About me
Ph.D. student in Computer Science with a focus on Machine Learning. I am part of the Robotics and Perception Group (RPG), supervised by Professor Davide Scaramuzza (University of Zurich), and an Associated Researcher at the ETH AI Center. My research focuses on Sequence Modeling and Efficient Neural Network Architectures for Event-based Vision. Additionally, I explore Machine Learning Fundamentals, Dynamical Systems, Applied Mathematics, and Theoretical Computer Science. I am fascinated by anything connected to computation and mathematics; my papers blend theory and practical applications. If you have intriguing ideas for collaboration, feel free to reach out. You can also explore some of my recent works in the publications tab.
Before my Ph.D., I earned a Master's in Computer Science from the University of Novi Sad. During this time, I interned at the University of Cambridge under the supervision of Professor Pietro Liò.
What I'm excited about
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Sequence Modeling
Investigating both theoretical foundations and practical applications of sequence modeling, focusing on efficient architectures to handle long sequences. By leveraging dynamical systems, I aim to develop models that not only reduce complexity but also improve scalability for various applications.
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Applications
Developing general models that can be applied across diverse domains, including neuromorphic systems, event cameras, genomic data, time series analysis, and language modeling.
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Sports
I enjoy boxing, running, and powerlifting. Through physical activity, I maintain a balance of discipline, strength, and endurance that complements my academic and research efforts.
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Biohacking
A strong advocate for optimizing health and energy levels through biohacking techniques, I focus on nutrition, sleep, and fitness. These methods are aimed at improving cognitive function, performance, and overall well-being.
