SAN JOSE, Calif. — (BUSINESS WIRE) — July 6, 2015 — Accenture (NYSE: ACN) has awarded 11 research grants to top universities around the world to significantly broaden and deepen the relationships between Accenture’s technology research and development (R&D) groups and leading university researchers.

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The grant program helps to support the ground-breaking efforts of leading university research teams, which will be invited to work in collaboration with researchers from the Accenture Technology Labs on R&D projects that are of strategic importance to the technology industry and Accenture’s enterprise clients.

“Universities are a critical source of technical and scientific research that can deliver long-term business benefits for organizations around the world,” said Prith Banerjee, managing director of Global Technology R&D, Accenture. “We are thrilled that this grant program, in conjunction with the Accenture Open Innovation initiative, will enable Accenture Technology Labs researchers to translate a university’s conceptual research – which spans topics from cyber security to 3D printing and cognitive computing – into ideas that can ultimately help solve real business challenges for our enterprise clients.”

The grant program is part of the Accenture Open Innovation initiative, in which Accenture functions as a bridgemaker between Accenture’s Global 2000 clients and the technology innovation ecosystem, which includes universities, top tier accelerators, start-ups, venture capitalists and corporate R&D labs from around the world. New technology research from Accenture Strategy found that four out of five enterprise respondents reported innovation was within their top three priorities and about one quarter placed innovation as the number one priority for their organization.

The 2015 Accenture Open Innovation university grant program recipients and the R&D areas of focus include:

• Prof. David Bader, Georgia Institute of Technology

This project is focused on accelerating anomaly detection of advanced persistent threats, zero-day malware, and other malicious cyber threats using graph analytics.

• Prof. Zhejing Bao, Zhejiang University, China

This project will focus on the development of a prediction technology that provides short-term customer energy demand forecasting by utilizing real-time and historical sensor data of electricity consumption and other information, such as weather forecasting data and customer information.

• Prof. Michael Bernstein and Prof. Melissa Valentine, Stanford University

Exploring tools and techniques needed to create a “Hybrid Virtual Workforce,” this project will look at how work traditionally carried out by static teams of enterprise employees can instead be carried out by computationally-guided, dynamically-assembled flash teams.

• Prof. Pushpak Bhattacharyya, Indian Institute of Technology Bombay, India

Focused on developing a text to universal language converter, this project aims to create more robust and accurate natural language processing capabilities.

• Prof. Sutanu Chakraborti, Indian Institute of Technology Madras, Chennai, India

This project will focus on the development of decision-making algorithms to conceptualize and develop cognitive learning systems. It will leverage a principled combination of bottom-up, data-driven techniques, such as machine learning, and top-down knowledge-based approaches classically used in planning and reasoning.

• Prof. Abhijit Deshmukh, Purdue University

Focused on developing new approaches to understanding complex systems, this project will look at building more efficient systems by using next generation manufacturing and supply chains in a circular economy as a use case.

• Prof. F. Javier Heredia and Prof. Joaquim Minguella, Universitat Politecnica de Catalunya, BarcelonaTech

Studying the advantages of ultra-postponement with 3D printing by using analytical tools and mathematical optimization models and algorithms, this project will explore how to transform supply chain management by allowing delayed and tailored production in the location where demand occurs.

• Prof. Michal Kosinski, Stanford University

This project aims to increase the understanding of customer behavior and design more psychologically matched customer interactions. It will explore approaches to building predictive models of a customer’s psychological profiles using machine learning in conjunction with shopping records and external social network data.

• Dean Richard Lyons, University of California, Berkeley, Haas School of Business

A new multi-disciplinary experiential learning course for MBA students will focus on data strategy and data science curriculum. The goal is to create the next generation of business decision makers, develop and broaden data strategy skills and refine and improve this developing field of activity.