Andrew Hlynka

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Andrew is a research applications developer with a background in artificial intelligence, interactive multimedia and animation. Specific experience includes use of programming languages including C# and Java, research with agent-modeling, Android app development with Android SDK, and game development with popular game engines including Unity3D and Unreal. He can assist with computer programming, agent-based simulation design, and understanding available tools for developing interactive applications or 3D visualizations.

Marcio Mourao

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Márcio’s PhD degree was obtained in partnership with the PhD Program in Computational Biology (PDBC) at the Instituto Gulbenkian de Ciência (IGC).  As part of his PhD specialization in complex systems, he wrote his thesis on “reverse engineering the mechanisms and the dynamical behavior of complex biochemical pathways”. Márcio has taught courses for Mechanical Engineering, Computer Science and Mathematics departments, including MatLab, Calculus and Mathematical Biology. As a mathematical/computational biologist, he has worked on numerous interdisciplinary problems, mostly focused in chemistry, biology and physiology. He has particular expertise in the development and analysis of dynamical systems, primarily using differential equations, and in the development of agent-based models and stochastic simulations.
For more information about Márcio, visit http://albasinimourao.weebly.com/ and https://www.linkedin.com/in/mdamourao

Kerby Shedden

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Kerby has collaborated with researchers in many areas of natural and social science, with a particular focus on studies involving high dimensional biological data, including genomics, biological imaging, statistical genetics, chemical informatics, health outcomes, and medical claims data. He also has extensive experience in software development, primarily in Python and Go.  His research focuses on computational statistics, and methods for modeling complex dependent data including multilevel, longitudinal, and spatial/temporal data.

Koki Sagiyama

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Koki has experience in high-performance computing with emphasis in numerical simulations of time-dependent engineering problems.

His recent interests include machine learning using neural networks and use of deep learning frameworks such as Torch/PyTorch.

Alex Cao

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Alex has more than 14 years of research experience in projects involving medical devices, surgical simulation, human factors testing, tele-operated robotics, Raman spectroscopy, and condition-based maintenance for military helicopters. He has worked for several academic institutions, an aerospace company, a start-up medical device company, and with NASA.