The fields of artificial intelligence (AI) and machine learning (ML) are constantly advancing as new insights emerge. With creativity and a determination to solve tough problems, Booz Allen develops and contributes inventive research that enables this critical progress. By building a research-focused culture and empowering our engineers and data scientists to innovate, we move AI forward into the future while helping our clients keep pace with the breakthroughs they need to achieve their most important objectives.
Booz Allen experts join with other leading voices to further the 21st-century AI conversation. Our team consistently publishes basic and applied AI/ML research in leading, peer-reviewed conferences and journals like Neural Information Processing Systems (NeurIPS) and Conference on Computer Vision and Pattern Recognition (CVPR). Our practitioners have published more than 60 papers in emerging areas of AI, ML, and deep learning. We also collaborate with startups on fundamental and early applied research projects that have improved AI applications in public health and other key areas. By using research as the foundation for informed, creative thinking, we’re better able to anticipate solutions that may not be possible today but could soon become essential for our clients’ defense, national security, and civil missions.
To connect our people with the latest ideas, a vibrant firmwide network links Booz Allen with outside research leaders from across the global academic community. We actively collaborate with computer science labs and math departments at Harvard University, Syracuse University, the Montreal-based Mila Institute, and other organizations. And our university-wide master collaboration agreement with the University of Maryland, Baltimore County, lets Booz Allen practitioners work on interdisciplinary projects with any professor from any department. Open access to academic environments enables our people to hone their expertise, often at the Ph.D. level, while continuing to build careers in industry.
We support emerging researchers by providing them with mentoring and ongoing opportunities to explore transformational AI concepts. A Booz Allen initiative provides computer science and math graduates from universities, including the Massachusetts Institute of Technology and Harvard, with opportunities to author papers and conduct other research activities. Participants build on their prior undergraduate and graduate coursework and their university research projects to rapidly hone skills and publish findings. We have also helped members of the University of Notre Dame’s ESTEEM program complement their advanced science and engineering backgrounds with learning experiences in entrepreneurship and innovation.
AI practitioners who bring their talents to Booz Allen benefit from world-class technical capabilities that open up new avenues for research. We invest in advanced computing infrastructure both to support specific client projects and to expand internal research opportunities. Booz Allen teams use a newly built, state-of-the-art graphics processing unit (GPU) cluster to explore their areas of research focus across AI-related disciplines, from adversarial AI and malware detection to computer vision, natural language processing, and more.
By investing in research as a powerful foundation for our business, we seek to create new knowledge and help the world better understand the promise of AI. What sets Booz Allen apart is the unique opportunity we have, as the largest provider of AI services to the federal government, to turn our research into real-world applications that transform how agencies solve challenging problems and achieve mission goals, whether it’s serving citizens more efficiently, turning raw data into intelligence insights, strengthening public health, or thwarting adversaries in cyberspace and on the battlefield. The unique needs of our clients then refine our research, ensuring our long-term work has real-world impact.
Read more than 60 research papers from Booz Allen experts and explore career opportunities to learn more about how we engineer the next AI solutions on a foundation of peer-reviewed research and practical innovation.
Our cybersecurity practice has shown that many off-the-shelf and best practices in machine learning and deep learning don’t translate to cybersecurity data. Because of this, we often develop new methods to meet the larger scale, non-independent, and identically distributed nature of real data.
Our scientists and engineers work together to transform organizations. From analytics to artificial intelligence and high-speed computing to quantum information services, we’re empowering people to change the world.