I am broadly interested in theoretical computer science, with a focus on the principles of distributed computing and graph theory. I am most proud of my work on universal optimality which provides a near-complete theoretical answer to the fundamental question of: "how fast can we solve global problems like the shortest path or the minimum spanning tree in a distributed network?" My coauthors and I design distributed algorithms that perfectly (and provably so) adapt to the underlying communication network. This includes quantifying the fundamental speed limits of coordination in a network, as well as matching those limits with ultra-fast algorithms designed with user-friendly tools.
This pursuit has led to uncovering of new connections between distributed computing and many seemingly-unrelated fields of theoretical computer science: including the theory of metric embedding, information theory, parallel graph algorithms, and optimal oblivious packet routing. Notably, these connections have proven to be mutually beneficial and have led to breakthroughs on both sides.
Short BiographyI am a research scientist at Google Research in Zürich.
Previously, I was a postdoctoctoral scholar at ETH Zürich, in the research group of Prof. Mohsen Ghaffari (now at MIT). I received my Ph.D. from the School of Computer Science at Carnegie Mellon University under the advisorship of Prof. Bernhard Haeupler with the thesis titled Towards Universal Optimality in Distributed Optimization. Earlier, I obtained my B.Sc. and M.Sc. from University of Zagreb under the advisorship of Prof. Mile Šikić. I like competitive programming and playing volleyball.
I am extremely honored to have received the 2021 ACM-EATCS Principles of Distributed Computing Doctoral Dissertation Award (see here and here). Earlier, I was also awarded the 2018 DFINITY Scholarship.Links:
|my CV||my fledgling blog (updated Feb'23)|
Publications (ⓐ = authors sorted alphabetically; ⓒ = sorted by contribution; ⓡ = order randomized)