Featured Research

Mojtaba Soltanalian


Assistant Professor, Electrical and Computer Engineering
Waveform design and processing for next-generation radar systems

Radars have been a vital part of our civilization’s advancement in navigation, defense, meteorology, and space exploration. Like bats and dolphins in the animal world, radars emit waveforms to collect information and localize targets. The performance of radar systems can be considerably improved by a judicious design of their probing waveforms. Mojtaba Soltanalian and his research team are working to develop novel and extremely low-cost waveform design algorithms that address the fundamental requirements of future radar systems, including enhanced adaptivity, agility, and reliability. One application of interest is radar systems deployed in autonomous vehicles. The radar technology offers excellent resolvability and immunity to bad weather conditions compared with visible and infrared imaging techniques. The goal of Dr. Soltanalian’s research is to reduce the cost of such radar systems while maintaining their reliability, thereby helping with the mass deployment of radar-based advanced vehicular safety features.

Learn more about Dr. Soltanalian’s research on the Waveform Optimization (WaveOPT) Laboratory website.

Natasha Devroye

wireless communication devices

Associate Professor, Electrical and Computer Engineering
Information theory for spectrum sharing

Wireless communications are important parts of our daily lives in the public and private sectors alike. Wireless communications share the radio spectrum, and as the demand for wireless services increases, it is important to efficiently use this shared spectrum. A theme in Dr. Devroye’s research has been understanding how to efficiently let different devices share the same spectrum and how to handle interference. Options include “smart” devices such as cognitive radios, as in her seminal work (see here and here for research papers) or wireless communication systems that share the spectrum with a radar system, as noted in her recent work (papers here and here). Dr. Devroye and her research team approach this question from an information theoretic perspective, seeking to derive the fundamental limits, or capacity regions, of wireless networks. Information theoretic bounds such as capacity regions not only act as technology-independent benchmarks for measuring the performance of current systems—a “speed of light” against which to measure current technology—but also may guide industry and government on which directions to pursue. Find more information about Dr. Devroye’s publications and research interests on her UIC site.

Hulya Seferoglu

Internet of Things illustration

Assistant Professor, Electrical and Computer Engineering
Distributed coded computations for Internet of Things

The Internet of Things (IoT) is emerging as a new Internet paradigm connecting an exponentially increasing number of smart IoT devices and sensors. IoT applications include smart cities, transportation systems, mobile healthcare and smart grid, to name a few. Unlocking the full power of IoT requires analyzing and processing this data through computationally intensive algorithms at unprecedented high rates, with stringent reliability, security, and latency constraints. In many scenarios, these algorithms cannot be run locally on the computationally limited IoT devices and are rather outsourced to the cloud. This leaves the IoT network, and the applications it is supporting, at the complete mercy of threats—for example, hackers, unfriendly nations, or natural disasters such as hurricanes or earthquakes—that can jeopardize the IoT or completely disconnect it from its “brain,” the cloud, with potentially catastrophic consequences. To mitigate the computational bottleneck in IoT, Dr. Seferoglu and her collaborators focus on the scenario that IoT devices help one another in their computations in a distributed fashion, with possible help from the cloud, if available. Their approach is based on the new theory of coded computations, which studies the design of erasure and error-correcting codes to improve the performance of distributed algorithms through “smart” data redundancy. Dr. Seferoglu and the team have developed distributed, adaptive, and secure coded computation algorithms for IoT devices, and they have deployed these algorithms on real IoT devices to demonstrate the efficiency of the approach.

Research papers by Dr. Seferoglu’s research team are available here and here.