Çağrı Eser

I am a Computer Vision and Machine Learning researcher with over five years of industrial experience in perception in autonomous systems. I completed my MSc in Computer Engineering at METU, where I also earned my BSc and a Minor in Mathematics. My thesis addressed class imbalance in long-tailed visual recognition, and my advisors were Sinan Kalkan and Emre Akbaş.

I am interested in computer vision, explainable machine learning, and multimodal representation learning. In particular, I greatly enjoy investigating representations of multiple modalities.

Selected Research

ICML2026 @ Workshop on Machine Learning for Audio

Evaluating Pretrained Music Embeddings for Cross-Performance Jazz Standard Recognition

Çağrı Eser

We evaluate the effectiveness of music embeddings from audio pretrained models on the challenging task of standard recognition from jazz performances, and suggest a lightweight contrastive adaptation for improving retrieval-based approaches.

[PDF] | [Code]

Neurocomputing 674 (2026) 132938

Intrinsic Dimensionality as a Model-Free Measure of Class Imbalance

Çağrı Eser, Zeynep Sonat Baltacı, Emre Akbaş, Sinan Kalkan

We propose an alternative perspective on imbalance in long-tailed datasets, focusing on the intrinsic dimensionalities of classes in image space rather than their cardinalities.

[PDF] | [Preprint] | [Code]

MSc thesis

Mitigating class imbalance in long-tailed visual recognition through the use of intrinsic dimensionality

Çağrı Eser

I concentrate on model-based and data-based definitions of intrinsic dimensionality and their relation to model performance, choice of architecture, choice of estimator and imbalance severity.

[PDF]

Other news

• August 2026 - Check out wordsim, a simple word guessing game based on semantic similarities of word representations for English and Turkish word embeddings.

• March 2026 - I’m serving as a reviewer for SIU2026.

• I’m serving as an adjunct lecturer for CENG240 for the Spring 2024 semester, a course for Programming with Python for Engineers.
  • Weekly course materials can be found here in the form of Jupyter notebooks.
• I have completed my MSc. degree in Computer Engineering at METU. I’d like to thank my supervisors Prof. Sinan Kalkan and Prof. Emre Akbaş for their continual guidance throughout my studies.
  • My thesis was about mitigating the effects of class imbalance in long-tailed visual recognition using intrinsic dimensionality. It can be accessed on OpenMETU through this link.
  • cGPA: 4.0/4.0