About me
I am a Ph.D. student with the Robotics and Perception Group (RPG), supervised by Professor Davide Scaramuzza
(University of Zurich) and Associated Researcher at ETH AI Center. My research focuses on Sequence Modeling and Efficient Neural Network Architectures for Event-based Vision.
Incorporating sequence modeling into event-based vision systems promises to significantly enhance the temporal resolution and predictive accuracy of these networks, paving the way for breakthroughs in dynamic environments where rapid and precise visual processing is crucial, such as in advanced robotics and real-time surveillance.
Before my Ph.D., I obtained a Master's Degree in Computer Science from University of Novi Sad while interning at the University of Cambridge under the supervision of Professor Pietro Lio.
What I'm excited about
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Sequence Modeling
Investigating alternative neural network architectures that offer a solution to the quadratic complexity issue inherent in Transformer models as sequence length increases.
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Event-based Vision
Applying sequence modeling and efficient neural network architectures to computer vision systems utilizing event cameras, known for their efficiency in dynamic and high-speed scenarios.
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Sports
I enjoy challenging myself with a variety of physical activities, such as boxing, engaging in CrossFit workouts, and dedicated fitness training sessions.
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Biohacking
Enthusiastic about nutrition and biohacking to enhance personal energy levels and overall well-being.
