Torgyn Erland

I am a Machine Learning consultant and Data Scientist, specialising in Algorithmic Transparency and Explainable AI.

As part of QuantumBlack, I am helping organisations worldwide to tackle some of their toughest problems with the power of data and advanced analytics. I am trusted to design, implement, and deploy innovative Machine Learning systems that support – in a safe and open way – decision makers from CEOs to nurses alike.

My background is in Computer and Information Engineering. I come from a rural school in a post-Soviet country, where in early 00s power outages were getting in the way of learning coding and sub-zero indoor temperatures caused the ink in pens to freeze. From this position, I feel very privileged to be representing in this prestigious award all those dreamers in science and technology who had to break down language, geopolitical, socio-economic, gender and other identity barriers.

I never could have imagined that my strive for academic excellence would bring me this far along my dreams. While studying towards the Bachelors’ degree, I earned the title of “IT/Computer Science Undergraduate of the Year” in a UK nationwide competition. My alma-mater is Warwick, where I have won numerous accolades for “Outstanding Academic Performance”, as well as my involvement in frontline student initiatives, such as Green Gown Award for building one of the world’s largest DIY wind turbines on a university campus, or setting up a Machine Learning bootcamp for fellow students in our Australian partner university.

It was during research for my Ph.D in Applied Machine Learning that I began to appreciate the real-world impact that advanced analytics can have. I collaborated with the local NHS trust and a medical school in Oxford, deploying Machine Learning to assist doctors with clinical decision making, harnessing biomedical data to highlight which treatments would be most effective. This grew into a variety of applications, from modelling how likely kidney transplants were to be accepted or rejected, to prediction models for a patient’s risk of developing diabetes over ten years.

In 2016 I won McKinsey’s Next Generation Women Leaders award and founded an outreach initiative that aimed to inspire and enable rural schoolchildren to learn programming. Ever since, I view myself proudly as a teacher. I teach computers and humans to learn complex patters from simple observations and data. My personal dream is to empower talented underrepresented youth from developing world to become the future IT-professionals that would shape a more open, accessible, and creative technology sector.