Professor Milan Vojnović

Milan Vojnović’s research focuses on machine learning and optimisation, involving the development of novel algorithms and the analysis of their theoretical guarantees to support the design of efficient intelligent systems. He has made significant contributions to scalable optimisation methods for machine learning, multi-armed bandits, multi-agent systems, algorithms under uncertainty, game theory, and network system control and optimisation. His work has been applied across a variety of domains, including online platforms, computer networks, and machine learning systems.

He has received several best paper awards at leading conferences, as well as the ACM SIGMETRICS Rising Star Researcher Award and the ERCIM Cor Baayen Award. He is also the author of Contest Theory, published by Cambridge University Press in 2016.

Milan has held a visiting scientist position at Meta. Prior to joining LSE, he spent 13 years as a researcher at Microsoft Research, working on a wide range of projects. He also held a two-year appointment as an affiliated lecturer at the Statistical Laboratory, University of Cambridge. He was awarded his PhD in 2003 by the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.

Milan Vojnovic’s research is in the area of machine learning and statistical inference. This involves developing new algorithms and establishing their performance guarantees to enable design of efficient intelligent systems. In particular, he worked in the areas of scalable optimisation methods for machine learning, multi-armed bandits, multi-agent systems, algorithms and uncertainty, and network system control and optimisation. His work has applications in several different areas, including online platforms, computer networks, and systems for machine learning.

His contributions to research have earned him recognition, including the 2010 ACM Sigmetrics Rising Star Researcher and the ERCIM Cor Baayen Award. Additionally, he received best paper awards at IEEE IWQoS 2007, IEEE Infocom 2005, ACM Sigmetrics 2005, and ITC 2001 for papers co-authored with various authors. His research is supported by a Facebook Research Award (2020), a Criteo Faculty Research Award (2018), and a Huawai Research Grant (2018).