illustration of hand picking grapes
Illustration: Brian Long, UCSB
Courtesy: Yon Visell's RE Touch Lab

CSP Research Activities

Activities & faculty include but are not limited to:

Computer Vision, Graphics, and Computational Imaging

Methods to interpret images and map them to objects. Methods to digitally synthesize images on a computer — Faculty

Control, Optimization and Game Theory

The theory of optimal design and operation of systems, including those with strategic interaction among multiple agents — Faculty

Information Theory and Statistical Inference

The theory of processing, storage, and communication of data in noisy environments with a probabilistic point of view — Faculty

Machine Learning and Data-Driven Methods

Methods to learn and predict from data — Faculty

Networked and Cyber-Physical Systems

The theory of operating networked systems in which physical, cyber, and human components are intertwined, e.g., transportation networks — Faculty

Robotics and Autonomous Systems

Systems that perform complicated tasks with a high degree of autonomy, e.g., robots, self-driving vehicles — Faculty

Signal and Image Processing

The design of algorithms and hardware to manipulate and process signals, e.g., audio, images, video, or sensor data — Faculty

Wireless Communication & RF Sensing

Theory and practice of sensing, communicating and inferring information via wireless communication systems and sensors — Faculty

CSP Research Overview

The field of Signal Processing is concerned with the design and implementation of algorithms for manipulating, forecasting or classifying signals containing information. Examples include classification of objects (e.g., faces) in an image, speech recognition and synthesis, video compression, medical diagnosis from biological signals such as the heartbeat in wearable devices, or learning a detailed map of the area surrounding an autonomous vehicle to allow safe navigation in unknown environments.  Signal processing techniques are ubiquitous in engineering systems, including but not limited to communications devices (cell phones, WiFi), digital music/video players, televisions, GPS receivers, radar and sonar systems, the Internet of Things (IoT), and medical imaging and monitoring systems.

Communications is as essential to modern society as electricity, providing technologies for both high speed connectivity (cellular, WiFi, Internet) and efficient storage (hard drive, flash memory). The field of communications spans signal processing and error control coding for transceiver design, information theory to identify fundamental performance benchmarks, and the design of communication network protocols.

The communications and signal processing faculty at UCSB engage in cutting-edge research in communication theory and networking (with current focus on next generation wireless communication and sensor networks), novel machine learning and optimization techniques (spanning a range of fundamental questions and practical applications), image informatics and reconstruction (extracting and organizing information from images for biological research, diagnosis, surveillance, production monitoring). The emergence of a well-developed software infrastructure for machine learning and large-scale optimization, along with the availability of large amounts of data in a variety of fields, is feeding a number of exciting research initiatives.  CSP faculty are leveraging these advances to attack problems that are difficult to solve with classical techniques, as well as bringing a CSP perspective to explore the fundamentals of robust, interpretable machine learning. In addition, research continues to be directed at advancing core knowledge in CSP in areas such as information theory, estimation theory, compression, and harmonic analysis. Much of the research in the CSP group involves interdisciplinary scientific and industrial collaborations, including technology transfer via startup companies. Close connections with industry are maintained through faculty interactions and student internships, leading to an understanding of emerging trends and bottlenecks in technology.

For more detailed descriptions of faculty research and activities, please follow the links to the various research centers, labs, and groups indicated on this page.

CSP UCSB Affiliations

CSP Faculty Groups / Labs

Name Group / Lab Research Interests
Mahnoosh Alizadeh Smart Infrastructure, Cyber-physical Systems, Network Systems
Jerry Gibson Agent Learning and On-Line Learning, Lossy Source Coding, Information Theoretic Signal Processing, Voice and Video Compression, Multimedia over Networks, Wireless Communications
Hua Lee High-Resolution Imaging Techniques; Microwave, Acoustic, and Ultrasound Imaging Systems; Medical Imaging Devices; Distributed Sensing and Imaging Networks
Upamanyu Madhow Next-generation Communication, Sensing and Inference Infrastructures centered around Millimeter Wave Systems; Signal Processing Algorithms; Robust Machine Learning
B.S. Manjunath Image Informatics
Yasamin Mostofi Mobile Sensor/Vehicle Networks, Wireless Communications, Networked Control Systems
Ramtin Pedarsani Machine Learning, Information Theory, Human-Cyber-Physical Systems, Stochastic Networks
Kenneth Rose Information Theory, Source Coding and Networking, Distributed Coding, 360-degree Video Coding, 3D Audio Coding, Pattern Recognition and Machine Learning, Nonconvex Optimization
Pradeep Sen Computer Graphics, Imaging, Computer Vision
Christos Thrampoulidis High-dimensional Data Analysis, Machine learning, Compressive Sensing, Computational imaging, Optimization
Yon Visell Haptics, Robotics, Tactile Sensing, Soft Electronics, Soft Robotics, Bioinspired Systems, Computational Acoustics