Lum specializes in novel natural language processing and machine reading technology providing bespoke solutions for commercial and government customers. Let us help you increase opportunities by automating your tedious and repetitive tasks.
Kevin advised the team at the University of Arizona prior to co-founding Lum in 2017. He brings over 30 years of experience in technology commercialization, and executive leadership working for companies like Motorola, Cray Research, SGI, Cisco Systems and Avid technology. Kevin works with Tech Launch Arizona as Mentor in Residence for UA startups.
Associate professor in the Computer Science department at University of Arizona, co-authored over 90 peer-reviewed publications and has over 15 years of experience in building systems driven by NLP and machine learning. His experience spans both academia (Stanford University, University of Arizona) and industry (Yahoo! Research and two other NLP-centric startups).
Holds a PhD in Computational Linguistics with a focus on implementing linguistic theory in machine reading systems, ordering and assembling machine-read fragments, and identifying non-interacting research communities engaged in complementary work.
Holds a PhD in Computer Science. He has previous experience with multiple startups and is an expert on machine reading technology.
Holds a PhD in Linguistics with a focus in natural language processing. She specializes in complex linguistic phenomena and adapting machine reading to new domains.
Started programming professionally more than 40 years ago and has worked in the area of language technology for multiple research universities and startups.
Our natural language processing (NLP) technology accelerates discovery by distilling unstructured text to reveal cause-and-effect relations and knowledge gaps that provide insight and impact on your development priorities.
The company was founded in 2014 by a team of University of Arizona researchers with expertise in language-understanding systems. Lum's work was initially funded by DARPA through the Big Mechanism program to uncover novel genetic pathways for seven types of cancer. Subsequently, the Bill & Melinda Gates Foundation's used Lum AI in their Healthy Birth, Growth and Development (HBGD) initiative to successfully retrieve, assemble and interpret knowledge fragments from more than a hundred thousand publications relevant to children's health.