Rate My Professor Jukka Suomela

Jukka Suomela is Full Professor in the Department of Computer Science at Aalto University, having advanced through the ranks since joining in 2014 as Assistant Professor (2014–2020), then Associate Professor (2020–2026), and Full Professor from 2026. He serves as the professor in charge of the Computer Science major (Tietotekniikka) and minor in the Bachelor's program, leads the Distributed Algorithms research group, and supervises doctoral students. Prior to Aalto, he held a Postdoctoral Researcher position at the Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki (2009–2013). Suomela obtained his BSc and MSc degrees in Computer Science from the University of Helsinki in 2005, a PhD in Computer Science in 2009, and was appointed Docent in Computer Science in 2012, all from the University of Helsinki. His research focuses on the theoretical foundations of distributed and parallel computing, with particular emphasis on the concept of locality, distributed algorithms, local algorithms, parallel algorithms, graph algorithms, computational complexity, and computability.

Suomela has earned major accolades, including the FOCS 2019 Best Paper Award, DISC 2012 and 2017 Best Paper Awards, Algosensors 2008 Best Paper Award, Steven Krauwer Award for CLARIN Achievements (2024), and numerous teaching honors such as Teacher of the Year (2017), Best Large Course awards multiple times (2014–2023), and SCI Teaching Award (2019) at Aalto University. He chaired the program committees for DISC 2019 and SIROCCO 2016, served as local chair for ALGO 2018, was a council member of the European Association for Theoretical Computer Science (EATCS) (2015–2019, 2021–), and is vice chair of the DISC steering committee (2022–2024). Suomela has contributed to award committees for the Edsger W. Dijkstra Prize in Distributed Computing (2019, 2024) and others, and reviewed for numerous top journals and conferences including PODC, STOC, ICALP, and SODA. Key publications include "Distributed computation with local advice" (Balliu et al., DISC 2025), "Distributed Quantum Advantage for Local Problems" (Balliu et al., STOC 2025), "Local problems in trees across a wide range of distributed models" (Dhar et al., OPODIS 2024), and "Low-Bandwidth Matrix Multiplication: Faster Algorithms and More General Forms of Sparsity" (Gupta et al., SIROCCO 2025). He teaches courses such as Distributed Algorithms (CS-E4510), Programming Parallel Computers (CS-E4580), and Competitive Programming (CS-E4590).