About me

Hello! I’m a Master’s student in Machine Learning at the University of Tübingen, supported by an ELIZA Research-Oriented Master’s Scholarship. My research interests are in representation learning, trustworthy AI, and NeuroAI.

My current work includes causal interventions in vision-language models for studying neural representations at EPFL’s NeuroAI Lab, and self-supervised audio-visual representation learning at Tübingen with Professor Hilde Kuehne and Edson Araujo. Other work includes FairSSL, developed with Professor Sinan Kalkan, Dr. Jiaee Cheong, and Cambridge AFAR, on fair multimodal self-supervised learning for neurological data.

News

  • Aug 2026

    I started my research internship at EPFL's NeuroAI Lab.

  • Jul 2026

    I attended ICML 2026 in Seoul, South Korea.

  • Apr 2026

    My shared first-author paper, FairSSL: Fair Multimodal Self-Supervised Learning, was accepted to ICML 2026.

  • Jan 2026

    I was awarded a Summer@EPFL fellowship to join the NeuroAI Lab at EPFL.

  • Oct 2025

    I started my M.Sc. studies in Machine Learning at the University of Tübingen.

  • Sep 2025

    I was awarded ELIZA's Research-Oriented Master's Scholarship, fully funding my Master's studies at the University of Tübingen.

  • Jul 2025

    I graduated from Middle East Technical University with a major in Statistics and minor in Mathematics, ranked 2/140 among graduating Statistics students.

  • Aug 2024

    I received METU's 100% international students' tuition fee payment scholarship for the third time for my senior year.

Daniel lewis
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Notes and Slides

Hosted on GitHub Pages. Modified from the
original theme by codewithsadee.

Resume

Full curriculum vitae View CV [PDF]

Education

  1. University of Tübingen

    October 2025 to Present · [Transcript]

    Master of Science in Machine Learning (German GPA: 1.09/1.00, WES U.S. equivalent: 4.00/4.00)

    Studies fully funded by ELIZA's Research-Oriented Master's Scholarship.

  2. Middle East Technical University

    October 2020 to July 2025 · [Transcript]
    Major in Statistics & Minor in Mathematics
    CGPA: 3.91/4.00, Rank 2/140.
     
    Graduate Coursework: Probability Theory, Probabilistic Programming, Probabilistic Models of Cognition, Deep Learning (year long), Computational Semantics and Syntax (year long)
    Graduated with a total of 367 ECTS Credits.

Research Experience

  1. EPFL, NeuroAI Lab | Research Intern

    Aug 2026 to Present · Advisors: Yingtian Tang, Professor Martin Schrimpf
    • Working on causal intervention methods for controlling representations in VLMs for neural scientific discovery.
    • Linking model representations and interventions to human neural responses and comparing representations in deep networks with those in humans.

  2. University of Tübingen, CVML Group | Research Assistant

    Apr 2026 to Present · Advisors: Professor Hilde Kuehne, Edson Araujo
    • Developing JEPA-based multimodal alignment methods for self-supervised audio-visual representation learning.

  3. METU ImageLab & Cambridge AFAR | Research Assistant

    Aug 2024 to Sep 2026 · Advisors: Dr. Jiaee Cheong, Professor Sinan Kalkan
    • Designed and implemented FairSSL, a self-supervised loss for modality agnostic, fair multimodal representation learning tasks for neurological datasets (Joint work with Cambridge Affective Intelligence and Robotics Lab).
    • Worked on model de-biasing strategies at the intersection of deep learning and kernel methods for fairness.

  4. METU | Undergraduate Researcher

    Feb 2024 to Jan 2025 · Advisor: Professor Barbaros Yet
    • Worked on causal agent-based models of decision theory in a medical shared decision-making setup.
    • Modeled the conversation strategies employed by patients and doctors as a language game, consisting of various states, utilities, costs, and rewards.

  5. METU | Undergraduate Researcher

    Jul 2023 to Jan 2024 · Advisor: Professor İlkay Ulusoy
    • Utilized Gaussian mixture models to cluster the Inter-Subject Correlation features in fMRI and extract the segmentation map for the brain's activity region.
    • Worked on Dynamic Bayesian Networks developed from fMRI images to compare Alzheimer's vs Normal Brain region connectivity.

Selected Technical Projects

  1. GenVariableElimination.jl [Repo]

    Extended the experimental variable elimination library of Gen.jl probabilistic programming system (GenVariableElimination.jl) with a JAX einsum backend for scalable factor-graph contraction on GPUs, preserving modeling interface and semantics across large models with over 10x speedup on specific tests.

  2. Bayesian Normalization Layers Reproduction [Repo]

    Implemented and reproduced the results of Bayesian Normalization Layers (BNL), CVPR 2024, contributing to the field as no implementation was available for this paper.

Teaching

  1. Student Teaching Assistant (Course Instructor: Zeynep Işıl Kalaylıoğlu)

    2022-2023 academic year

    I was the student assistant for upper devision theoretical courses, Mathematical Statistics I (STAT 303) and Mathematical Statistics II (STAT 304). I led office hours for over 100 students and provided weekly individualized support and guidance on course material and problem-solving. ▶ Keywords: Theory of Statistical Inference, Theory of Estimation, Bayesian Inference

Publications

  1. Jiaee Cheong*, Abtin Mogharabin*, Paul Liang, Hatice Gunes, Sinan Kalkan (2026), FairSSL: Fair multimodal self-supervised learningAccepted to ICML 2026 Proceedings [PDF]

  2. Abtin Mogharabin, Vilda Purutçuoğlu. (2025), A Network Analysis of Family Dynamics, Linguistic Influences, and Happiness in TurkeyJournal of Science: Engineering and Innovation, Gazi University, Part A, 12(3), 918-934 [PDF]

  3. Abtin Mogharabin. (2024), Modeling Emotional Functions in Medical Shared Decision-MakingPreprint [PDF]

*Equal Contribution

Contact

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