Robert Munro

/ Rob Munro

@WWRob on Twitter @rmunro on GitHub @robert.munro on Medium @robertjmunro on LinkedIn

PLEASE NOTE: I am currently helping with the COVID-19 response and might be slow to respond to other communications. If you are a data scientist and would like to help with the response, please see my article in KDnuggets for recommendations on where to begin: 5 Ways Data Scientists Can Help Respond to COVID-19 and 5 Actions to Avoid

Robert Munro is an expert in combining Human and Machine Intelligence. Robert has founded several AI companies, building some of the top teams in Artificial Intelligence. He has worked in many diverse environments, from Sierra Leone, Haiti and the Amazon, to London, Sydney and Silicon Valley, in organizations ranging from startups to the United Nations. This includes work as the CEO and founder of Idibon, the CTO at Figure Eight, and leading AWS's first Natural Language Processing and Machine Translation services, Amazon Comprehend and Amazon Translate.

Robert is the author of Human-in-the-Loop Machine Learning, covering practical methods for Active Learning, Transfer Learning, and Annotation.

Robert organizes Bay Area NLP, Silicon Valley's largest community of Language Technology AI professionals.

Robert is the founder & CEO of Machine Learning Consulting, a network of Machine Learning professionals dedicated to building smarter, fairer applications.

Outside of work, Robert has traveled across more than 20 countries by bicycle.

Robert's career combines leadership in Machine Learning and Technology for Disaster Response, with a focus on fairness and inclusion in Machine Learning.

Recent talks:

KDD (Conference on Knowledge Discovery and Data Mining), 2019. Should You Open-Source Your Model? Ethical questions for open-sourcing Machine Learning models:

Google Next, 2018. Vision: API and Cloud AutoML:

AWS re:Invent, 2017. Building an Artificial Intelligence Practice for Consulting:

Train AI, 2018. Real World Human-in-the-Loop Machine Learning:

Natural Language Processing (NLP) at scale

Robert led Product for Amazon Comprehend and Amazon Translate, AWS's first Natural Language Processing and Machine Translation solutions.

Robert was CEO and co-founder of Idibon, the first enterprise machine learning startup to launch out of Stanford University, setting the trend for many more to follow. Idibon shipped language-indepedent NLP products to the largest companies in accounting, gaming, automotive, finance, and gave the technology away to support free maternal healthcare.

AI and Distributed Human Computing for Disaster Response

Robert worked in post-conflict development in Seirra Leone and Liberia for local organizations and the United Nations. Everyone in the refugee camps had access to a cellphone, but because the machine learning applications only worked in a handful of languages, it meant that most people were not able to take advantage of advances in AI.

Robert completed his PhD at Stanford with a dissertation focused on adapting machine learning to low resource languages for healthcare and disaster response.

While at Stanford he still regularly helped respond to disasters, including managing 2000 members of the Haitian diaspora to translate, categorize and map emergency text messages sent in Haiti in the wake of the earthquake in 2010.

Global Epidemic Tracking

Robert worked at Global Viral Forecasting (now Metabiota) as the Chief Technology Officer for EpidemicIQ, a solution for tracking global disease outbreaks. Tracking billions of data-points daily from data in more than a dozen languages and often beating the major health organizations by days in identifying outbreaks.

Documenting Indigenous Languages

Half of the world's 7,000 languages will disappear within the next century. The majority are only spoken languages, so the race is on to record as many as possible before the languages, stories, and cultures disappear.

Robert was a software developer for the Endangered Languages Archive which preserves recordings of 100s of languages and lived with Matses of the Peruvian Amazon, documenting their language, which is one of the most unique on earth.