Convergence Accelerator Portfolio

The Convergence Accelerator program is comprised of two cohorts, 2019 and 2020. Each cohort is focusing on two research track topics. The 2019 cohort teams are in phase two. The 2020 cohort teams are in phase one. 

2019 Cohort


Launched in September 2019, a total of 43 phase one teams were awarded a total of $39 million to support projects focused on the two research track topics—Open Knowledge Networks and the Future of Work.  At the end of phase one, the teams participated in a formal pitch presentation and phase two proposal. In September 2020, the Convergence Accelerator awarded nine teams phase two awards investing in more than $28 million to address national-scale societal challenges and to generate knowledge to transition ideas from research into practice. 

Track Topics

Open Knowledge Networks | Track A


Knowledge networks pool together many types of information and ideas so that they can be accessed and leveraged to create new understanding. These networks have become important tools for many large organizations that are taking advantage of the current big data revolution. However, these vast information networks are often unavailable to many in government, academia, small businesses, and nonprofits. The Convergence Accelerator is funding the creation of a nonproprietary infrastructure for building an Open Knowledge Network. Some of the teams are building tools that will identify, harvest, and incorporate datasets for the network. Others will build elements of the open knowledge network that address specific challenges, such as judicial

Open Knowledge Networks funded teams include:

Open Knowledge Networks Track Manager: Lara Campbell, Program Director


The Future of Work| Track B


The world's technological advancements in AI, machine learning, and robotics are irrevocably shifting the future of work in unanticipated ways. The Convergence Accelerator is focusing on solutions to train, reskill, upskill, and prepare the current and future workforce with industry needs and jobs of the future, as well as build a talent pipeline to stimulate the U.S. workforce. Some teams are focusing on predictive AI tools and educational technology needs for adult learning, while others are developing innovative approaches that employers need to support workers seeking the skills required for 21st century work related to AI, data science, predictive analytics, and other technologies of the future.

The Future of Work funded teams include:

The Future of Work Track Manager: Linda K. Molnar, Program Director

Resources

2019 Cohort Project Videos


The Convergence Accelerator's 2019 Cohort phase I included 43 teams focused solutions in two track topics—Open Knowledge Networks (Track A) and The Future of Work (Track B). Both track topics support two of NSF's Big Ideas": Harnessing the Data Revolution and the Future of Work at the Human-Technology Frontier.

During Phase I, a nine-month planning effort, teams leveraged the Convergence Accelerator's fundamentals and innovation curriculum to identify new team members and to further develop the identified solution. The innovation curriculum consists of training in human-centered design, team science activities, inter-team communications, pitch preparation, and presentation coaching—all of which are essential components of the Accelerator's model. At the end of phase I, each team participated in an Expo, pitch competition and a proposal evaluation. Selected teams from phase I were then selected into phase II. These videos feature 2019 Cohort Phase I teams and were crated for the 2020 Convergence Accelerator Expo.  View the video list here.

News


NSF Convergence Accelerator awards bring together scientist, businesses, nonprofits to benefit workers
, September 10, 2019

Accelerating research to impact society at scale, September 3, 2020

2020 Cohort


In September 2020, the Convergence Accelerator launched the 2020 cohort, awarding 29 teams phase one awards totaling $27 million. The 2020 cohort addresses two transformative research areas of national important: quantum technology and artificial intelligence. 

Track Topics

Quantum Technology | Track C


Improving the U.S. industrial base, create jobs, and provide significant progress toward economic and societal needs is vital. Teams within the Quantum Technology track are developing a wide range of solutions to include preparing the future workforce including students entering the workforce, reskilling, and upskilling the current workforce, as well as developing quantum sensors and interconnects to deploy new technologies in a variety of applications, such as autonomous vehicles and healthcare.

Quantum Technology funded teams include:

Quantum Technology Track Manager: Pradeep Fulay, Program Director


AI-Driven Innovation via Data and Model Sharing | Track D


Artificial intelligence (AI) research and development is a U.S. priority, including developing and enabling access to high-quality datasets and environments; and testing and training resources. Teams aligned to this track topic are developing solutions to address a variety of data and model-related challenges and data types to include platform development to enable easy and efficient data matching and sharing; and privacy protection tools and processes to ensure sensitive data is secure.

AI-Driven Innovation via Data and Model Sharing funded teams include:

AI-Driven Innovation via Data and Model Sharing Track Manager: Michael Pozmantier, Program Director

News


Delivering societal impact through quantum and AI-driven data and model research
, September 17, 2020