The 2019 CTO Universe MVP Awards!

CTO Universe brings together the best content from hundreds of industry thought-leaders. These awards will recognize the Most Valuable Posts as judged by our readers, award committee, and our machine intelligence and social media. We will recognize the posts that provide the highest value to industry professionals - useful and actionable information, that is tactical or strategic in nature, providing either long-term or short-term value.

Check out the 2019 MVP Awards Winners Spotlight:

 

CATEGORIES

Awards will be given for articles covering the following categories:

Audience Size

Every day, our articles are read by an audience of over 21,000 people on our site and newsletter. We use our machine intelligence and social media, bolstered by our editorial team, to curate this content.

But 2019 is coming to an end and we want to know: of all of our articles, which are the best of the best? Our machine intelligence, social media, and editors can get us close. But we want that extra special touch that comes from beloved reader feedback.

You can represent these 21,000 readers. Cast your vote and let us know what you like to see!

Judging Criteria

We're judging posts that we see to provide the highest value to industry professionals. Does your article include useful and actionable information? Is it tactical or strategic? Does it provide short- or long-term value? Those are the types of questions our judges will be asking themselves.

PROCESS AND TIMING

Submitting content for consideration

To nominate an article, please fill out the Typeform above. Articles must have been published between January 1st, 2019 and October 18th, 2019 to be eligible.

Nominations are open until October 18th. After that, our panel of judges will review the nominations and narrow them down to a list of finalists for each category.

Voting

Finalists will be announced on November 18th. Once finalists are announced, we will open up voting to our readers. Voting ends on November 25th. Winners will be announced on December 4th.

Program Committee

Meet our expert panel of judges!

Patrick Kua

Chief Scientist, N26

Patrick Kua is the Chief Scientist and former CTO of the modern bank N26 (Berlin, Germany). With almost 20 years of experience in technology, he spent a significant time at ThoughtWorks as a Principal Technical Consultant. There he helped organisations improve their ability to rapidly build and evolve software. He is the author of three books, The Retrospective Handbook, Talking with Tech Leads and Building Evolutionary Architectures. Patrick is a frequent keynote speaker and writer and runs the Level Up Newsletter for all types of leaders in tech. He is passionate about a balanced focus between people, organisations and technology.

Melissa Woo

Senior Vice President, IT and Enterprise Chief Information Officer, Stony Brook University

Dr. Melissa Woo is the Senior Vice President for IT and Enterprise Chief Information Officer at Stony Brook University, responsible for the IT services supporting the University's teaching, research, patient care, and service mission. Melissa has also worked for the central IT organizations at the University of Oregon, University of Wisconsin-Milwaukee, and the University of Illinois at Urbana-Champaign. She was the 2012 recipient of the EDUCAUSE Rising Star Award, an annual award that recognizes an emerging leader in higher education IT. Melissa is actively engaged with higher education IT professional organizations, and is particularly passionate in her support of aspiring leaders from diverse backgrounds.

Alex Rasmussen

CEO, Bits on Disk

Alex Rasmussen is a data engineering consultant. Previously, he was VP of engineering at Freenome, an AI genomics company, and an early employee at Trifacta, a pioneer in the data wrangling space. He holds a PhD from the University of California San Diego (UCSD), where his dissertation focused on highly efficient large-scale data processing systems. While at UCSD, he led the TritonSort project, which set several world records in large-scale sorting.