Advice on Complex Systems, Network Science, Data Science and product development
A theoretical physicist at his core, Suresh is a renowned leader in the fields of Data Science, Customer Intelligence and Marketing Analytics. His broad and deep understanding across science, computing and technology has enabled him to motivate and coordinate diverse teams to generate innovation in these fields.
Suresh's research interests are in complexity theory, network science and statistical mechanics. He has carried over concepts and methodologies from these theoretical domains to frame and solve problems in the practical world. For example, inspired by ant foraging he designed self-organising algorithms for network routing (Nortel Networks) and distributed computing (ByCast, acquired by NetApp); and distilled the complexity of online gaming ecosystems to simpler, multi-agent environments.
During his tenure as Head of Customer Analytics & Insights (Europe) at eBay, Suresh disrupted the world of marketing attribution. He demonstrated, as in science, that multiple (dynamic) models were required to have understanding at different granularities: that prediction and insights are not always compatible. Later, as Director of Data Science at ProSiebenSat.1 he expanded his research in marketing and media analytics, generating time-dependent insights not present in stock models. More recently, as the lead for the Data Science & Intelligence Program at Microsoft To-Do, his teams have been using task classification and queuing models to develop product features around task organisation and recommendation.
Suresh holds a Mathematical Physics degree from Queen's University (Kingston), followed by MSc research in Theoretical Physics/Complex Systems at UBC (Vancouver) and a PhD (cand.) at ETH Zurich.