Connectivity, Information & Intelligence Lab

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The Connectivity, Information & Intelligence Lab (Ci2Lab), directed by Professor Reza Arghandeh, has a simple goal: explain infrastructure networks with data analytics. Our research focuses on the intersection of machine learning, causal inference, and complex networks. We endeavor to answer how infrastructure networks are interconnected, how the environment impacts them (and the other way around), and how they shape our lives. 

 

Research

GridEyeS: AI-based Satellite Data Analytics for Infrastructure Monitoring

The rise of satellite imagery data and machine learning provide an opportunity to close the loop with continuous data-driven vegetation monitoring around infrastructure. We have developed an automated framework for monitoring vegetation along roadways and electricity lines using high-resolution satellite imagery and a semi-supervised machine learning algorithm. The proposed satellite-based vegetation monitoring framework, GridEyeS, aims to reduce the cost and time of asset monitoring by partially replacing ground patrols and helicopter or drone inspection with satellite data analytics. GridEyeS is supported by the European Space Agency. It is implemented on a Norwegian DSO system.

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AI4Hydro: AI Powered Forecasting for Hydro-Power 

The complex nature of cascaded reservoirs for hydropower generation plus climate change impose massive uncertainty and dynamics into classic hydropower scheduling tools. We are developing artifactual intelligent-based hydropower forecasting algorithms using hydrological and meteorological data to deal with spatiotemporal interdependencies among various reservoirs' inflow and water capacity for the Norwegian power system. This project is in collaboration with NTNU and Smart Innovation Norway.

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Co-Resilience: Multi-Domain Infrastructure Networks Resilience

Most studies on resilience treat it as a single dimension attribute of a system or investigate the different dimensions of the resilience separately without considering its multi-domain nature. We developed an advanced causal inference approach combined with machine learning to characterize the spatiotemporal and multi-domain vulnerability of an urban infrastructure, coined as "co-resilience.'' We performed resilience assessments for combined electricity and transportation networks by considering the meteorological, topographic, and demographic attributes of Tallahassee, Florida after Hurricane Hermine (2016) and Hurricane Michael (2018).

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Co-Mobility: Causal Inference for Complex Multi-Layer Networks

Urban mobility and electricity demand are multidimensional characteristics of city infrastructure including places, people, and information. The emergence of electric vehicles creates even more interdependency between electricity and transportation networks. Therefore, the study of electricity and transportation systems should go beyond an individual network and merge with other networks. However, understanding relationships between driving patterns, electricity demand, weather conditions, and demographics is a complex problem that is out of reach for classic machine learning. We tackle such a complex problem by introducing the "Co-Mobility" concept based on the causal Bayesian multi-network models. We have implemented our framework on actual data from the City of Tallahassee, Florida.

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Team

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Prof. Reza Arghandeh

 

Director, Ci2Lab

Professor in Data Science, Department of Comp Sci. and Elect Eng.

Leader, Data Science Group

Western Norway University of Applied Science (HVL)

Lead Data Scientist, StormGeo 

Current Members

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Dr. Mojtaba Yousefi

Postdoc

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email: Mojtaba.yousefi@hvl.no 

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Michele Gazzea

PhD Student

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email: Michele.Gazzea@hvl.no 

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Atle Føli

MS Student

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email: 150362@stud.hvl.no

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Sindre Aalhus

MS Student

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email: 182037@stud.hvl.no

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Oscar Sommervold

MS Student

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email:Oscar.Sommervold@student.uib.no 

Alumni

Jose Guillen Cordova

Dr. Jose David Cordova

Ph.D. 

Department of Electrical and Computer Engineering

Florida State University

Lalitha Madhavi K.S

Lalitha Madhavi K.S

 

Ph.D.

Department of Electrical and

Computer Engineering

Florida State University

Mostafa Gilanifar

Dr. Mostafa Gilanifar

 

Ph.D. 

Department of Industrial Engineering

Florida State University

Mehmet Baran Ulak

Dr. Mehmet Baran Ulak

Ph.D. 

Department of Civil and Environmental Engineering

 

Florida State University

Andres Sanchez

MS

Department of Electrical and

Computer Eng

 

 Florida State University

 

Ali Sayghe

Ali Sayghe

PhD

Department of Electrical and Computer Engineering

Florida State University

Xiaorui Liu

XiaoRui Liu

MS

Department of Electrical and

Computer Engineering

 

Florida State University

Ayberk Kocatepe

Dr. Ayberk Kocatepe

PhD

Connetics Transportation Group

Donlin Cai

 DongLin Cai

 MS

Dept of Electrical and Computer  Engineering​

 

Florida State University

Hasan H. Karabağ

MS

Department of Civil and

Environmental Engineering

Florida State University

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    Matthias Stifter

      Visiting PhD Student

      Dept of Electrical Engineering​

     

      Technical University of Vienna, 

      Austria

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Mengmeng Xiao

Visiting PhD Student

Dept of Electrical Engineering​

Huazhong University of Science and Technology, China

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    Davide Pinzan

      Visiting MS Student

      Dept of Electrical Engineering​

     

      University of Padova, Italy

    

 

Projects

Transnational Partnership for Excellent Research and Education in Disruptive Technologies for a Resilient Future

Dr. Arghandeh Co-PI, Research Council of Norway, 2020-2022

Satellite Technologies Feasibility Study for Power Lines

Dr. Arghandeh PI, Statnett & StormGeo, 2021-2021

Towards a FAIR and Open Data Ecosystem in the Low Carbon Energy Research Community

