Welcome to the NET-SCIENCE Lab.
At the NET-SCIENCE lab, we are working on building the next generation of our critical infrastructures more roubst, more reliable, more secure and more efficient through real-time smart decisions. Humans are becoming a part of the smart cities, where the Internet-of-things (IoT) devices such as connected sensors, traffic lights, and meters are used to collect and analyze data to control and improve infrastrcutures, public utilities and services to the customers. Therefore, understanding the interactions between humans, smart devices, and the infrastructures will be helpful to design more meaningful control strategies. Our goal is to understand such interactions, and use this understanding to make better design and control decisions. More specifically, we focus on efficiently analyzing different data sources such as online social network and IoT (Internet of Things) devices to predict and control events in our critical infrastrucutres. Our mission is to build a distributed platform that can optimally and efficiently analyze the big data collected from different data sources to design more reliable, more efficient, and more robust interdependent infrastructures for smart cities.
A paper co-authored by Minoo, Nathaniel, and Dr. Khamfroush on latency/accuracy trade-off of deep learning models on the edge has been accepted for publication for IEEE GLOBECOM's 2020 Workshop series.September 19, 2020
Nathaniel received the NSF student travel grant for the 2020 SMARTCOMP conference.September 08, 2020
Minoo and Dr. Khamfroush's paper on edge layer optimization has been accepted for the SmartGridComm 2020 conference.August 26, 2020
Dr. Khamfroush has been designated to serve as the co-advisor of ACM-W at the University of Kentucky.July 28, 2020
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Join the Team!
We are always looking for motivated undergraduate and graduate students to work with us. The lab is a growing and fast paced environment, and there are many interesting and challenging research problems to work on across different disciplines. Our research is interdisciplinary, we are working with researchers from many diffrent disciplines, including, public health, transporation, electrical engineering and social science. I am especially interested to work with students with background in machine learning, networking, optimization and algorithms! If you are interested and you feel like this can be a good fit for you, please send an email to firstname.lastname@example.org, include your CV, and describe what aspect of my research is interesting to you.
**For students who are already at the University of Kentucky, stop by my office at 317 DMB during my office hours, or email me to arrange a meeting.
Notes for interested undergraduate students.
The NET-SCIENCE Lab is always looking for talented and enthusiastic undergraduate students. If you are interested in getting involved with our lab, please contact Dr. Hana Khamfroush via email (go to Contact page for details).