Research Overview

Prof. Heather Zheng at the white board

Computer Engineering Research at UCSB

CE research lies not only at the interface of computer science and electrical engineering, but increasingly ties computing together with biology, medicine, chemistry, physics, mechanical engineering, and even environmental engineering.

Our research is ideally positioned to help solve societal problems through the construction of practical systems composed of emerging technologies. We live in a time of both opportunity and crisis. Rising carbon emissions and energy costs are a global problem. Aging populations increasingly strain healthcare resources. Computing technologies are at the heart of many potential solutions to these problems. Emerging technologies in nanoscale and bio-compatible materials hold the promise to increase energy-efficiency and revolutionize healthcare. We also see opportunities in massive information gathering and large-scale computing resources to exploit that information.

We must also address increasing challenges to continued scaling of conventional silicon and to maintaining the dramatic performance growth of past computing systems.

CE Areas of Research

  • Bioinspired Computing
  • Circuit and System Design
  • Computer Architecture
  • Electronic Design Automation & Testing
  • Emerging Technologies for Computing

  • Energy-efficient Computing
  • Nanotechnology
  • Networking
  • Operating and Distributed Systems
  • Software and Language

Faculty Lab Spotlight


Intelligent and Predictive Systems Laboratory
Alberto-Giovanni Busetto, Assistant Professor


ips lab logo

The research work of the IPS Lab primarily concerns the development of methods to reliably extract useful knowledge from raw data. The ultimate goal of our interdisciplinary activity is to provide users with tools able to automatically select the most useful bits of information for the purpose of improving the performance of a specific task (for instance, solving an optimization problem).


Our research program consists of three main aspects:

  1. Extracting information to algorithmically generate hypotheses and models, to explore data with the purpose of identifying causal relationships, as well as to detect outliers, atypical and anomalous behavior;
  2. Validating predictions to select the correct model class from a set of candidates, to statistically validate how appropriate is the available class for a specific application, to adaptively approximate input-output functions and quantify uncertainty;
  3. Deciding optimally to design crucial experiments, to select interventions, inputs or actions to maximize the expected utility by taking advantage of validated information.

In our vision, these steps will help building computer systems that are able to operate well even under heterogeneous disturbances, general uncertainty, and in particular to perform efficiently when dealing with noisy big data. A key aspect of our research is the emphasis on strategies designed to achieve justified tradeoffs between exploration and exploitation, and between model simplicity and predictive power.

Our activity exhibits the following methodological priorities:

  • Information-theoretic validation of unsupervised learning (clustering, in particular), big data, time-series analysis and causal inference.
  • Statistical system identification of discrete (automata, Boolean networks), continuous (ordinary, stochastic, partial differential equations) and hybrid systems (cyber-physical, digital-dynamic controllers).
  • Reinforcement learning with multi-armed bandit models, sequential and parallel design of experiments.

Our contributions impact a wide spectrum of application domains, and our research is motivated by concrete problems from personalized medicine, synthetic biology, nanotechnology, computational physics, wind power, and human learning. We welcome and encourage further collaborations with other groups!

Asst. Prof. Alberto Giovanni Busetto selected for NAE's 2015 U.S. Frontiers of Engineering Symp.

photo of alberto giovanni busetto Giovanni Busetto among eighty-nine of the nation’s brightest young engineers selected to take part in the National Academy of Engineering’s 21st annual U.S. Frontiers of Engineering (USFOE) symposium.

Faculty Research News

Prof. Chandra Krintz named 2015 UCSB Academic Senate Faculty Sustainability Champion

photo of chandra krintz Krintz’s proposal addressed the problem of sustainable food security and food safety, especially with smaller farms. The AS work group was impressed with Krintz's use of computer science to provide a framework for the management of agricultural resources.

Faculty Research Profile: Professor Rich Wolski

photo of Rich Wolski
  • Ph.D.: UC Davis
  • Lab / Group: RACELab
  • Research Interests: to explore ways in which the ubiquitous proliferation of high-performance network connectivity can be used to foster new distributed computing capabilities and systems

Tell Us About Your Research: We investigate the use of open source software technologies to build scalable systems. Cloud computing and large-scale high-performance computing depend on software innovations that enable the computational, communication, and storage capabilities of many computers and networks to be used together. Our group studies the system-building principles needed to create such amalgamations empirically, by building experimental software systems that can be tested and studied in a scientific context.

Why Did You Get Into Your Area of Research and Why UCSB?:
I have always been fascinated by the idea of building large systems that can perform ever more powerful computations. The emergence of Internet Search as a key societal technology demonstrates how very large scale computation can lead to important new capabilities. UCSB is remarkable in its support of empirical research (that has impact in the "real world") and cross-disciplinary collaborative research. I was drawn to it because there did not seem to be boundaries or impediments to how and what I could study in this exciting field.

What Do Find Particularly Rewarding About Your Research?: Working with students to investigate new answers and solutions to pressing and difficult problems is by far the most rewarding part of research for me.

Where Will Your Research Take You Next?: Scalable computing will continue to change the world by making what human kind can know, broader and more accessible. I'm looking forward to the research that accelerates this process.

(More about Professor Wolski and other faculty's research...)