Research

Research Direction

I work at the intersection of computer vision, medical image analysis, and multimodal learning. My goal is to develop intelligent systems that can understand and reason about complex visual and multimodal information, with applications in clinical decision support and beyond.

Research Statement

My research focuses on developing intelligent learning systems capable of understanding complex visual and multimodal information. I am particularly interested in applying deep learning and representation learning to challenging problems in computer vision and medical image analysis, while also exploring the capabilities, limitations, and interpretability of large multimodal models.

A central theme in my work is the interplay between visual perception and language understanding. Vision-language models offer a promising path toward more general AI systems, but their robustness, interpretability, and reliability in safety-critical domains such as medical imaging remain open challenges. I aim to contribute to addressing these challenges through rigorous empirical and methodological research.

As an incoming MSc student at the University of Bonn, I plan to deepen my work in representation learning, explainable AI, and multimodal reasoning, with the goal of pursuing a long-term academic research career.

Research Ecosystem

AI Research
Computer Vision
Medical Image Analysis
Multimodal Learning
Vision-Language Models
Large Language Models
Research Interests

Areas of Focus

My research interests span several interconnected domains within artificial intelligence.

Computer Vision

Developing deep learning systems that can understand, analyze, and interpret visual information across diverse domains.

Medical Image Analysis

Applying AI to medical imaging problems including segmentation, classification, diagnosis, and clinical decision support.

Vision-Language Models

Investigating multimodal models that bridge visual and linguistic understanding for richer AI capabilities.

Multimodal AI

Building systems capable of learning from multiple modalities such as images, text, and structured data.

Large Language Models

Exploring language models, instruction tuning, retrieval, and the foundations of language understanding.

Machine Learning

Developing robust and generalizable machine learning systems with strong theoretical grounding.

Current Focus

Computer Vision
Medical AI
Multimodal Learning

Broader Research Interests

Vision-Language Models
Medical Image Analysis
Representation Learning
Large Language Models
Projects

Research Projects

Ongoing and completed research projects that illustrate my research direction.