Newswise — The National Science Foundation (NSF) announced today an investment of $220 million to establish 11 artificial intelligence (AI) institutes, each receiving $20 million over five years. One of these, The Institute for Learning-enabled Optimization at Scale (TILOS), will be led by the University of California San Diego in partnership with the Massachusetts Institute of Technology; San Diego-based National University; the University of Pennsylvania; the University of Texas at Austin; and Yale University. TILOS is also partially supported by Intel Corporation. 

“These institutes are hubs for academia, industry and government to accelerate discovery and innovation in AI," said National Science Foundation Director Sethuraman Panchanathan. "Inspiring talent and ideas everywhere in this important area will lead to new capabilities that improve our lives ... and position us in the vanguard of competitiveness and prosperity.”  

"As a global society, we can't afford to allow advances in optimization to be underutilized," said UC San Diego Chancellor Pradeep K. Khosla. "The TILOS team is made of an incredible combination of engineers, computer scientists, data scientists and educators who will tackle the hardest theoretical and applied challenges in optimization through virtuous feedback loops that ensure the advances will make a positive difference in the real world."  

Learning-enabled optimization

“Optimization is a universal quest: we are driven to do better,” said Andrew Kahng, a computer science and electrical engineering professor at the UC San Diego Jacobs School of Engineering and TILOS director. “Optimization is also a hard problem, as the number of choices explodes in large-scale systems. The TILOS mission is to make today’s impossible optimizations possible, at scale and in practice. Whether for energy-efficiency, safety, robustness or other criteria, improved optimizations have the potential to bring incalculable benefits to society.”

Optimization is a fundamental component of machine learning, an important area of modern AI. Conversely, learning can help solve difficult optimization problems. Foundational research in TILOS will explore this interplay to develop optimization methods that can change the leading edge of real-world practice. In close collaboration with industry partners, institute researchers will develop learning-enabled optimization tools for application areas of strategic importance to the United States, including chip design, robotics, and communication networks. 

Fundamental and applied research

"Optimization is both a science and a technology,” commented Rajesh K. Gupta, director of the Halicioglu Data Science Institute, UC San Diego’s campus hub for data science that will house TILOS. “This new AI institute will not only discover new science at the interface of AI and optimization, but also deliver it to real-world practitioners as a technology: measuring it to improve it, with benchmarking and a roadmap of progress.”

Foundational research will drive important applications. In chip design, these advances would dramatically shorten the time needed to design chips, increasing quality, productivity and innovation in the process. In robotics, optimization breakthroughs would improve the way robots learn and interact with humans and other robots in many contexts, including search and rescue, autonomous transportation, and warehouses. In communication networks, better optimization would lead to more capable and efficient power grids, mobile phones, and ecosystems within the Internet of Everything.   

Data and insights from optimization in these application areas will further inspire and challenge fundamental research efforts in AI and optimization. This virtuous cycle in TILOS will accelerate the pace of discovery and translation into the leading edge of practice.

Education and workforce development 

The TILOS research will engage undergraduates, graduate students and post-doctoral researchers at every step. In addition, the TILOS team has planned a broad program for workforce development, which will identify and teach new practical skills and mindsets that emerge from fundamental and applied advances in optimization. The team is building an openly accessible program of continuing education with long-term, lifelong learning and skills renewal as its central tenet. 

Broadening participation

TILOS programming will extend beyond the classroom, with embodied robot demonstrations, community art installations, and portable, adaptable “outreach in a box” modules to engage and excite a next generation of learners. These initiatives aim to grow awareness of, and access to, new career and educational opportunities -- especially among students who are traditionally underrepresented in engineering. 

"Many meaningful and rewarding career opportunities will emerge at the nexus of AI, optimization, and application domains. As a team, we will pursue basic research, translate our results into industrial practice, train the future workforce, and bring awareness of the broader educational and job opportunities that result from advances in AI and optimization," said Kahng.  

Learn more:

TILOS website

TILOS on Twitter: @tilos_ai