Advisory Board

Alison B. Lowndes

Alison B. Lowndes is Advisor to the General AI Challenge at GoodAI Applied, Founding team member of the Frontier Development Lab at NASA, Founder Trustee and Social Media Strategist at AVIF, and Artificial Intelligence DevRel | EMEA at NVIDIA. She is responsible for NVIDIA’s Artificial Intelligence Developer Relations in the EMEA region. She is a graduate in Artificial Intelligence combining technical and theoretical computer science with a physics background. After researching image & feature recognition using GPUs and deep learning at the University of Leeds, she joined NVIDIA as a Deep Learning Solutions Architect.

Alison consults on a wide range of AI applications, including Planetary Defense with NASA. As AI DevRel, she stays knowledgeable in state of the art across all areas of research and advises, teaches, and evangelizes NVIDIA’s platform, around the globe.

After first joining NVIDIA in 2015, the first thing she achieved was helping to establish the Frontier Development Lab, a staggering number of fascinating minds all working together to harness AI for the good of humankind.

She was a trainer for the new UK Computing Curriculum. This program is intended to teach children to code. As a result of the connections she initiated during talks with Kiambu County, rural Kenya set up IT code clubs in May 2015.

On account of Alison’s achievements in a career field that garners few women, two impressive articles were published about her. Alison B. Lowndes, Artificial Intelligence Developer Relations at NVIDIA, written by Gabriela Motroc and Women on Top in Tech Alison B. Lowndes, Artificial Intelligence Developer Relations at NVIDIA, Founding Team Member of NASA Frontier Development Lab, and a Founder Trustee of AVIF, which appeared in The Asian Entrepreneur written by Marion Neubronner.

She has given many keynote and public speeches which include Fuelling the AI Revolution with Gaming, Fuelling the Artificial Intelligence revolution with gaming!, NVIDIA Deep Learning Platform Update, and CogX 2018 — AI and the Road to AGI. View a complete list of Alison’s recorded speeches.

In addition to public speaking, she has authored the book Deep Learning with GPUs: For the beginner and the research paper Deep Learning with GPU Technology for Image & Feature Recognition.

She earned a BSc in Artificial Intelligence in 2015 from the University of Leeds. She studied cooperative phenomena in nature; emergence, self-organization, and embodiment; genetic algorithms; swarm intelligence; biological and artificial neural networks; clustering, dimensionality reduction; and bioinformatics.



  • Granted support from NVIDIA towards her final year project on deep learning with GPUs (given a TESLA K40 card and access to K80s).
  • 2nd time poster Finalist & Google-sponsored Attendee at the British Computer Society Women’s “Lovelace Colloquium” at the University of Edinburgh.


  • Won a £500 Award from the Leeds Foundation for Life towards costs to visit a community in Greenland to forge links with her charity work.
  • Scrum-mastered a 6px software dev project for a cinema booking system using Java and Swing pulling in data from the Rotten Tomatoes API [non-live].


  • Internship with National Nuclear Laboratory presentation:
  • Poster Finalist & Google-sponsored Attendee at the British Computer Society Women’s “Lovelace Colloquium” at Nottingham University.


  • IEEE Women in Engineering and Student Member #92441196.
  • Coordinated/liaised/attended a meeting between her organization and an Amazonian conservation organization from northern Brazil, in Nairobi, with the Kenyan Minister for the Environment to discuss proactive steps for the Rio Summit towards reforestation of Kenya and its geological significance to Brazil.

Alison’s superpower is “Having a universal view of a problem with a talent for synthesis. I may not be capable of solving every aspect but I’ll know someone who can”.

Alison said, “Since 2006 when Geoffrey Hinton optimized deep-learning algorithms and when these were massively accelerated a few years later by Andrew Ng porting them to GPUs, a perfect storm of parallel computation, bigger data, and deeper algorithms have converged to create the powerhouse that is today’s AI. And AI will keep improving. I am excited by what happened after IBM’s Deep Blue beat Garry Kasparov in 1997. More and more people started to master chess augmented by AI. If AI can help humans become better chess players, it can help us become better at anything.”

“AI will help us define what it is to be human, helping us to specialize our individual talents, augmented by the sheer focus of AI, leaving us to continue creatively thinking about all things an AI can’t. I want to be part of that movement. My final year project was an empirical study on the use of convolutional and recurrent neural networks, supported by NVIDIA’s GPUs, for medical image (CT) feature recognition. As a result, I now have high-level state-of-the-art knowledge on this field and in GPU programming (CUDA) with a fuller understanding of chip design and parallel computing”.

View her Facebook page and her Flickr photostream. Read her Google+ profile and her LinkedIn profile. Follow her Twitter feed. Visit her company website.