JT Turner

JT Turner began his computer science research career in 2013, in the resurgent era of neural networks and deep learning. His early research prior to joining Knexus included use of stacked Boltzmann machines/autoencoders for detection of seizures in children, and fine tuning convolutional architectures for faster, more accurate object detection. At Knexus his PhD work was in using context and non target pixels to further push towards realtime accurate detection, and discovery of novel objects.

JT has published 20+ works in academic journals, conference in proceedings, and stays recent with the newest trends and technology in AI and Machine Learning, as well as one international patent. JT has presented his work internationally in Canada and Sweden, and served as a paper reviewer for various AAAI workshops.

JT’s current work and research is on best practices in using generative AI to solve a wide array of problems, ranging from textual summarization, scenario generation, information extraction, and image creation via stable diffusion techniques.

In between his two times working at Knexus, JT worked at Clarifai, Accenture, and Deloitte. When not working, JT can be found at a golf course fighting for par, or watching a (Commanders, Capitals, Nationals) game live or conversing with a TV screen about the game. JT is a featured Bass 2 singer in the local community choir.

More information can be found on his personal website www.JTT.ai