Networks make the whole greater than the sum of its parts. Social networks, computer networks, and transportation networks are all examples of networks that are deeply enmeshed into our lives. CISE investigates fundamental research questions in networks, such as network formation and evolution, and interaction between network agents (which may be selfish or malicious). The questions are addressed through advances in the fields of optimization, control, distributed algorithms, and game theory. The theoretical methods are complemented by experimental work, which include testing of IoT and 5G network systems, deployment of networks of autonomous agents (e.g., robots, drones, and connected vehicles), design of neural networks for deep learning, federation of cloud computing systems, and data-driven methods to detect and thwart malicious behavior on the Internet.

Collaborative Research: CPS: Medium: An Online Learning Framework for Socially Emerging Mixed Mobility

Emerging mobility systems, e.g., connected and automated vehicles and shared mobility, provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better decisions for improving safety and transportation efficiency. However, different levels of vehicle automation in the transportation network can significantly alter transportation efficiency metrics (travel times, energy, environmental […]

Faster, Greener, Cheaper, More Secure: Yazicigil’s GRAND Project Pushes Forward with New Funding

CISE Faculty Affiliate Professor Rabia Yazicigil (ECE)  and her MIT collaborators are on a roll. The multi-institutional team behind the GRAND universal decoder algorithm and its first realization in hardware have been awarded $5M in funding by the Defense Advanced Research Program Agency (DARPA) to continue developing revolutionary improvements to wireless communications. Alongside co-PIs Professor […]

Arslan Riaz awarded COMSNETS 2022 Best Research Demo Award

Arslan Riaz, PhD candidate (ECE), won the “Best Research Demo” award at the 14th International Conference on COMmunication Systems & NETworkS (COMSNETS 2022) January 3-8, 2022. Riaz demonstrated the first fully-integrated universal Maximum Likelihood Decoder in 40 nm CMOS using the Guessing Random Additive Noise Decoding (GRAND) algorithm. This novel technology provides a universal system for […]

Collaborative Research: SaTC: CORE: Medium: ONSET: Optics-enabled Network Defenses for Extreme Terabit DDoS Attacks

Distributed Denial of Service (DDoS) attacks continue to present a clear and imminent danger to critical network infrastructures. DDoS attacks have increased in sophistication with advanced strategies to continuously adapt (e.g., changing threat postures dynamically) and induce collateral damage (i.e., higher latency and loss for legitimate traffic). Furthermore, advanced attacks may also employ reconnaissance (e.g., […]

CNS Core: Small: Building Resilience into Blockchains

Blockchains and cryptocurrencies have emerged as disruptive technologies with profound financial and societal impact. This state of affairs makes it imperative to gain better understanding of the dynamics and resilience of the underlying peer-to-peer networks on which blockchains operate. To this end, this project researches novel measurement methodologies, statistical modeling, and design approaches for distributed […]

Collaborative Research: SWIFT: Facilitating Spectrum Access by Noise Guessing

Wireless technologies play an essential role in enabling growth and prosperity in societies by supporting business, government, science and education, defense, and health sectors. The boom of connected Internet of Things (IoT) nodes and 5G wireless communications will lead to a many-fold increase in wireless data traffic. This data storm and connectivity-in-everything model will result […]