I’m a data scientist with a deep-rooted passion for machine learning, Bayesian statistics, and the exciting world of large language models. My academic background in physics laid the foundation for a career where curiosity and a love for complex problem-solving are at the forefront.

A strongly Bayesian mindset has transformed my thinking, and my approach to complex problem solving. I have taken the lessons that i’ve learnt from studying this statistical framework and applied them across several projects that you can read about in this website, including a recent publication on the use of Bayesian inference in time series forecasting for highly stochastic, non-stationary, and non-gaussian processes.

Having worked extensively cross-domaine in data science, I have developed a diverse skill set, from producing production quality code, deployed on cloud compute infrastructure, to implementing various high-impact POC projects, to advocate for the power of data science innovation across various industries.

Through various projects, I have developed a strong grasp of image processing algorithms, pattern recognition, and the application of deep learning techniques like Convolutional Neural Networks (CNNs). My work in this area not only underscores my technical proficiency but also my ability to apply these skills to real-world problems, creating tangible improvements and demonstrating what can be possible with a data-centric approach.

Machine learning, and recent developments in generative modelling is another focus of mine. The capabilities of these models and their wide spread adoption has already begun to transform industries, and the potential in this space is only just beginning to be utilized. I’m constantly exploring new advancements in this field, staying ahead of the curve in a rapidly evolving landscape.

If you want to find out more about my work, please shoot me a message over on my Linkedin! or you can email me at adam.jaspan@googlemail.com