Experience

  1. Postdoctoral Researcher

    Genome Institute of Singapore, A*STAR
    • Demonstrated that genomic foundation models behave fundamentally differently from text LLMs via entropy analysis, questioning the value of DNA pretraining; will be presented at ICLR - Learning Meaningful Representations of Life workshop 2026: arXiv

  2. Senior Research Officer

    Genome Institute of Singapore, A*STAR
    • Developed GNNome, a GNN-based de novo genome assembler representing a new paradigm for the field; achieved 20% improvement in NG50 and NGA50 over SOTA on human genome with comparable results across three other species; published in Genome Research 2025.
    • Contributed to the first de novo assembly of an Indian reference genome, providing a valuable genomic resource for the South Asian population: bioRxiv
    • Lectured at the ASTAR/NTU AI + Computational Genomics course covering deep learning and genome assembly

  3. Intern (ARAP Scholarship Awardee)

    Genome Institute of Singapore, A*STAR
    • Pioneered neural algorithmic reasoning approaches to de novo genome assembly; presented at NeurIPS - Learning Meets Combinatorial Algorithms workshop 2020: arXiv
    • Developed a CNN-based classifier for long read type classification, achieving competitive accuracy across multiple classes

  4. Research and Teaching Assistant

    Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia
    • Taught introductory Programming and Data Science courses

Education

  1. PhD in Computer Science

    University of Zagreb, Croatia
    Developed GNNome – a novel approach to de novo genome assembly based on graph representation learning. Supervised by Mile Šikić and Xavier Bresson. Presented my work at a NeurIPS and ICML workshops and published it in Genome Research.
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  2. BSc Computer Science

    University of Zagreb, Croatia

    GPA: 4.6/5.0

    To get a deeper understanding of Computer Science, and particularly AI, I enrolled into a Bachelor’s CS program. For my Bachelor’s thesis, I worked on developing a DNA sequence polishing tool based on convolutional neural networks (CNNs). Supervised by Mile Šikić. My desire to learn more about fundamentals of CS led to a funny situation where, during the 2018/2019 academic year, I was simultaneously a Bachelor’s and a PhD student at the same department!

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  3. Integrated BSc and MSc in Physics

    University of Zagreb, Croatia

    GPA: 4.9/5.0

    Award: summa cum laude (highest honors)

    For my Master’s thesis, I worked on machine learning applications in solid-state and statistical physics. Supervised by Vinko Zlatić and Ivor Lončarić.

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