Cognitive Reconfigurable Embedded Systems Lab

Cognitive Reconfigurable Embedded Systems Lab is a unique research entity within UCLA, which focuses on research in Cognitive Radio and Cognitive Radio-like systems. We are interested in all modern radio technologies, with the emphasis on systems that enable more efficient utilization of spectrum. Our group headed by Prof. Danijela Čabrić is a vibrant and young group of graduate students, international visitors and researchers.


September, 2023

Welcome to our new MS student, Nicholas Borda!

September, 2022

Welcome to our new graduate student, Ibrahim Pehlivan, and our new visiting scholar, Hazem Sallouha from KU Leuven!

May, 2022

Congratulations to Samer Hanna for winning the Best PhD Dissertation Research Award in Signals & Systems!

December, 2021

CORES Lab releases the WiSig dataset!

September, 2021

Welcome to our new graduate student, Manali Sharma, and our new postdoc, Shamik Sarkar!

June, 2021

Congratulations to Benjamin Domae for being selected to receive one of the prestigious Department of Defense (DoD) National Defense and Engineering Graduate (NDSEG) Fellowships!

September, 2020

Congratulations to Han YanBenjamin Domae and Prof. Danijela Cabric for winning the Best Paper Award at the 4th ACM Workshop on Millimeter-Wave Networks and Sensing Systems (mmNets) 2020 for the paper “mmRAPID: Machine Learning assisted Noncoherent Compressive Millimeter-Wave Beam Alignment”!

September, 2020

Welcome to our new graduate students: Ruifu Li and Aditya Wadaskar!

May, 2020

Congratulations to Han Yan for winning the Best PhD Dissertation Research Award in Signals & Systems!

January, 2020

Congratulations to Enes Krijestorac for securing the 1st place in the Ph.D. Preliminary Examination (Signals & Systems track)!

September, 2019

CORES lab receives a new NSF award for Circuits and Systems Design for UAV Swarm Enabled Communications.

September, 2019

Welcome to our new graduate students: Benjamin Domae and Samurdhi Karunaratne!

May, 2019

Congratulations to Han Yan on winning the prestigious Qualcomm Innovation Fellowship!

February, 2019

Congratulations to Ghaith Hattab on defending his Ph.D. thesis!

February, 2019

Congratulations to Samer Hanna and Prof. Danijela Cabric for winning the Best Paper Award at IEEE ICNC 2019 for the paper “Deep Learning Based Transmitter Identification using Power Amplifier Nonlinearity”!

UCLA CORES Lab (as of February 2023)
from left to right Ding Zhao, Yen-Chin Wang, Ibrahim Pehlivan, Benjamin Domae, Tianyi Zhao, Hazem Sallouha, Danijela Čabrić, Enes Krijestorac, Shamik Sarkar, Donar Li, and Aditya Wadaskar

Our Research

CORES lab focuses on advances in radio hardware, signal processing, machine learning, sensing, communications, network protocols, and system architectures to enable future wireless networks. Our vision is that wireless networks require fundamentally new approaches to spectrum access based on dynamic spectrum sharing, operation at high frequencies and network intelligence. Critical to this vision is design of radios with sensing, learning, and cognition capabilities that can enable new dimensions for networks coordination and optimization of spectrum resources across time, frequency, and space. From the implementation perspective, the feasibility of hardware design, its cost and energy efficiency become critically important for their applications and adoption in future 5G cellular networks and Internet-of-Things (IoT). To address these research challenges, we have taken an interdisciplinary approach with a balanced mix of theoretical modeling, algorithmic development, system implementation and experimental validation. Our research activities have revolved around three main research thrusts:

See current projects
Postdoc position available

Postdoctoral scholar position (starting January 2020) available in Prof. Cabric’s research group at University of California, Los Angeles (UCLA), in the areas of millimeter wave communications, machine learning for spectrum sharing and distributed communications and sensing (funded by DARPA and NSF). Candidates with strong background in wireless communications, signal processing and machine learning are encouraged to apply. Prior experience in these research areas is preferred. Interested applicants should send their CV, along with the names of at least one reference, to Prof. Cabric via email (

We are thankful to our sponsors