Community

Furkan Gürsoy Member since: Thursday, August 02, 2018 Full Member

Ph.D., Management Information Systems, Boğaziçi University, M.Sc., Data Science, Istanbul Şehir University, B.Sc., Management Information Systems, Boğaziçi University

Furkan Gürsoy received the BS in Management Information Systems from Boğaziçi University, Turkey, and the MS in Data Science from İstanbul Şehir University, Turkey. He is currently a PhD Candidate at Boğaziçi University. He previously worked as an IS/IT Consultant and a Machine Learning Engineer with the industry for several years. He held a Visiting Researcher Position with IMT Atlantique, France, in 2020. His research interests include complex networks, machine learning, simulation, and broad data science.

network science, machine learning, simulation, data science.

Paul Python ndekou tandong Member since: Sunday, March 24, 2019 Full Member

Mathematical modeling
agent-based modeling
coupling of agent-based models and mathematical models
machine learning algorithms
deep learning algorithms
Statistical inference
infectious diseases modeling

Rory Sie Member since: Tuesday, February 11, 2014

dr., MSc.

Mainly interested in studying social networks of learners, teachers, and innovators. Uses Social Network Analysis, but also sentiment analysis, data mining, and recommender system techniques.

Yifei Wang Member since: Saturday, February 25, 2017 Full Member Reviewer

Ph.D in Computing, M.Eng. in Astronautics Engineering, B.Eng. Computer Science & Technology

Tomer Czaczkes Member since: Thursday, December 17, 2015

PhD

Behavioural ecology and modelling of ant behaviour, with an emphasis on understanding how individual-level complexity affects collective decision-making

Peter Hayes Member since: Wednesday, January 04, 2012

BS Electrical Engineering, MS Environmental Studies, MA Economics, PhD Computational Resource Economics (interdisciplinary - in process)

I am investigating the use of machine learning techniques in non-stationary modeling environments to better reproduce aspects of human learning and decision-making in human-natural system simulations.

Eileen Young Member since: Tuesday, September 10, 2019 Full Member

B.S., Liberal Studies, University of Wisconsin - Whitewater, M.S., Disaster Science and Management, University of Delaware

Graduate student in Disaster Science and Management at the University of Delaware.

Kit Martin Member since: Thursday, January 15, 2015 Full Member

B.A. History, Bard College, M.A. International Development Practice Humphrey School of Public Affairs, PhD. Northwestern, Learning Sciences

I have a strong background in building and incorporating agent-based simulations for learning. Throughout my graduate career, I have worked at the Center for Connected Learning and Computer Based Modeling (CCL), developing modeling and simulation tools for learning. In particular, we develop NetLogo, the gold standard agent-based modeling environment for learners around the world. In my dissertation work, I marry biology and computer science to teach the emergent principles of ant colonies foraging for food and expanding. The work builds on more than a decade of experience in ABM. I now work at the Center for the Science and the Schools as an Assistant Professor. We delivered a curriculum to teach about COVID-19, where I incorporated ABMs into the curriculum.

You can keep up with my work at my webpage: https://kitcmartin.com

Studying the negative externalities of networks, and the ways in which those negatives feedback and support the continuities.

Mariam Kiran Member since: Friday, August 17, 2012 Full Member Reviewer

PhD Agent based modelling of economic and social systems, MSc (Eng) Advanced software engineering

Dr. Mariam Kiran is a Research Scientist at LBNL, with roles at ESnet and Computational Research Division. Her current research focuses on deep reinforcement learning techniques and multi-agent applications to optimize control of system architectures such as HPC grids, high-speed networks and Cloud infrastructures.. Her work involves optimization of QoS, performance using parallelization algorithms and software engineering principles to solve complex data intensive problems such as large-scale complex decision-making. Over the years, she has been working with biologists, economists, social scientists, building tools and performing optimization of architectures for multiple problems in their domain.

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