Engineering student at Istanbul Technical University; co-authored a Springer-published GAT model for football outcome prediction.

Turkey

Message

At Istanbul Technical University, I co-designed TSW-GAT, a dual-graph model for predicting football match outcomes. Published at ISACE 2026 in Springer LNCS, it outperformed a cumulative-GAT baseline and demonstrated zero-shot generalization across four unseen leagues.

At BAYKAR, I benchmarked nine pretrained vision backbones under a matched multi-task protocol and documented 23 experiments. I also developed a deterministic UAV swarm simulation and validated its flight envelopes across 208 automated tests.

At TURKCELL, I developed an XGBoost time-series forecasting model that reduced forecast error by 22% against linear-regression baselines. I’ve also built backend and deployment systems, including a RESTful image-classification API at Apidon and an agentic financial-analytics project that reached the KKB Hackathon finals.

Experience

Work history, roles, and key accomplishments

Current

Undergraduate Research Assistant

Current

Istanbul Technical University

Oct 2025 - Present (1 year 1 month)

Co-designed TSW-GAT, a dual-graph architecture for real-time football match outcome prediction, outperforming baselines and demonstrating zero-shot cross-league generalization. Applied gradient-based interpretability and ran grid searches over window parameters.

graph neural networks GAT PyTorch Geometric GNN Research Model Interpretability Grad CAM Time Series Analysis

Advanced Autonomy Intern

Baykar

Aug 2026 - Sep 2026 (1 month)

Developed a deterministic swarm formation simulation in Python for Bayraktar TB2 UAVs, modeling 3-DOF point-mass dynamics and a virtual-leader architecture. Designed a collision avoidance layer with rule-based control for 13 contingency scenarios, achieving zero safety violations across 208 automated tests.

Python Simulation Control Systems Collision Avoidance RK4 Virtual Leader Architecture

Computer Vision Intern

Baykar

Jun 2026 - Aug 2026 (2 months)

Benchmarked nine pretrained backbones on a shared multi-task head, holding architecture, data, and training schedule fixed. Found that adaptation gain is inversely related to frozen-feature quality and isolated object detection as feature-bound through ablations.

Computer Vision PyTorch DinoV2 CLIP MAE SAM I JEPA DeiT ResNet50 LoRAs multi task learning Ablation Studies

Digital Twin & Simulation Developer

ITU DATABEES

Nov 2025 - Jun 2026 (7 months)

Designed a thread-safe, event-driven architecture using asynchronous programming to process 500+ data packets per second without UI latency. Implemented MQTT protocols for real-time synchronization and optimized GPU throughput in Unity via compute shaders.

Unity C#MQTT Asynchronous Programming ComputeShaders IoT Digital Twin GPU Optimization

Machine Learning Intern

Turkcell

Jul 2025 - Aug 2025 (1 month)

Developed an XGBoost time-series forecasting model that reduced forecast error by 22% relative to linear regression baselines. Engineered 10+ calendar-driven features and built automated Python data pipelines for outlier detection and cleaning.

XGBoost Time series Forecasting Feature Engineering Python Data Pipelines Anomaly Detection

Co-Founder & Software Architect

Apidon

Nov 2023 - Jul 2024 (8 months)

Built a Classification API supporting remote image processing and dynamic model deployment via RESTful endpoints, with seamless switching between PyTorch and TensorFlow pipelines. Deployed infrastructure with Docker and Nginx, reaching the finals of a nationwide startup competition.

REST APIs PyTorch TensorFlow Docker Nginx SSL TLS Software Architecture

Education

Degrees, certifications, and relevant coursework

Istanbul Technical University

B.Sc., Computer Engineering

2023 -

Grade: 3.33/4.00

B.Sc. in Computer Engineering with a GPA of 3.33/4.00, including High Honor List in the last two semesters. Relevant coursework includes Learning from Data, AI Accelerators Lab, and Probability and Statistics.