Assistant Professor at the University of Edinburgh Business School
Welcome to my world, where ancient philosophy meets modern science, fueling a lifelong learning journey and a pursuit of excellence. Collaborating with leading academics, visionary CEOs, and prominent professionals, I navigate the intricate tapestry of data using versatile and practical methods that consistently deliver impactful results.
The whole is greater than the sum of its parts, particularly in today's ultra-connected world. Examining the causal interdependencies among the components of complex systems offers a dual advantage. On one hand, it helps one understand why the system operated in specific ways in the past. On the other hand, it enables one to predict potential future states in an explainable manner. This is why causality is an ever-present aspect of my research.
Non-linearities in data, ranging from weather measurements to financial asset prices, are the norm. This makes mainstream linear methods unsuitable for real-world systems. Chaos theory, on the other hand, provides scientists with an assortment of assumption-agnostic frameworks. Within these, I have discovered timeless teachings that unlock untapped potential in the data.
Patterns emerge in nature and society, spanning from the microcosm to the macrocosm. Some patterns are universal, like the orbiting components in solar systems and atoms, while others are unique to specific systems, such as singularities. Hidden patterns, in particular, offer decision-makers distinct perspectives, revealing unexplored courses of action and providing them with a competitive edge. Uncovering hidden patterns is at the core of the frameworks I create.