Engineer Change.

Big Data, Artificial Intelligence and Machine Learning

 

Finding the needle in the haystack? That’s easy. Sorting through a few billion haystacks to figure out why a few needles are there in the first place? That’s where UCLA Samueli engineers and computer scientists come in. We’re crunching numbers to come up with better medicines. We’re mining information networks to better inform public policy. And we’re designing new software systems to speed up big data analysis. We’re bringing our expertise to major collaborations across the campus in biology and cardiovascular health.

In artificial intelligence and machine learning, we’re developing technologies that will change how we interact with the world. Of course, we’ve been making revolutionary breakthroughs on modern AI since the start.

How good will machines be at learning in 10 years or 20? Stay tuned here to find out.

Click on the links below to visit some of our labs.
A group of UCLA faculty members are working on high-performance analysis of big data.
Director: Wei Wang, Leonard Kleinrock Professor of Computer Science
The institute is working on the advancement and application of the risk sciences to save lives, protect the environment and improve system performance.
Director: Ali Mosleh, Evalyn Knight Chair in Engineering, professor of materials science and engineering
A partnership between the UCLA College, the Health Sciences, and Engineering, the institute’s mission is to support quantitative and computational biosciences research, training, and education.
Director: Peipei Ping
Researching the science and engineering of complex networks.
Director: Vwani Roychowdhury, professor of electrical and computer engineering
The center pursues a unified framework for representation, learning, inference and reasoning, and looks to build intelligent computer systems for real world applications. Director: Song-Chun Zhu
Probabilistic and logical reasoning and their applications to problems in science and engineering disciplines.
Director: Adnan Darwiche, professor of computer science
The lab studies machine learning, knowledge representation and reasoning, applications of probabilistic reasoning and learning and AI in general.
Director: Guy Van den Broeck, assistant professor of computer science
Analyzing a large amount of information generated by users, so that we can deliver the most up-to-date, high-quality, relevant information to users.
Analyzing a large amount of information generated by users, so that we can deliver the most up-to-date, high-quality, relevant information to users.
Research in robust automatic speech recognition, text-to-speech synthesis, and models of human speech production and perception mechanisms. Applications in education, health, and telecommunications.