Dr. Arghandeh Co-PI, EU HORIZON 2020, 2020-2022

Information Mining with a Span of Fuzzy and Causality Approaches

Dr. Arghandeh Co-PI, the University and College Network for Western Norway, 2019-2020

GridEyeS - Smart Grid Eye, from Space to Sky

Dr. Arghandeh PI, European Space Agency, 2019-2020

IBM Faculty Award, IoT Technology for Smart Buildings

Dr. Arghandeh PI, IBM, 2018-2019

User-Centered Heterogeneous Data Fusion for Multi-Networked City Mobility UHDNetCity

Dr. Arghandeh PI and Dr. Ozguven Co-PI, U.S. National Science Foundation, 2016-2019

Resilient Alaskan Distribution System Improvements using Automation and Energy Storage

Dr. Arghandeh Co-PI, U.S. Department of Energy, 2017-2020

Bridging the Digital Divide for the Well-Being of Aging Populations in Smart Cities

Dr. Arghandeh Partner, U.S. National Science Foundation, 2017-2018

Open-source Distributed Control Platform for HIL-based Testing Advanced Ship Power Systems

Dr. Arghandeh Co-PI, U.S. Office of Naval Research, 2016-2017

High Resolution Monitoring System for Distribution Networks with Micro-Synchrophasors

Dr. Arghandeh PI, Florida State University Office of Research, FYA Program, 2016

Data and Model Integration for Multidimensional System Observability

Dr. Arghandeh PI, Florida State University Office of Research, 2015

 

News

Last updated Sep 2019! A lot of cool things have happened since then; updates coming here soon!

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Aug 2019

The Smart Grid Eye, from Space to Sky (GridEyeS) is funded by the European Space Agency. The overall goal of this study is to create an end to end electric grid monitoring platform using satellite images combined with high-resolution drone data to create multi-layer situational awareness, especially in the case of extreme weather events in the electric grid. 

More info

March 2018

Dr. Arghandeh honored for book publication in Florida State University

Sep 2018

Dr. Arghandeh joined the Western Norway University of Applied Sciences, as the "Big Data and Machine Learning Associate Professor" in the Department of Computing, Mathematics, and Physics.

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January 2018 

Dr. Arghandeh and Dr.Ozguven visit of NASA Challenger Learning Center

and talk on BigData for SmartCities

January 2018 

Dr. Arghandeh's book "Big Data Application in Power System" published by Elsevier

October 2017

Dr. Ozguven, published an article in Tampa Bay Times

 

October 2017

Dr. Ozguven, published an article in Tallahassee Democrat

 

Oct 2017

Dr. Ozguven on WTXL TV talking about our research on Evacuating senior people and their furry friends 

 

Oct 2017

Resilient Distribution Systems Lab Call Awards, Office Of The Under Secretary For Science And Energy, U.S. Department of Energy

 

Oct 2016

Radio Interview," the progression and development of DigiTally", Tallahassee Talk Radio Show.

 

 

Oct 2016

Featured Research,"FSU Team Tackles Urban Mobility In Smart City Era" FSU News.

 

 

Oct 2016

Featured Research," FSU Researchers Transforming Tallahassee Into a Smart City,” Florida Flambeau.

 

 

Jul 2015

News,"EECS postdoc scholar Reza Arghandeh has been selected to receive the 2015 ASME Award"

UC Berkeley.

 

 

Jul 2015

News, "ASME Power Award for FSU New Faculty" FSU College of Engineering Website.

 

 

Jun 2015,

News, " IEEE PES Award for Paper on Data Accuracy for Inverters Control" FSU College of Engineering Website.

 

Publications

For the updated list of publications, please check:
Reza Arghandeh Google Scholars 

Recent Papers:

2021:

Developing city-wide hurricane impact maps using real-life data on infrastructure, vegetation and weather, M Chen, A Karaer, EE Ozguven, T Abichou, R Arghandeh, J Nienhius, Transportation research record 2675 (3), 393-404, 2021

 

Resilience Characterization for Multi-Layer Infrastructure Networks, MB Ulak, LMK Sriram, A Kocatepe, EE Ozguven, R Arghandeh, IEEE Intelligent Transportation Systems Magazine, 2021

 

Automated Power Lines Vegetation Monitoring using High-Resolution Satellite Imagery, M Gazzea, M Pacevicius, DO Dammann, A Sapronova, TM Lunde, R Arghandeh, IEEE Transactions on Power Delivery, 2021

 

Exploring Correlations Between Vehicle Travels and Tropospheric Nitrogen Dioxide (NO2) Density Among Florida Counties Impacted by COVID-19, A Karaer, N Balafkan, M Gazzea, R Arghandeh, EE Ozguven, Transportation Research Board 100th Annual Meeting 2021

 

Post-Hurricanes Roadway Closure Detection using Satellite Imagery and Semi-Supervised Ensemble Learning, M Gazzea, A Karaer, N Balafkan, EE Ozguven, R Arghandeh, Transportation Research Board 100th Annual Meeting 2021

 

Leveraging Remote Sensing Indices for Hurricane-induced Vegetative Debris Assessment: A GIS-based Case Study for Hurricane Michael, A Karaer, B Ulak, T Abichou, R Arghandeh, EE Ozguven, Transportation Research Board 100th Annual Meeting 2021

 

 

CONTACT

Prof. Reza Arghandeh

reza[dot]arghandeh[at]hvl.no